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

Full-scale testing, production and cost analysis data for the advanced composite stabilizer for Boeing 737 aircraft, volume 2

The development, testing, production activities, and associated costs that were required to produce five-and-one-half advanced-composite stabilizer shipsets for Boeing 737 aircraft are defined and discussed

Modelling Emergent Patterns of Dynamic Desert Ecosystems

In many desert ecosystems vegetation is both patchy and dynamic: vegetated areas are interspersed with patches of bare ground, and both the positioning and the species composition of the vegetated areas exhibit change through time. These characteristics lead to the emergence of multi-scale patterns in vegetation that arise from complex relationships between plants, soils and transport processes. Previous attempts to probe the causes of spatial complexity and predict responses of desert ecosystems tend to be limited in their focus: models of dynamics have been developed with no consideration of the inherent patchiness in the vegetation, or else models have been developed to generate patterns with no consideration of the dynamics. Here we develop a general modelling framework for the analysis of ecosystem change in deserts that is rooted in the concept of connectivity and is derived from a detailed process-based understanding. We explicitly consider spatial interactions among multiple vegetation types and multiple resources, and our model is formulated to predict responses to a variety of endogenous and exogenous disturbances. The model is implemented in the deserts of the American Southwest both to test hypotheses of the causes of the invasion of woody shrubs, and to test its ability to reproduce 16 observed spatial differences in response to drought in the twentieth century. The model’s performance leads us to argue that vertical and lateral connectivity are key emergent properties of the ecosystem, which both control its behaviour and provide indicators of its state. If this argument is shown to be compatible with field observations, the model presented here will provide a more certain approach towards preventing further degradation of semi-arid grasslands. http://www.esajournals.org/doi/pdf/10.1890/12-1253.

Energetics of the primary electron transfer reaction revealed by ultrafast spectroscopy on modified bacterial reaction centers

The modification of reaction centers from Rhodobacter sphaeroides by the introduction of pheophytins instead of bacteriopheophytins leads to interesting changes in the primary photosynthetic reaction: long-living populations of the excited electronic state of the special pair P* and the bacteriochlorophyll anion B−A show up. The data allow the determination of the energetics in the reaction center. The free energy of the first intermediate P+B−A, where the electron has reached the accessory bacteriochlorophyll BA lies ≈ 450 cm−1 below the initially excited special pair P*

Mitochondrial DNA footprints from Western Eurasia in modern Mongolia

Mongolia is located in a strategic position at the eastern edge of the Eurasian Steppe. Nomadic populations moved across this wide area for millennia before developing more sedentary communities, extended empires, and complex trading networks, which connected western Eurasia and eastern Asia until the late Medieval period. We provided a fine-grained portrait of the mitochondrial DNA (mtDNA) variation observed in present-day Mongolians and capable of revealing gene flows and other demographic processes that took place in Inner Asia, as well as in western Eurasia. The analyses of a novel dataset (N = 2,420) of mtDNAs highlighted a clear matrilineal differentiation within the country due to a mixture of haplotypes with eastern Asian (EAs) and western Eurasian (WEu) origins, which were differentially lost and preserved. In a wider genetic context, the prevalent EAs contribution, larger in eastern and central Mongolian regions, revealed continuous connections with neighboring Asian populations until recent times, as attested by the geographically restricted haplotype-sharing likely facilitated by the Genghis Khan’s so-called Pax Mongolica. The genetic history beyond the WEu haplogroups, notably detectable on both sides of Mongolia, was more difficult to explain. For this reason, we moved to the analysis of entire mitogenomes (N = 147). Although it was not completely possible to identify specific lineages that evolved in situ, two major changes in the effective (female) population size were reconstructed. The more recent one, which began during the late Pleistocene glacial period and became steeper in the early Holocene, was probably the outcome of demographic events connected to western Eurasia. The Neolithic growth could be easily explained by the diffusion of dairy pastoralism, as already proposed, while the late glacial increase indicates, for the first time, a genetic connection with western Eurasian refuges, as supported by the unusual high frequency and internal sub-structure in Mongolia of haplogroup H1, a well-known post-glacial marker in Europe. Bronze Age events, without a significant demographic impact, might explain the age of some mtDNA haplogroups. Finally, a diachronic comparison with available ancient mtDNAs made it possible to link six mitochondrial lineages of present-day Mongolians to the timeframe and geographic path of the Silk Route

Morphological characteristics of motor neurons do not determine their relative susceptibility to degeneration in a mouse model of severe spinal muscular atrophy

