31 resultados para decomposition of polymeric precursor method (DPP)


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A One-Dimensional Time to Explosion (ODTX) apparatus has been used to study the times to explosion of a number of compositions based on RDX and HMX over a range of contact temperatures. The times to explosion at any given temperature tend to increase from RDX to HMX and with the proportion of HMX in the composition. Thermal ignition theory has been applied to time to explosion data to calculate kinetic parameters. The apparent activation energy for all of the compositions lay between 127 kJ mol−1 and 146 kJ mol−1. There were big differences in the pre-exponential factor and this controlled the time to explosion rather than the activation energy for the process.

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Motivation: In order to enhance genome annotation, the fully automatic fold recognition method GenTHREADER has been improved and benchmarked. The previous version of GenTHREADER consisted of a simple neural network which was trained to combine sequence alignment score, length information and energy potentials derived from threading into a single score representing the relationship between two proteins, as designated by CATH. The improved version incorporates PSI-BLAST searches, which have been jumpstarted with structural alignment profiles from FSSP, and now also makes use of PSIPRED predicted secondary structure and bi-directional scoring in order to calculate the final alignment score. Pairwise potentials and solvation potentials are calculated from the given sequence alignment which are then used as inputs to a multi-layer, feed-forward neural network, along with the alignment score, alignment length and sequence length. The neural network has also been expanded to accommodate the secondary structure element alignment (SSEA) score as an extra input and it is now trained to learn the FSSP Z-score as a measurement of similarity between two proteins. Results: The improvements made to GenTHREADER increase the number of remote homologues that can be detected with a low error rate, implying higher reliability of score, whilst also increasing the quality of the models produced. We find that up to five times as many true positives can be detected with low error rate per query. Total MaxSub score is doubled at low false positive rates using the improved method.

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Scoring rules are an important tool for evaluating the performance of probabilistic forecasting schemes. A scoring rule is called strictly proper if its expectation is optimal if and only if the forecast probability represents the true distribution of the target. In the binary case, strictly proper scoring rules allow for a decomposition into terms related to the resolution and the reliability of a forecast. This fact is particularly well known for the Brier Score. In this article, this result is extended to forecasts for finite-valued targets. Both resolution and reliability are shown to have a positive effect on the score. It is demonstrated that resolution and reliability are directly related to forecast attributes that are desirable on grounds independent of the notion of scores. This finding can be considered an epistemological justification of measuring forecast quality by proper scoring rules. A link is provided to the original work of DeGroot and Fienberg, extending their concepts of sufficiency and refinement. The relation to the conjectured sharpness principle of Gneiting, et al., is elucidated.

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References (20)Cited By (1)Export CitationAboutAbstract Proper scoring rules provide a useful means to evaluate probabilistic forecasts. Independent from scoring rules, it has been argued that reliability and resolution are desirable forecast attributes. The mathematical expectation value of the score allows for a decomposition into reliability and resolution related terms, demonstrating a relationship between scoring rules and reliability/resolution. A similar decomposition holds for the empirical (i.e. sample average) score over an archive of forecast–observation pairs. This empirical decomposition though provides a too optimistic estimate of the potential score (i.e. the optimum score which could be obtained through recalibration), showing that a forecast assessment based solely on the empirical resolution and reliability terms will be misleading. The differences between the theoretical and empirical decomposition are investigated, and specific recommendations are given how to obtain better estimators of reliability and resolution in the case of the Brier and Ignorance scoring rule.

