Fundamental Limits of Nonintrusive Load Monitoring

Provided an arbitrary nonintrusive load monitoring (NILM) algorithm, we seek bounds on the probability of distinguishing between scenarios, given an aggregate power consumption signal. We introduce a framework for studying a general NILM algorithm, and analyze the theory in the general case. Then, we specialize to the case where the error is Gaussian. In both cases, we are able to derive upper bounds on the probability of distinguishing scenarios. Finally, we apply the results to real data to derive bounds on the probability of distinguishing between scenarios as a function of the measurement noise, the sampling rate, and the device usage.Comment: Submitted to the 3rd ACM International Conference on High Confidence Networked Systems (HiCoNS

Neural NILM: Deep Neural Networks Applied to Energy Disaggregation

Energy disaggregation estimates appliance-by-appliance electricity consumption from a single meter that measures the whole home's electricity demand. Recently, deep neural networks have driven remarkable improvements in classification performance in neighbouring machine learning fields such as image classification and automatic speech recognition. In this paper, we adapt three deep neural network architectures to energy disaggregation: 1) a form of recurrent neural network called `long short-term memory' (LSTM); 2) denoising autoencoders; and 3) a network which regresses the start time, end time and average power demand of each appliance activation. We use seven metrics to test the performance of these algorithms on real aggregate power data from five appliances. Tests are performed against a house not seen during training and against houses seen during training. We find that all three neural nets achieve better F1 scores (averaged over all five appliances) than either combinatorial optimisation or factorial hidden Markov models and that our neural net algorithms generalise well to an unseen house.Comment: To appear in ACM BuildSys'15, November 4--5, 2015, Seou

Preparation of anti-vicinal amino alcohols: asymmetric synthesis of D-erythro-Sphinganine, (+)-spisulosine and D-ribo-phytosphingosine

Two variations of the Overman rearrangement have been developed for the highly selective synthesis of anti-vicinal amino alcohol natural products. A MOM-ether directed palladium(II)-catalyzed rearrangement of an allylic trichloroacetimidate was used as the key step for the preparation of the protein kinase C inhibitor D-erythro-sphinganine and the antitumor agent (+)-spisulosine, while the Overman rearrangement of chiral allylic trichloroacetimidates generated by asymmetric reduction of an alpha,beta-unsaturated methyl ketone allowed rapid access to both D-ribo-phytosphingosine and L-arabino-phytosphingosine

Ensemble Learning for Low-Level Hardware-Supported Malware Detection

Abstract. Recent work demonstrated hardware-based online malware detection using only low-level features. This detector is envisioned as a first line of defense that prioritizes the application of more expensive and more accurate software detectors. Critical to such a framework is the detection performance of the hardware detector. In this paper, we explore the use of both specialized detectors and ensemble learning tech-niques to improve performance of the hardware detector. The proposed detectors reduce the false positive rate by more than half compared to a single detector, while increasing the detection rate. We also contribute approximate metrics to quantify the detection overhead, and show that the proposed detectors achieve more than 11x reduction in overhead compared to a software only detector (1.87x compared to prior work), while improving detection time. Finally, we characterize the hardware complexity by extending an open core and synthesizing it on an FPGA platform, showing that the overhead is minimal.

The Escherichia coli transcriptome mostly consists of independently regulated modules

Underlying cellular responses is a transcriptional regulatory network (TRN) that modulates gene expression. A useful description of the TRN would decompose the transcriptome into targeted effects of individual transcriptional regulators. Here, we apply unsupervised machine learning to a diverse compendium of over 250 high-quality Escherichia coli RNA-seq datasets to identify 92 statistically independent signals that modulate the expression of specific gene sets. We show that 61 of these transcriptomic signals represent the effects of currently characterized transcriptional regulators. Condition-specific activation of signals is validated by exposure of E. coli to new environmental conditions. The resulting decomposition of the transcriptome provides: a mechanistic, systems-level, network-based explanation of responses to environmental and genetic perturbations; a guide to gene and regulator function discovery; and a basis for characterizing transcriptomic differences in multiple strains. Taken together, our results show that signal summation describes the composition of a model prokaryotic transcriptome

Bacterial Distribution in the Rhizosphere of Wild Barley under Contrasting Microclimates

