Inferring Personal Information from Demand-Response Systems

Current and upcoming demand-response systems provide increasingly detailed power-consumption data to utilities and a growing array of players angling to assist consumers in understanding and managing their energy use. The granularity of this data, as well as new players' entry into the energy market, creates new privacy concerns. The detailed per-household consumption data that advanced metering systems generate reveals information about in-home activities that such players can mine and combine with other readily available information to discover more about occupants' activities. The authors explore the technological aspects of this claim, focusing on the ways in which personally identifying information can be collected and repurposed. Their results show that, even with relatively unsophisticated hardware and data-extraction algorithms, some information about occupant behavior can be estimated with a high degree of accuracy. The authors propose a disclosure metric to aid in quantifying the impact of data collection on in-home privacy and construct an example metric for their experiment.     

Adaptive decoding for brain-machine interfaces through Bayesian parameter updates

Brain-machine interfaces (BMIs) transform the activity of neurons recorded in motor areas of the brain into movements of external actuators. Representation of movements by neuronal populations varies over time, during both voluntary limb movements and movements controlled through BMIs, due to motor learning, neuronal plasticity, and instability in recordings. To ensure accurate BMI performance over long time spans, BMI decoders must adapt to these changes. We propose the Bayesian regression self-training method for updating the parameters of an unscented Kalman filter decoder. This novel paradigm uses the decoder's output to periodically update its neuronal tuning model in a Bayesian linear regression. We use two previously known statistical formulations of Bayesian linear regression: a joint formulation, which allows fast and exact inference, and a factorized formulation, which allows the addition and temporary omission of neurons from updates but requires approximate variational inference. To evaluate these methods, we performed offline reconstructions and closed-loop experiments with rhesus monkeys implanted cortically with microwire electrodes. Offline reconstructions used data recorded in areas M1, S1, PMd, SMA, and PP of three monkeys while they controlled a cursor using a handheld joystick. The Bayesian regression self-training updates significantly improved the accuracy of offline reconstructions compared to the same decoder without updates. We performed 11 sessions of real-time, closed-loop experiments with a monkey implanted in areas M1 and S1. These sessions spanned 29 days. The monkey controlled the cursor using the decoder with and without updates. The updates maintained control accuracy and did not require information about monkey hand movements, assumptions about desired movements, or knowledge of the intended movement goals as training signals. These results indicate that Bayesian regression self-training can maintain BMI control accuracy over long periods, making clinical neuroprosthetics more viable.     

Pattern matching in the Hamming distance with thresholds

It has long been known that pattern matching in the Hamming distance metric can be done in time, where n is the length of the text, m is the length of the pattern, and Σ is the alphabet. The classic algorithm for this is due to Abrahamson and Kosaraju. This paper considers the following generalization, motivated by the situation where the entries in the text and pattern are analog, or distorted by additive noise, or imprecisely given for some other reason: in any alignment of the pattern with the text, two aligned symbols a and b contribute +1 to the similarity score if they differ by no more than a given threshold θ, otherwise they contribute zero. We give an time algorithm for this more general version of the problem; the classic Hamming distance matching problem is the special case of θ=0.     

Fluorescence lifetime imaging of coral fluorescent proteins

Corals, like many other coelenterates, contain fluorescent pigments that show considerable homology with the well known green fluorescent protein of the jellyfish Aequoria. In corals, unlike jellyfish, multiple proteins are present and the range of excitations and emissions suggest the possibility of energy transfer. The occurrence of F?rster resonant energy transfer (FRET) between fluorescent proteins in corals has already been reported and time-resolved spectra have shown the effect on fluorescent lifetime, but without any spatial resolution. Lifetime confocal microscopy offers lower time resolution but excellent spatial resolution. Lifetimes of the isolated A. millepora pigments amilFP490, amilFP504, and amilFP593 (names indicate emission peaks) were 2.8, 2.9, and 2.9 ns, respectively. In the coral sample, imaging the entire emission spectrum from 420 nm, the mean lifetime was reduced to 1.5 ns, implying that FRET was occurring. Looking just at the fluorescence from FRET donors the lifetime was even shorter, at 1.3 ns, supporting this interpretation. In contrast, no reduction in lifetime is seen in the coral Euphyllia ancora, where the pigment distribution also suggests that the pigments are unlikely to be involved in photoprotection. This study set out to determine the extent of FRET between pigments in two corals, Acropora millepora and Euphyllia, ancora which differ in the arrangement of their pigments and hence possibly in pigment function.     