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Ozone (O3) precursor emissions influence regional and global climate and air quality through changes in tropospheric O3 and oxidants, which also influence methane (CH4) and sulfate aerosols (SO42−). We examine changes in the tropospheric composition of O3, CH4, SO42− and global net radiative forcing (RF) for 20% reductions in global CH4 burden and in anthropogenic O3 precursor emissions (NOx, NMVOC, and CO) from four regions (East Asia, Europe and Northern Africa, North America, and South Asia) using the Task Force on Hemispheric Transport of Air Pollution Source-Receptor global chemical transport model (CTM) simulations, assessing uncertainty (mean ± 1 standard deviation) across multiple CTMs. We evaluate steady state O3 responses, including long-term feedbacks via CH4. With a radiative transfer model that includes greenhouse gases and the aerosol direct effect, we find that regional NOx reductions produce global, annually averaged positive net RFs (0.2 ± 0.6 to 1.7 ± 2 mWm−2/Tg N yr−1), with some variation among models. Negative net RFs result from reductions in global CH4 (−162.6 ± 2 mWm−2 for a change from 1760 to 1408 ppbv CH4) and regional NMVOC (−0.4 ± 0.2 to −0.7 ± 0.2 mWm−2/Tg C yr−1) and CO emissions (−0.13 ± 0.02 to −0.15 ± 0.02 mWm−2/Tg CO yr−1). Including the effect of O3 on CO2 uptake by vegetation likely makes these net RFs more negative by −1.9 to −5.2 mWm−2/Tg N yr−1, −0.2 to −0.7 mWm−2/Tg C yr−1, and −0.02 to −0.05 mWm−2/Tg CO yr−1. Net RF impacts reflect the distribution of concentration changes, where RF is affected locally by changes in SO42−, regionally to hemispherically by O3, and globally by CH4. Global annual average SO42− responses to oxidant changes range from 0.4 ± 2.6 to −1.9 ± 1.3 Gg for NOx reductions, 0.1 ± 1.2 to −0.9 ± 0.8 Gg for NMVOC reductions, and −0.09 ± 0.5 to −0.9 ± 0.8 Gg for CO reductions, suggesting additional research is needed. The 100-year global warming potentials (GWP100) are calculated for the global CH4 reduction (20.9 ± 3.7 without stratospheric O3 or water vapor, 24.2 ± 4.2 including those components), and for the regional NOx, NMVOC, and CO reductions (−18.7 ± 25.9 to −1.9 ± 8.7 for NOx, 4.8 ± 1.7 to 8.3 ± 1.9 for NMVOC, and 1.5 ± 0.4 to 1.7 ± 0.5 for CO). Variation in GWP100 for NOx, NMVOC, and CO suggests that regionally specific GWPs may be necessary and could support the inclusion of O3 precursors in future policies that address air quality and climate change simultaneously. Both global net RF and GWP100 are more sensitive to NOx and NMVOC reductions from South Asia than the other three regions.

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This letter presents an effective approach for selection of appropriate terrain modeling methods in forming a digital elevation model (DEM). This approach achieves a balance between modeling accuracy and modeling speed. A terrain complexity index is defined to represent a terrain's complexity. A support vector machine (SVM) classifies terrain surfaces into either complex or moderate based on this index associated with the terrain elevation range. The classification result recommends a terrain modeling method for a given data set in accordance with its required modeling accuracy. Sample terrain data from the lunar surface are used in constructing an experimental data set. The results have shown that the terrain complexity index properly reflects the terrain complexity, and the SVM classifier derived from both the terrain complexity index and the terrain elevation range is more effective and generic than that designed from either the terrain complexity index or the terrain elevation range only. The statistical results have shown that the average classification accuracy of SVMs is about 84.3% ± 0.9% for terrain types (complex or moderate). For various ratios of complex and moderate terrain types in a selected data set, the DEM modeling speed increases up to 19.5% with given DEM accuracy.

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The effects of forage conservation method on plasma lipids, mammary lipogenesis, and milk fat were examined in 2 complementary experiments. Treatments comprised fresh grass, hay, or untreated (UTS) or formic acid treated silage (FAS) prepared from the same grass sward. Preparation of conserved forages coincided with the collection of samples from cows fed fresh grass. In the first experiment, 5 multiparous Finnish Ayrshire cows (229 d in milk) were used to compare a diet based on fresh grass followed by hay during 2 consecutive 14-d periods, separated by a 5-d transition during which extensively wilted grass was fed. In the second experiment, 5 multiparous Finnish Ayrshire cows (53 d in milk) were assigned to 1 of 2 blocks and allocated treatments according to a replicated 3 × 3 Latin square design, with 14-d periods to compare hay, UTS, and FAS. Cows received 7 or 9 kg/d of the same concentrate in experiments 1 and 2, respectively. Arterial concentrations of triacylglycerol (TAG) and phospholipid were higher in cows fed fresh grass, UTS, and FAS compared with hay. Nonesterified fatty acid (NEFA) concentrations and the relative abundance of 18:2n-6 and 18:3n-3 in TAG of arterial blood were also higher in cows fed fresh grass than conserved forages. On all diets, TAG was the principle source of fatty acids (FA) for milk fat synthesis, whereas mammary extraction of NEFA was negligible, except during zero-grazing, which was associated with a lower, albeit positive calculated energy balance. Mammary FA uptake was higher and the synthesis of 16:0 lower in cows fed fresh grass than hay. Conservation of grass by drying or ensiling had no influence on mammary extraction of TAG and NEFA, despite an increase in milk fat secretion for silages compared with hay and for FAS than UTS. Relative to hay, milk fat from fresh grass contained lower 12:0, 14:0, and 16:0 and higher S3,R7,R11,15-tetramethyl-16:0, cis-9 18:1, trans-11 18:1, cis-9,trans-11 18:2, 18:2n-6, and 18:3n-3 concentrations. Even though conserved forages altered mammary lipogenesis, differences in milk FA composition were relatively minor, other than a higher enrichment of S3,R7,R11,15-tetramethyl-16:0 in milk from silages compared with hay. In conclusion, differences in milk fat composition on fresh grass relative to conserved forages were associated with a lower energy balance, increased uptake of preformed FA, and decreased synthesis of 16:0 de novo in the mammary glands, in the absence of alterations in stearoyl-coenzyme A desaturase activity.

