An empirical evaluation of imbalanced data strategies from a practitioner's point of view

This research tested the following well known strategies to deal with binary imbalanced data on 82 different real life data sets (sampled to imbalance rates of 5%, 3%, 1%, and 0.1%): class weight, SMOTE, Underbagging, and a baseline (just the base classifier). As base classifiers we used SVM with RBF kernel, random forests, and gradient boosting machines and we measured the quality of the resulting classifier using 6 different metrics (Area under the curve, Accuracy, F-measure, G-mean, Matthew's correlation coefficient and Balanced accuracy). The best strategy strongly depends on the metric used to measure the quality of the classifier. For AUC and accuracy class weight and the baseline perform better; for F-measure and MCC, SMOTE performs better; and for G-mean and balanced accuracy, underbagging

A framework for human microbiome research

A variety of microbial communities and their genes (the microbiome) exist throughout the human body, with fundamental roles in human health and disease. The National Institutes of Health (NIH)-funded Human Microbiome Project Consortium has established a population-scale framework to develop metagenomic protocols, resulting in a broad range of quality-controlled resources and data including standardized methods for creating, processing and interpreting distinct types of high-throughput metagenomic data available to the scientific community. Here we present resources from a population of 242 healthy adults sampled at 15 or 18 body sites up to three times, which have generated 5,177 microbial taxonomic profiles from 16S ribosomal RNA genes and over 3.5 terabases of metagenomic sequence so far. In parallel, approximately 800 reference strains isolated from the human body have been sequenced. Collectively, these data represent the largest resource describing the abundance and variety of the human microbiome, while providing a framework for current and future studies

The effect of the integration interval on the measurement accuracy of RMS values and powers in systems with nonsinusoidal waveforms

In this paper the possibility of errors in the measurement of average values (in particular rms values or active powers) in power systems under nonsinusoidal conditions are discussed. The errors considered are either due to the fact that the measurement time interval is not an exact multiple of the fundamental period of the voltage and current signals, or due to the presence of interharmonics or subharmonics. The errors are calculated and the results are illustrated by means of simple examples

Fractal Strings and Multifractal Zeta Functions

For a Borel measure on the unit interval and a sequence of scales that tend to zero, we define a one-parameter family of zeta functions called multifractal zeta functions. These functions are a first attempt to associate a zeta function to certain multifractal measures. However, we primarily show that they associate a new zeta function, the topological zeta function, to a fractal string in order to take into account the topology of its fractal boundary. This expands upon the geometric information garnered by the traditional geometric zeta function of a fractal string in the theory of complex dimensions. In particular, one can distinguish between a fractal string whose boundary is the classical Cantor set, and one whose boundary has a single limit point but has the same sequence of lengths as the complement of the Cantor set. Later work will address related, but somewhat different, approaches to multifractals themselves, via zeta functions, partly motivated by the present paper.Comment: 32 pages, 9 figures. This revised version contains new sections and figures illustrating the main results of this paper and recent results from others. Sections 0, 2, and 6 have been significantly rewritte

Natural regulatory (CD4+CD25+FOXP+) T cells control the production of pro-inflammatory cytokines during Plasmodium chabaudi adami infection and do not contribute to immune evasion.

Different functions have been attributed to natural regulatory CD4+CD25+FOXP+ (Treg) cells during malaria infection. Herein, we assessed the role for Treg cells during infections with lethal (DS) and non-lethal (DK) Plasmodium chabaudi adami parasites, comparing the levels of parasitemia, inflammation and anaemia. Independent of parasite virulence, the population of splenic Treg cells expanded during infection, and the absolute numbers of activated CD69+ Treg cells were higher in DS-infected mice. In vivo depletion of CD25+ T cells, which eliminated 80% of CD4+FOXP3+CD25+ T cells and 60–70% of CD4+FOXP3+ T cells, significantly decreased the number of CD69+ Treg cells in mice with lethal malaria. As a result, higher parasite burden and morbidity were measured in the latter, whereas the kinetics of infection with non-lethal parasites remained unaffected. In the absence of Treg cells, parasite-specific IFN-γ responses by CD4+ T cells increased significantly, both in mice with lethal and non-lethal infections, whereas IL-2 production was only stimulated in mice with non-lethal malaria. Following the depletion of CD25+ T cells, the production of IL-10 by CD90− cells was also enhanced in infected mice. Interestingly, a potent induction of TNF- and IFN-γ production by CD4+ and CD90− lymphocytes was measured in DS-infected mice, which also suffered severe anaemia earlier than non-depleted infected controls. Taken together, our data suggest that the expansion and activation of natural Treg cells represent a counter-regulatory response to the overwhelming inflammation associated with lethal P.c. adami. This response to infection involves TH1 lymphocytes as well as cells from the innate immune system