Prerequisites for offering ultrasound services in general practice]

In the course of the past few years, sonography has become firmly established in clinical practice. The accuracy of the investigations does not only depend on the quality of the equipment used but also to a considerable degree on the standards of investigator training. To reduce the discrepancy between the number and quality of the investigations in the German Federal Republic, the "Kassen?rztliche Vereinigung" has released guidelines requiring the users of sonographic equipment to undergo theoretical and practical training. These guidelines are reviewed and commented.     

The organization and postnatal development of the commissural projection of the rat somatic sensory cortex

Anterograde and retrograde tracing experiments have been used to demonstrate the origin and terminal distribution of commissural fibers in the first somatosensory cortex (SI) of the rat. The commissural fibers originate from pyramidal cells of all layers, but predominantly from layers III and V. The fibers terminate in a series of approximately vertical bands. In each of these there are concentrations of terminals extending from the inner portion of the molecular layer to the deep portion of layer III as well as in the superficial part of layer V, and in layer VI. Discrete vertical bands of cortex are reciprocally connected across the midline to give both the origin and terminal regions of the projection a patchy or "columnar" appearance. The commissural fibers arise from and terminate in areas of the cortex that lie between and alongside the aggregations of granule cells that distinguish SI of the rat. No commissural fibers terminate within the aggregations of layer IV cells themselves but the more superficial terminal ramifications may come to overlie these aggregations. A heterotopic projection to the contralateral second somatosensory cortex has been observed and is similar in form to the homotopic projection to SI. Many commissural fibers have crossed the midline in the corpus callosum by the day of birth but lie in the underlying white matter and do not enter the cortical plate until at least the third postnatal day. During the first postnatal week these fibers grow somewhat diffusely into the maturing cortex and their topographic and laminar pattern of distribution attains its adult characteristics by the end of the first week. Commissural axons, thus, arise from immature cells but the maturation of cell form seems to precede the ingrowth of these axons and the acquisition of commissural synapses.     

GPR55 Receptor Activation by the N-Acyl Dopamine Family Lipids Induces Apoptosis in Cancer Cells via the Nitric Oxide Synthase (nNOS) Over-Stimulation

GPR55 is a GPCR of the non-CB1/CB2 cannabinoid receptor family, which is activated by lysophosphatidylinositol (LPI) and stimulates the proliferation of cancer cells. Anandamide, a bioactive lipid endocannabinoid, acts as a biased agonist of GPR55 and induces cancer cell death, but is unstable and psychoactive. We hypothesized that other endocannabinoids and structurally similar compounds, which are more hydrolytically stable, could also induce cancer cell death via GPR55 activation. We chemically synthesized and tested a set of fatty acid amides and esters for cell death induction via GPR55 activation. The most active compounds appeared to be N-acyl dopamines, especially N-docosahexaenoyl dopamine (DHA-DA). Using a panel of cancer cell lines and a set of receptor and intracellular signal transduction machinery inhibitors together with cell viability, Ca²⁺, NO, ROS (reactive oxygen species) and gene expression measurement, we showed for the first time that for these compounds, the mechanism of cell death induction differed from that published for anandamide and included neuronal nitric oxide synthase (nNOS) overstimulation with concomitant oxidative stress induction. The combination of DHA-DA with LPI, which normally stimulates cancer proliferation and is increased in cancer setting, had an increased cytotoxicity for the cancer cells indicating a therapeutic potential.