Effects of Australian Economic Activities on Waste Generation and Treatment

Understanding the relationships between the Australian economic system and waste generation from intermediate sectors and households is a prerequisite for planning and implementing waste management strategies at a national scale. Data of waste generation accounts link to those of national economic accounts. However, in Australia, some years’ data are absent and so these links cannot be made. To rectify this data gap, this paper interpolates and extrapolates the Australian input-output table (IOT) of 2010–2011. Waste input-output (WIO) analysis is then used to assess the effects of the Australian economy on waste generation and treatment between 2009–2010 and 2010–2011. Analysis indicated that the result of interpolation was more reasonable than that of extrapolation, and the interpolation of the Australian IOT of 2010–2011 can be applicable. This comparative analysis of the time series data in WIO model has identified that: (1) per million $AUD of output of the Construction sector generated the most amount of direct and total waste during the period; (2) the relationships between the development of Australian economy and waste generation illustrate that the Australian economy is currently a traditional linear economy; (3) the effectiveness of waste-related policies are shown by the growth of the sums of direct and total effects of intermediate sectors on the Recovery sector; and (4) the amount of waste generated by households increased sharply over the two years. The physical flows of waste footprint show details of waste generation and treatment in the Australian economic system. The information provided in this paper is beneficial to formulate tailor-made policies for waste management in Australia

Trophic classification of selected Colorado lakes

Multispectral scanner data, acquired over several Colorado lakes using LANDSAT-1 and aircraft, were used in conjunction with contact-sensed water quality data to determine the feasibility of assessing lacustrine trophic levels. A trophic state index was developed using contact-sensed data for several trophic indicators. Relationships between the digitally processed multispectral scanner data, several trophic indicators, and the trophic index were examined using a supervised multispectral classification technique and regression techniques. Statistically significant correlations exist between spectral bands, several of the trophic indicators and the trophic state index. Color-coded photomaps were generated which depict the spectral aspects of trophic state

Oral History Interview: Mr. and Mrs. S. H. Boland

This interview is one of a series conducted concerning rural life in West Virginia. Mr. and Mrs. Boland have spent most of their lives in Summers County, West Virginia. Mrs. Boland\u27s parents died when she was young, and she and her two older sisters lived together on their farm until they married. Mr. and Mrs. Boland discuss their childhood experiences, education, courting practices, work experiences (Mr. Boland was Hinton fire chief for forty- seven years), the development of their rural district, and life in the country compared to city life.https://mds.marshall.edu/oral_history/1143/thumbnail.jp

Level-Based Analysis of the Population-Based Incremental Learning Algorithm

The Population-Based Incremental Learning (PBIL) algorithm uses a convex combination of the current model and the empirical model to construct the next model, which is then sampled to generate offspring. The Univariate Marginal Distribution Algorithm (UMDA) is a special case of the PBIL, where the current model is ignored. Dang and Lehre (GECCO 2015) showed that UMDA can optimise LeadingOnes efficiently. The question still remained open if the PBIL performs equally well. Here, by applying the level-based theorem in addition to Dvoretzky--Kiefer--Wolfowitz inequality, we show that the PBIL optimises function LeadingOnes in expected time $\mathcal{O}(n\lambda \log \lambda + n^2)$ for a population size $\lambda = \Omega(\log n)$, which matches the bound of the UMDA. Finally, we show that the result carries over to BinVal, giving the fist runtime result for the PBIL on the BinVal problem.Comment: To appea

Gastrointestinal tract size, total-tract digestibility, and rumen microflora in different dairy cow genotypes

peer-reviewedThe superior milk production efficiency of Jersey (JE) and Jersey × Holstein-Friesian (JE × HF) cows compared with Holstein-Friesian (HF) has been widely published. The biological differences among dairy cow genotypes, which could contribute to the milk production efficiency differences, have not been as widely studied however. A series of component studies were conducted using cows sourced from a longer-term genotype comparison study (JE, JE × HF, and HF). The objectives were to (1) determine if differences exist among genotypes regarding gastrointestinal tract (GIT) weight, (2) assess and quantify whether the genotypes tested differ in their ability to digest perennial ryegrass, and (3) examine the relative abundance of specific rumen microbial populations potentially relating to feed digestibility. Over 3 yr, the GIT weight was obtained from 33 HF, 35 JE, and 27 JE × HF nonlactating cows postslaughter. During the dry period the cows were offered a perennial ryegrass silage diet at maintenance level. The unadjusted GIT weight was heavier for the HF than for JE and JE × HF. When expressed as a proportion of body weight (BW), JE and JE × HF had a heavier GIT weight than HF. In vivo digestibility was evaluated on 16 each of JE, JE × HF, and HF lactating dairy cows. Cows were individually stalled, allowing for the total collection of feces and were offered freshly cut grass twice daily. During this time, daily milk yield, BW, and dry matter intake (DMI) were greater for HF and JE × HF than for JE; milk fat and protein concentration ranked oppositely. Daily milk solids yield did not differ among the 3 genotypes. Intake capacity, expressed as DMI per BW, tended to be different among treatments, with JE having the greatest DMI per BW, HF the lowest, and JE × HF being intermediate. Production efficiency, expressed as milk solids per DMI, was higher for JE than HF and JE × HF. Digestive efficiency, expressed as digestibility of dry matter, organic matter, N, neutral detergent fiber, and acid detergent fiber, was higher for JE than HF. In grazing cows (n = 15 per genotype) samples of rumen fluid, collected using a transesophageal sampling device, were analyzed to determine the relative abundance of rumen microbial populations of cellulolytic bacteria, protozoa, and fungi. These are critically important for fermentation of feed into short-chain fatty acids. A decrease was observed in the relative abundance of Ruminococcus flavefaciens in the JE rumen compared with HF and JE × HF. We can deduce from this study that the JE genotype has greater digestibility and a different rumen microbial population than HF. Jersey and JE × HF cows had a proportionally greater GIT weight than HF. These differences are likely to contribute to the production efficiency differences among genotypes previously reported

