Qualitative Short-Time (ST) Dynamical Systems Analysis of Changes in Smoke Patterns with Applications to other ST dynamical Systems in Nature

The smoking of a cigarette is an obvious metaphor for the observation of qualitative short-time (ST) dynamical patterns in life as a function of heat, diffusion, and the eventual death of a system of molecules (i.e., see laws of thermodynamics [4]), which includes particles that make up common ingredients in a cigarette, including nicotine, tobacco, and the associated artificial chemicals used to deliver these materials into the blood stream. I use the basic materials associated with smoking a cigarette as a framework for exploring qualitative patterns observed in ST dynamical systems. The actual process of smoking a cigarette was used to test the following hypotheses: (1) Do the patterns of change over time of smoking a cigarette from start to finish demonstrate ST dynamical patterns that can be analyzed with simple time series (TS) analysis tools? (2) Does the qualitative ST dynamical behavior generated from smoking a cigarette follow a predictable pattern? Next, I place my qualitative observations within a quantitative framework. Lastly, I use results obtained from hypotheses (1) and (2) to propose how change over time in qualitative ST dynamical behavior of the simple act of smoking a cigarette can be applied to other experiments, especially experiments examining the qualitative and quantitative ST dynamics of patterns observed in naturally occurring systems

The Color, Power Spectrum, and Hurst Exponent Associated with the Linear and chaotic Nature of Changes in Pitch of Selections of Music By Philip Glass

White noise is what we call random or white colored noise. It is a simple measure of the frequency at which the system changes over time. The color of noise is a measure of the instability (white noise) or probabilistic nature of a system’s dynamics (i.e. white noise is the most unstable random colored noise), whereas, red noise is the most stable, non-random colored noise. In all types of music, changes in the pitch of the music is a proxy for measuring change in the color of noise, and hence, the stability of noise over time. In the following paper, I hypothesize that particular pieces of Philip Glass’s music can be used to measure (qualitatively and quantitatively), linear and chaotic or fractal (unstable) dynamic change in pitch, which can best be qualitatively and quantitatively explored by determining the color and chaotic (or fractal) nature of a particular measure within a composition. I use statistical models and analysis of those models using computer software to test my hypothesis. The models presented here are analogs, which do not explicitly model the pitch patterns ingrained in a measure from a particular Glass composition. Rather, these models are meant to generate the types of patterns one expects Glass’s music to generate. Surprisingly, I found that one of the analog models predicted that a measure of one of Glass’s compositions consisted of both linear and chaotic pitch components, resulting in the generation of a measure with an indefinite pitch (blue color) state, one, whose dynamics are in-between a stable and unstable state. Analysis of each individual note of a measure of a particular composition is not the intent of this paper at this moment in time. Future research the explicitly models pitch dynamics is needed. Lastly, I opine about further application of this approach to quantify the color of noise and associated power spectrum in many other disciplines.&nbsp

Evenness drives consistent diversity effects in intensive grassland systems across 28 European sites

Ecological and agronomic research suggests that increased crop diversity in species-poor intensive systems may improve their provision of ecosystem services. Such general predictions can have critical importance for worldwide food production and agricultural practice but are largely untested at higher levels of diversity. 2We propose new methodology for the design and analysis of experiments to quantify diversity-function relationships. Our methodology can quantify the relative strength of inter-specific interactions that contribute to a functional response, and can disentangle the separate contributions of species richness and relative abundance. 3Applying our methodology to data from a common experiment at 28 European sites, we show that the above-ground biomass of four-species mixtures (two legumes and two grasses) in intensive grassland systems was consistently greater than that expected from monoculture performance, even at high productivity levels. The magnitude of this effect generally resulted in transgressive overyielding. 4A combined analysis of first-year results across sites showed that the additional performance of mixtures was driven by the number and strength of pairwise inter-specific interactions and the evenness of the community. In general, all pairwise interactions contributed equally to the additional performance of mixtures; the grass-grass and legume-legume interactions were as strong as those between grasses and legumes. 5The combined analysis across geographical and temporal scales in our study provides a generality of interpretation of our results that would not have been possible from individual site analyses or experimentation at a single site. 6Our four-species agricultural grassland communities have proved a simple yet relevant model system for experimentation and development of methodology in diversity-function research. Our study establishes that principles derived from biodiversity research in extensive, semi-natural grassland systems are applicable in intensively managed grasslands with agricultural plant species

Social studies of volcanology:Knowledge generation and expert advice on active volcanoes

International audienceThis paper examines the philosophy and evolution of volcanological science in recent years, particularly in relation to the growth of volcanic hazard and risk science. It uses the lens of Science and Technology Studies to examine the ways in which knowledge generation is controlled and directed by social forces, particularly during eruptions, which constitute landmarks in the development of new technologies and models. It also presents data from a survey of volcanologists carried out during late 2008 and early 2009. These data concern the felt purpose of the science according to the volcanologists who participated and their impressions of the most important eruptions in historical time. It demonstrates that volcanologists are motivated both by the academic science environment and by a social concern for managing the impact of volcanic hazards on populations. Also discussed are the eruptions that have most influenced the discipline and the role of scientists in policymaking on active volcanoes. Expertise in volcanology can become the primary driver of public policy very suddenly when a volcano erupts, placing immense pressure on volcanologists. In response, the epistemological foundations of volcanology are on the move, with an increasing volume of research into risk assessment and management. This requires new, integrated methodologies for knowledge collection that transcend scientific disciplinary boundaries

Immunometabolic Signatures Predict Risk of Progression to Active Tuberculosis and Disease Outcome

Immunogenetics and cellular immunology of bacterial infectious disease