In this paper, we propose and evaluate the application of unsupervised machine learning to anomaly detection for a Cyber-Physical System (CPS). We compare two methods: Deep Neural Networks (DNN) adapted to time series data generated by a CPS, and one-class Support Vector Machines (SVM). These methods are evaluated against data from the Secure Water Treatment (SWaT) testbed, a scaled-down but fully operational raw water purification plant. For both methods, we first train detectors using a log generated by SWaT operating under normal conditions. Then, we evaluate the performance of both methods using a log generated by SWaT operating under 36 different attack scenarios. We find that our DNN generates fewer false positives than our one-class SVM while our SVM detects slightly more anomalies. Overall, our DNN has a slightly better F measure than our SVM. We discuss the characteristics of the DNN and one-class SVM used in this experiment, and compare the advantages and disadvantages of the two methods.

Diazotrophs had not previously been identified among bacterial species in the phylum Bacteroidetes until the rapid expansion of bacterial genome sequences, which revealed the presence of nitrogen fixation (nif) genes in this phylum. We herein determined the draft genome sequences of Bacteroides graminisolvens JCM 15093T and Geofilum rubicundum JCM 15548T. In addition to these and previously reported ‘Candidatus Azobacteroides pseudotrichonymphae’ and Paludibacter propionicigenes, an extensive survey of the genome sequences of diverse Bacteroidetes members revealed the presence of a set of nif genes (nifHDKENB) in strains of Dysgonomonas gadei, Dysgonomonas capnocytophagoides, Saccharicrinis fermentans, and Alkaliflexus imshenetskii. These eight species belonged to and were distributed sporadically within the order Bacteroidales. Acetylene reduction activity was detected in the five species examined, strongly suggesting their diazotrophic nature. Phylogenetic analyses showed monophyletic clustering of the six Nif protein sequences in the eight Bacteroidales species, implying that nitrogen fixation is ancestral to Bacteroidales and has been retained in these species, but lost in many other lineages. The identification of nif genes in Bacteroidales facilitates the prediction of the organismal origins of related sequences directly obtained from various environments.

It has been hypothesized that nitrogen fixation occurs in the human gut. However, whether the gut microbiota truly has this potential remains unclear. We investigated the nitrogen-fixing activity and diversity of the nitrogenase reductase (NifH) genes in the faecal microbiota of humans, focusing on Papua New Guinean and Japanese individuals with low to high habitual nitrogen intake. A 15N2 incorporation assay showed significant enrichment of 15N in all faecal samples, irrespective of the host nitrogen intake, which was also supported by an acetylene reduction assay. The fixed nitrogen corresponded to 0.01% of the standard nitrogen requirement for humans, although our data implied that the contribution in the gut in vivo might be higher than this value. The nifH genes recovered in cloning and metagenomic analyses were classified in two clusters: one comprising sequences almost identical to Klebsiella sequences and the other related to sequences of Clostridiales members. These results are consistent with an analysis of databases of faecal metagenomes from other human populations. Collectively, the human gut microbiota has a potential for nitrogen fixation, which may be attributable to Klebsiella and Clostridiales strains, although no evidence was found that the nitrogen-fixing activity substantially contributes to the host nitrogen balance.

In this paper, we study the inequality indices for some models of wealth exchange. We calculated Gini index and newly introduced k-index and compare the results with reported empirical data available for different countries. We have found lower and upper bounds for the indices and discuss the efficiencies of the models. Some exact analytical calculations are given for a few cases. We also exactly compute the quantities for Gamma and double Gamma distributions.

Fibroblasts from emphysematous lungs had lower proliferative activity and were more susceptible to cigarette smoke than those from non-emphysematous lungs. Cigarette smoke may play a critical role in the development and deterioration of pulmonary emphysema by suppressing the growth of lung fibroblasts.