Flows and Non-thermal Velocities in Solar Active Regions Observed with the Extreme-ultraviolet Imaging Spectrometer on Hinode: A Tracer of Active Region Sources of Heliospheric Magnetic Fields?

From Doppler velocity maps of active regions constructed from spectra obtained by the Extreme-ultraviolet Imaging Spectrometer (EIS) on the Hinode spacecraft we observe large areas of outflow (20-50 km/s) that can persist for at least a day. These outflows occur in areas of active regions that are faint in coronal spectral lines formed at typical quiet Sun and active region temperatures. The outflows are positively correlated with non-thermal velocities in coronal plasmas. The bulk mass motions and non-thermal velocities are derived from spectral line centroids and line widths, mostly from a strong line of Fe XII at 195.12 Angstroms. The electron temperature of the outflow regions estimated from an Fe XIII to Fe XII line intensity ratio is about 1.2-1.4 MK. The electron density of the outflow regions derived from a density sensitive intensity ratio of Fe XII lines is rather low for an active region. Most regions average around 7E10+8 cm(-3), but there are variations on pixel spatial scales of about a factor of 4. We discuss results in detail for two active regions observed by EIS. Images of active regions in line intensity, line width, and line centroid are obtained by rastering the regions. We also discuss data from the active regions obtained from other orbiting spacecraft that support the conclusions obtained from analysis of the EIS spectra. The locations of the flows in the active regions with respect to the longitudinal photospheric magnetic fields suggest that these regions might be tracers of long loops and/or open magnetic fields that extend into the heliosphere, and thus the flows could possibly contribute significantly to the solar wind.Comment: one tex file, 11 postscript figure file

Assessing net energy consumption of Australian economy from 2004-05 to 2014-15: environmentally-extended input-output analysis, structural decomposition analysis, and linkage analysis

This paper provides a comprehensive analysis of Australian net energy consumption between 2004–05 and 2014–15. Results from environmentally-extended input-output (EEIO) analysis show that the Transport sector has the largest direct effect on net energy consumption in industrial sectors, which decreased by about 35% for net energy consumption per million $AUD in the period. The Export sector has the largest direct net energy consumption while Households consumption results in the largest net energy consumption embodied in different categories of Final demand. The structural decomposition analysis (SDA) decomposes the change of net energy consumption into five drivers, in which net energy intensity mainly reduces Australian net energy consumption by about 8000 Petajoules, while the level effect of Final demand increases it by about 10,000 Petajoules. Analysis of forward and backward linkages highlights the Manufacturing sector as the key industrial sector with the largest energy consumption reduction potential via minor changes in its input and Final demand. This indicates that more attention should be given to the reduction of energy demand from the consumption patterns of Households consumption, the improvement of energy intensity, and the application of cleaner technologies in the Transport and Manufacturing sectors. The Australian Environmental-Economic Accounts is combined with Australian input-output tables to construct the EEIO tables for net energy consumption. The combination of economic and environmental data sets provides a depth of understanding their potential to inform environmental policy decisions. The novelty of the research is the combination of economic and energy data sets, the application of EEIO model, the implementation of the additive SDA method, and the use of forward and backward linkages for the Australian energy system

Stochastic Description of a Bistable Frustrated Unit

Mixed positive and negative feedback loops are often found in biological systems which support oscillations. In this work we consider a prototype of such systems, which has been recently found at the core of many genetic circuits showing oscillatory behaviour. Our model consists of two interacting species A and B, where A activates not only its own production, but also that of its repressor B. While the self-activation of A leads already to a bistable unit, the coupling with a negative feedback loop via B makes the unit frustrated. In the deterministic limit of infinitely many molecules, such a bistable frustrated unit is known to show excitable and oscillatory dynamics, depending on the maximum production rate of A which acts as a control parameter. We study this model in its fully stochastic version and we find oscillations even for parameters which in the deterministic limit are deeply in the fixed-point regime. The deeper we go into this regime, the more irregular these oscillations are, becoming finally random excitations whenever fluctuations allow the system to overcome the barrier for a large excursion in phase space. The fluctuations can no longer be fully treated as a perturbation. The smaller the system size (the number of molecules), the more frequent are these excitations. Therefore, stochasticity caused by demographic noise makes this unit even more flexible with respect to its oscillatory behaviour.Comment: 28 pages, 17 figure