Modeling natural sounds with modulation cascade processes

Natural sounds are structured on many time-scales. A typical segment of speech, for example, contains features that span four orders of magnitude: Sentences ($\sim1$s); phonemes ($\sim10$−$1$ s); glottal pulses ($\sim 10$−$2$s); and formants ($\sim 10$−$3$s). The auditory system uses information from each of these time-scales to solve complicated tasks such as auditory scene analysis [1]. One route toward understanding how auditory processing accomplishes this analysis is to build neuroscience-inspired algorithms which solve similar tasks and to compare the properties of these algorithms with properties of auditory processing. There is however a discord: Current machine-audition algorithms largely concentrate on the shorter time-scale structures in sounds, and the longer structures are ignored. The reason for this is two-fold. Firstly, it is a difficult technical problem to construct an algorithm that utilises both sorts of information. Secondly, it is computationally demanding to simultaneously process data both at high resolution (to extract short temporal information) and for long duration (to extract long temporal information). The contribution of this work is to develop a new statistical model for natural sounds that captures structure across a wide range of time-scales, and to provide efficient learning and inference algorithms. We demonstrate the success of this approach on a missing data task.

Self-assembled multilayer graphene oxide membrane and carbon nanotubes synthesized using a rare form of natural graphite

The fabrication of flexible multilayer graphene oxide (GO) membrane and carbon nanotubes (CNTs) using a rare form of high-purity natural graphite, vein graphite, is reported for the first time. Graphite oxide is synthesized using vein graphite following Hummer's method. By facilitating functionalized graphene sheets in graphite oxide to self-assemble, a multilayer GO membrane is fabricated. Electric arc discharge is used to synthesis CNTs from vein graphite. Both multilayer GO membrane and CNTs are investigated using microscopy and spectroscopy experiments, i.e., scanning electron microscopy (SEM), atomic force microscopy (AFM), high-resolution transmission electron microscopy (HRTEM), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), thermogravimetric analysis (TGA), core level photoelectron spectroscopy, and C K-edge X-ray absorption spectroscopy (NEXAFS), to characterize their structural and topographical properties. Characterization of vein graphite using different techniques reveals that it has a large number of crystallites, hence the large number of graphene sheets per crystallite, preferentially oriented along the (002) plane. NEXAFS and core level spectra confirm that vein graphite is highly crystalline and pure. Fourier transform infrared (FT-IR) and C 1s core level spectra show that oxygen functionalities (-C-OH, -CO,-C-O-C-) are introduced into the basal plane of graphite following chemical oxidation. Carbon nanotubes are produced from vein graphite through arc discharge without the use of any catalyst. HRTEM confirm that multiwalled carbon nanotube (MWNTs) are produced with the presence of some structure in the central pipe. A small percentage of single-walled nanotubes (SWNTs) are also produced simultaneously with MWNTs. Spectroscopic and microscopic data are further discussed here with a view to using vein graphite as the source material for the synthesis of carbon nanomaterials. © 2013 American Chemical Society.

Natural frequency and damping ratio of a vertically vibrated surface foundation

It is possible and common to obtain equivalent natural frequency and damping for a soil-foundation system from results of experimental or numerical analysis assuming the system has a single degree of freedom. Three approaches to extract natural frequency and damping were applied to the vertically vibrated soil-foundation system. The sensitivity of the computed natural frequency and damping to the soil properties was evaluated through parametric studies. About 10-20% of discrepancy in values of natural frequency was observed due to different approaches. The results help to assess the reliability of equivalent soil properties determined from the reported natural frequency of the system. Finally the results obtained using theoretical predictions with linear soil properties measured in situ were compared to those calculated from experimental data. The prediction and experimental results showed good agreements if the embedment of the foundation is neglected with stepped sine test but considered with impulse test. © 2010 Elsevier Ltd.

Unified compression model for venice lagoon natural silts

Over the last 50 years, the city of Venice, Italy, has observed a significant increase in the frequency of flooding. Numerous engineering solutions have been proposed, including the use of movable gates located at the three lagoon inlets. A key element in the prediction of performance is the estimation of settlements of the foundation system of the gates. The soils of Venice Lagoon are characterized by very erratic depositional patterns of clayey silts, resulting in an extremely heterogeneous stratigraphy with discontinuous layering. The soils are also characterized by varying contents of coarse and fine-grained particles. In contrast, the mineralogical composition of these deposits is quite uniform, which allows us to separate the influence of mineralogy from that of grain size distribution. A comprehensive geotechnical testing program was performed to assess the one-dimensional compression of Venice soils and examine the factors affecting the response in the transition from one material type to another. The compressibility of these natural silty clayey soils can be described by a single set of constitutive laws incorporating the relative fraction of granular to cohesive material. © 2007 ASCE.