Spinal muscular atrophy (SMA) is a leading genetic cause of infant mortality, resulting primarily from the degeneration and loss of lower motor neurons. Studies using mouse models of SMA have revealed widespread heterogeneity in the susceptibility of individual motor neurons to neurodegeneration, but the underlying reasons remain unclear. Data from related motor neuron diseases, such as amyotrophic lateral sclerosis (ALS), suggest that morphological properties of motor neurons may regulate susceptibility: in ALS larger motor units innervating fast-twitch muscles degenerate first. We therefore set out to determine whether intrinsic morphological characteristics of motor neurons influenced their relative vulnerability to SMA. Motor neuron vulnerability was mapped across 10 muscle groups in SMA mice. Neither the position of the muscle in the body, nor the fibre type of the muscle innervated, influenced susceptibility. Morphological properties of vulnerable and disease-resistant motor neurons were then determined from single motor units reconstructed in Thy.1-YFP-H mice. None of the parameters we investigated in healthy young adult mice - including motor unit size, motor unit arbor length, branching patterns, motor endplate size, developmental pruning and numbers of terminal Schwann cells at neuromuscular junctions - correlated with vulnerability. We conclude that morphological characteristics of motor neurons are not a major determinant of disease-susceptibility in SMA, in stark contrast to related forms of motor neuron disease such as ALS. This suggests that subtle molecular differences between motor neurons, or extrinsic factors arising from other cell types, are more likely to determine relative susceptibility in SMA

Origin of spectral broadening in pi-conjugated amorphous semiconductors

We present a study of the picosecond fluorescence dynamics of pi-conjugated semiconducting organic dendrimers in the solid state. By varying the degree of branching within the dendrons, referred to as the dendrimer generation, a control of intermolecular spacing of the emissive core and therefore of the lattice parameter for Forster-type energy transfer is achieved. This allows a distinction between spectral diffusion and excimer formation as the two main sources of spectral broadening in organic semiconductors. Whereas Forster-type dispersive spectral relaxation is independent of temperature but strongly dependent on the interchromophore distance, excimer formation is also strongly thermally activated due to temperature-dependent conformational changes and the influence of thermally activated dynamic disorder. The rapid spectral diffusion allows a determination of the excimer rise in the emission, which is shown to have a profound impact on the steady state luminescence properties of dendrimer films. We show that the dendrimer generation not only allows a microscopic control of intermolecular interactions but also a direct control of the rate of spectral diffusion. Implications for the design of novel materials for optoelectronic devices are discussed

Tetrahedrally bonded ternary amorphous semiconductor alloys

The properties of tetrahedrally bonded ternary amorphous semiconductors a-CSiSn:H and a-CSiGe:H are reviewed with particular emphasis on the temperature dependence of dark conductivity and the coordination in random networks. It is shown here that the dark conductivity as a function of the temperature strongly depends on the carbon content and, more precisely, on the proportion of sp3 and sp2 sites in the carbon. Ternary alloys with different carbon contents are compared to binary alloys using the average coordination number. The ternary alloys have an average coordination number close to the optimal value predicted for amorphous covalent networks

Photon echo studies of photosynthetic light harvesting

The broad linewidths in absorption spectra of photosynthetic complexes obscure information related to their structure and function. Photon echo techniques represent a powerful class of time-resolved electronic spectroscopy that allow researchers to probe the interactions normally hidden under broad linewidths with sufficient time resolution to follow the fastest energy transfer events in light harvesting. Here, we outline the technical approach and applications of two types of photon echo experiments: the photon echo peak shift and two-dimensional (2D) Fourier transform photon echo spectroscopy. We review several extensions of these techniques to photosynthetic complexes. Photon echo peak shift spectroscopy can be used to determine the strength of coupling between a pigment and its surrounding environment including neighboring pigments and to quantify timescales of energy transfer. Two-dimensional spectroscopy yields a frequency-resolved map of absorption and emission processes, allowing coupling interactions and energy transfer pathways to be viewed directly. Furthermore, 2D spectroscopy reveals structural information such as the relative orientations of coupled transitions. Both classes of experiments can be used to probe the quantum mechanical nature of photosynthetic light-harvesting: peak shift experiments allow quantification of correlated energetic fluctuations between pigments, while 2D techniques measure quantum beating directly, both of which indicate the extent of quantum coherence over multiple pigment sites in the protein complex. The mechanistic and structural information obtained by these techniques reveals valuable insights into the design principles of photosynthetic light-harvesting complexes, and a multitude of variations on the methods outlined here