Background: All plants in nature harbor a diverse community of rhizosphere bacteria which can affect the plant growth. Our samples are isolated from the rhizosphere of wild barley Hordeum spontaneum at the Evolution Canyon (‘EC’), Israel. The bacteria which have been living in close relationship with the plant root under the stressful conditions over millennia are likely to have developed strategies to alleviate plant stress. Methodology/Principal Findings: We studied distribution of culturable bacteria in the rhizosphere of H. spontaneum and characterized the bacterial 1-aminocyclopropane-1-carboxylate deaminase (ACCd) production, biofilm production, phosphorus solubilization and halophilic behavior. We have shown that the H. spontaneum rhizosphere at the stressful South Facing Slope (SFS) harbors significantly higher population of ACCd producing biofilm forming phosphorus solubilizing osmotic stress tolerant bacteria. Conclusions/Significance: The long-lived natural laboratory ‘EC ’ facilitates the generation of theoretical testable and predictable models of biodiversity and genome evolution on the area of plant microbe interactions. It is likely that the bacteria isolated at the stressful SFS offer new opportunities for the biotechnological applications in our agro-ecologica

Replacement of α-galactosidase A in Fabry disease: effect on fibroblast cultures compared with biopsied tissues of treated patients

The function and intracellular delivery of enzyme therapeutics for Fabry disease were studied in cultured fibroblasts and in the biopsied tissues of two male patients to show diversity of affected cells in response to treatment. In the mutant fibroblasts cultures, the final cellular level of endocytosed recombinant α-galactosidases A (agalsidases, FabrazymeTM, and ReplagalTM) exceeded, by several fold, the amount in control fibroblasts and led to efficient direct intra-lysosomal hydrolysis of (3H)Gb3Cer. In contrast, in the samples from the heart and some other tissues biopsied after several months of enzyme replacement therapy (ERT) with FabrazymeTM, only the endothelial cells were free of storage. Persistent Gb3Cer storage was found in cardiocytes (accompanied by increase of lipopigment), smooth muscle cells, fibroblasts, sweat glands, and skeletal muscle. Immunohistochemistry of cardiocytes demonstrated, for the first time, the presence of a considerable amount of the active enzyme in intimate contact with the storage compartment. Factors responsible for the limited ERT effectiveness are discussed, namely post-mitotic status of storage cells preventing their replacement by enzyme supplied precursors, modification of the lysosomal system by longstanding storage, and possible relative lack of Sap B. These observations support the strategy of early treatment for prevention of lysosomal storage

Is Bacterial Persistence a Social Trait?

The ability of bacteria to evolve resistance to antibiotics has been much reported in recent years. It is less well-known that within populations of bacteria there are cells which are resistant due to a non-inherited phenotypic switch to a slow-growing state. Although such ‘persister’ cells are receiving increasing attention, the evolutionary forces involved have been relatively ignored. Persistence has a direct benefit to cells because it allows survival during catastrophes–a form of bet-hedging. However, persistence can also provide an indirect benefit to other individuals, because the reduced growth rate can reduce competition for limiting resources. This raises the possibility that persistence is a social trait, which can be influenced by kin selection. We develop a theoretical model to investigate the social consequences of persistence. We predict that selection for persistence is increased when: (a) cells are related (e.g. a single, clonal lineage); and (b) resources are scarce. Our model allows us to predict how the level of persistence should vary with time, across populations, in response to intervention strategies and the level of competition. More generally, our results clarify the links between persistence and other bet-hedging or social behaviours

Prophage Spontaneous Activation Promotes DNA Release Enhancing Biofilm Formation in Streptococcus pneumoniae

Streptococcus pneumoniae (pneumococcus) is able to form biofilms in vivo and previous studies propose that pneumococcal biofilms play a relevant role both in colonization and infection. Additionally, pneumococci recovered from human infections are characterized by a high prevalence of lysogenic bacteriophages (phages) residing quiescently in their host chromosome. We investigated a possible link between lysogeny and biofilm formation. Considering that extracellular DNA (eDNA) is a key factor in the biofilm matrix, we reasoned that prophage spontaneous activation with the consequent bacterial host lysis could provide a source of eDNA, enhancing pneumococcal biofilm development. Monitoring biofilm growth of lysogenic and non-lysogenic pneumococcal strains indicated that phage-infected bacteria are more proficient at forming biofilms, that is their biofilms are characterized by a higher biomass and cell viability. The presence of phage particles throughout the lysogenic strains biofilm development implicated prophage spontaneous induction in this effect. Analysis of lysogens deficient for phage lysin and the bacterial major autolysin revealed that the absence of either lytic activity impaired biofilm development and the addition of DNA restored the ability of mutant strains to form robust biofilms. These findings establish that limited phage-mediated host lysis of a fraction of the bacterial population, due to spontaneous phage induction, constitutes an important source of eDNA for the S. pneumoniae biofilm matrix and that this localized release of eDNA favors biofilm formation by the remaining bacterial population