Plasma biochemical responses of the planktivorous filter-feeding silver carp (Hypophthalmichthys molitrix) and bighead carp (Aristichthys nobilis) to prolonged toxic cyanobacterial blooms in natural waters

The planktivorous filter-feeding silver carp (Hypophthalmichthys molitrix) and bighead carp (Aristichthys nobilis) are the attractive candidates for bio-control of plankton communities to eliminate odorous populations of cyanobacteria. However, few studies focused on the health of such fishes in natural water body with vigorous toxic blooms. Blood parameters are useful and sensitive for diagnosis of diseases and monitoring of the physiological status of fish exposed to toxicants. To evaluate the impact of toxic cyanobacterial blooms on the planktivorous fish, 12 serum chemistry variables were investigated in silver carp and bighead carp for 9 months, in a large net cage in Meiliang Bay, a hypereutrophic region of Lake Taihu. The results confirmed adverse effects of cyanobacterial blooms on two phytoplanktivorous fish, which mainly characterized with potential toxicogenomic effects and metabolism disorders in liver, and kidney dysfunction. In addition, cholestasis was intensively implied by distinct elevation of all four related biomarkers (ALP, GGT, DBIL, TBIL) in bighead carp. The combination of LDH, AST activities and DBIL, URIC contents for silver carp, and the combination of ALT. ALP activities and TBIL, DBIL. URIC concentrations for bighead carps were found to most strongly indicate toxic effects from cyanobacterial blooms in such fishes by a multivariate discriminant analysis. (C) 2009 Elsevier B.V. All rights reserved.

The role of cell-surface-bound phosphatases in species competition within natural phytoplankton assemblage: an in situ experiment

Despite it is widely acknowledged that the ability to hydrolyze dissolved organic matter using extracellular phosphatases is diverse in fresh water phytoplankton, the competition within single species related to presence and quantity of cell-surface-bound phosphatases has not been examined in natural conditions yet. Here, we studied phytoplankton species competition in a freshwater reservoir during an in situ experiment. A natural plankton community, with the exclusion of large zooplankton, was enclosed in permeable dialysis bags inside two large containers of different bioavailable phosphate concentrations. Phytoplankton species biomass and the abundance of bacteria were determined in purpose to compare the development of enclosed microbial communities. Total and cell-surface-bound phosphatase activities in the phytoplankton were investigated using the Fluorescently Labelled Enzyme Activity (FLEA) technique that allows for direct microscopic detection of phosphatase-positive cells and, with image cytometry, enables quantification of phosphatase hydrolytic capacity. Production of extracellular phosphatases was not completely inhibited or stopped in the phosphate-enriched environment, phytoplankton cells only showed the activity less often. Under the phosphate-nonenriched conditions, the production of phosphatases was enhanced, but active species did not proliferate amongst phytoplankton assemblage. Further, specific growth rates of the phosphatase-positive species in the non-enriched environment were lower than the same phosphatase-positive species in phosphate-enriched environment. Interestingly, the phosphatase-positive cells of Ankyra ancora increased their size in both treatments equally, although the population in phosphate-enriched environment grew much faster and the cell-specific phosphatase activity was lower. We hypothesize that brand new daughter cells had sufficient phosphorus reserves and therefore did not employ extracellular phosphatases until they matured and needed extra bioavailable phosphorus to support their metabolism before cell division. Based on presented in situ experiment, we propose that the ability to hydrolyze organic polymers and particles with cell-surface-hound phosphatases is advantageous for longer persistence of given population in a phosphate-scarce environment; although phosphatase-positive species cannot dominate the reservoir phytoplankton solely because of specific phosphorus-scavenging strategy.

Automatic construction and natural-language description of nonparametric regression models

Copyright © 2014, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. This paper presents the beginnings of an automatic statistician, focusing on regression problems. Our system explores an open-ended space of statistical models to discover a good explanation of a data set, and then produces a detailed report with figures and natural- language text. Our approach treats unknown regression functions non- parametrically using Gaussian processes, which has two important consequences. First, Gaussian processes can model functions in terms of high-level properties (e.g. smoothness, trends, periodicity, changepoints). Taken together with the compositional structure of our language of models this allows us to automatically describe functions in simple terms. Second, the use of flexible nonparametric models and a rich language for composing them in an open-ended manner also results in state- of-the-art extrapolation performance evaluated over 13 real time series data sets from various domains.