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This article proposes a systematic approach to determine the most suitable analogue redesign method to be used for forward-type converters under digital voltage mode control. The focus of the method is to achieve the highest phase margin at the particular switching and crossover frequencies chosen by the designer. It is shown that at high crossover frequencies with respect to switching frequency, controllers designed using backward integration have the largest phase margin; whereas at low crossover frequencies with respect to switching frequency, controllers designed using bilinear integration with pre-warping have the largest phase margins. An algorithm has been developed to determine the frequency of the crossing point where the recommended discretisation method changes. An accurate model of the power stage is used for simulation and experimental results from a Buck converter are collected. The performance of the digital controllers is compared to that of the equivalent analogue controller both in simulation and experiment. Excellent closeness between the simulation and experimental results is presented. This work provides a concrete example to allow academics and engineers to systematically choose a discretisation method.

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The detection of physiological signals from the motor system (electromyographic signals) is being utilized in the practice clinic to guide the therapist in a more precise and accurate diagnosis of motor disorders. In this context, the process of decomposition of EMG (electromyographic) signals that includes the identification and classification of MUAP (Motor Unit Action Potential) of a EMG signal, is very important to help the therapist in the evaluation of motor disorders. The EMG decomposition is a complex task due to EMG features depend on the electrode type (needle or surface), its placement related to the muscle, the contraction level and the health of the Neuromuscular System. To date, the majority of researches on EMG decomposition utilize EMG signals acquired by needle electrodes, due to their advantages in processing this type of signal. However, relatively few researches have been conducted using surface EMG signals. Thus, this article aims to contribute to the clinical practice by presenting a technique that permit the decomposition of surface EMG signal via the use of Hidden Markov Models. This process is supported by the use of differential evolution and spectral clustering techniques. The developed system presented coherent results in: (1) identification of the number of Motor Units actives in the EMG signal; (2) presentation of the morphological patterns of MUAPs in the EMG signal; (3) identification of the firing sequence of the Motor Units. The model proposed in this work is an advance in the research area of decomposition of surface EMG signals.

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Little is known about the effect of edaphic conditions on the decomposition of buried mammalian tissues. To address this, we set up a replicated incubation study with three fresh soils of contrasting pH: a Podsol (acidic), a Cambisol (neutral), and a Rendzina (alkaline), in which skeletal muscle tissue (SMT) of known mass was allowed to decompose. Our results clearly demonstrated that soil type had a considerable effect on the decomposition of SMT buried in soil. Differences in the rate of decomposition were up to three times greater in the Podsol compared with the Rendzina. The rate of microbial respiration was correlated to the rate of soft tissue loss, which suggests that the decomposition of SMT is dependent on the microbial community present in the soil. Decompositional by-products caused the pH of the immediate soil environment to change, becoming more alkaline at first, before acidifying. Our results demonstrate the need for greater consideration of soil type in future taphonomic studies.

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The ecology of soils associated with dead mammals (i.e. cadavers) is poorly understood. Although temperature and soil type are well known to influence the decomposition of other organic resource patches, the effect of these variables on the degradation of cadavers in soil has received little experimental investigation. To address this, cadavers of juvenile rats (Rattus rattus) were buried in one of three contrasting soils (Sodosol, Rudosol, and Vertosol) from tropical savanna ecosystems in Queensland, Australia and incubated at 29 °C, 22 °C, or 15 °C in a laboratory setting. Cadavers and soils were destructively sampled at intervals of 7 days over an incubation period of 28 days. Measurements of decomposition included cadaver mass loss, carbon dioxide–carbon (CO2–C) evolution, microbial biomass carbon (MBC), protease activity, phosphodiesterase activity, and soil pH, which were all significantly positively affected by cadaver burial. A temperature effect was observed where peaks or differences in decomposition that at occurred at higher temperature would occur at later sample periods at lower temperature. Soil type also had an important effect on some measured parameters. These findings have important implications for a largely unexplored area of soil ecology and nutrient cycling, which are significant for forensic science, cemetery planning and livestock carcass disposal.