Complete genome analysis of a rabies virus isolate from Brazilian wild fox

The complete genome sequence of wild-type rabies virus (RABV) isolated from a wild Brazilian hoary fox (Dusicyon sp.), the BR-Pfx1 isolate, was determined and compared with fixed RABV strains. The genome structure and organization of the BR-Pfx1 isolate were composed of 11,924 nt and included the five standard genes of rhabdoviruses. Sequences of mRNA start and stop signals for transcription were highly conserved among all structural protein genes of the BR-Pfx1 isolate. All amino acid residues in the glycoprotein (G) gene associated with pathogenicity were retained in the BR-Pfx1 isolate, while unique amino acid substitutions were found in antigenic region I of the nucleoprotein gene and III of G. These results suggest that although the standard genome structure and organization of the RABV isolate are common between the BR-Pfx1 isolate and fixed RABV strains, the unique amino acid substitutions in functional sites of the BR-Pfx1 isolate may result in different biological characteristics from fixed RABV strains.

Structural decomposition analysis and input-output subsystems: An application to Spanish CO2 emissions

Analysis of gas emissions by the input-output subsystem approach provides detailed insight into pollution generation in an economy. Structural decomposition analysis, on the other hand, identifies the factors behind the changes in key variables over time. Extending the input-output subsystem model to account for the changes in these variables reveals the channels by which environmental burdens are caused and transmitted throughout the production system. In this paper we propose a decomposition of the changes in the components of CO2 emissions captured by an input-output subsystems representation. The empirical application is for the Spanish service sector, and the economic and environmental data are for years 1990 and 2000. Our results show that services increased their CO2 emissions mainly because of a rise in emissions generated by non-services to cover the final demand for services. In all service activities, the decomposed effects show an increase in CO2 emissions due to a decrease in emission coefficients (i.e., emissions per unit of output) compensated by an increase in emissions caused both by the input-output coefficients and the rise in demand for services. Finally, large asymmetries exist not only in the quantitative changes in the CO2 emissions of the various services but also in the decomposed effects of these changes. Keywords: structural decomposition analysis, input-output subsystems, CO2 emissions, service sector.

Multiway Array Decomposition Analysis of EEGs in Alzheimer’s Disease

Methods for the extraction of features from physiological datasets are growing needs as clinical investigations of Alzheimer’s disease (AD) in large and heterogeneous population increase. General tools allowing diagnostic regardless of recording sites, such as different hospitals, are essential and if combined to inexpensive non-invasive methods could critically improve mass screening of subjects with AD. In this study, we applied three state of the art multiway array decomposition (MAD) methods to extract features from electroencephalograms (EEGs) of AD patients obtained from multiple sites. In comparison to MAD, spectral-spatial average filter (SSFs) of control and AD subjects were used as well as a common blind source separation method, algorithm for multiple unknown signal extraction (AMUSE). We trained a feed-forward multilayer perceptron (MLP) to validate and optimize AD classification from two independent databases. Using a third EEG dataset, we demonstrated that features extracted from MAD outperformed features obtained from SSFs AMUSE in terms of root mean squared error (RMSE) and reaching up to 100% of accuracy in test condition. We propose that MAD maybe a useful tool to extract features for AD diagnosis offering great generalization across multi-site databases and opening doors to the discovery of new characterization of the disease.

Disentangling water usage in the European Union: A decomposition analysis

The Water Framework Directive (WFD) defines common objectives for water resources throughout the European Union (EU). Given this general approach to water preservation and water policy, the objective of this paper is to analyse whether common patterns of water consumption exist within Europe. In particular, our study uses two methods to reveal the reasons behind sectoral water use in all EU countries. The first method is based on an accounting indicator that calculates the water intensity of an economy as the sum of sectoral water intensities. The second method is a subsystem input‐output model that divides total water use into different income channels within the production system. The application uses data for the years 2005 and 2009 on water consumption in the production system of the 27 countries of the EU. From our analysis it emerges that EU countries are characterized by very different patterns of water consumption. In particular water consumption by the agriculture sector is extremely high in Central/Eastern Europe, relative to the rest of Europe. In most countries, the water used by the fuel, power and water sector is consumed to satisfy domestic final demand. However, our analysis shows that for some countries exports from this sector are an important driver of water consumption. Focusing on the agricultural sector, the decomposition analysis suggests that water usage in Mediterranean countries is mainly driven by final demand for, and exports of, agricultural products. In Central/Eastern Europe domestic final demand is the main driver of water consumption, but in this region the proportion of water use driven by demand for exports is increasing over time. Given these heterogeneous water consumption patterns, our analysis suggests that Mediterranean and Central/Eastern European countries should adopt specific water policies in order to achieve efficient levels of water consumption in the European Union. JEL codes: N5; C67 Keywords: Water use, Subsystem input–output model; Water intensity, European Union.

Environmental Structural Decomposition Analysis of Italian Emissions, 1995-2005

[spa] El estudio analiza la evolución de los gases de efecto invernadero (GEI) y las emisiones de acidificación para Italia durante el periodo 1995-2005. Los datos muestran que mientras las emisiones que contribuyen a la acidificación han disminuido constantemente, las emisiones de GEI han aumentado debido al aumento de dióxido de carbono. El objetivo de este estudio es poner de relieve cómo diferentes factores económicos, en particular el crecimiento económico, el desarrollo de una tecnología menos contaminante y la estructura del consumo, han impulsado la evolución de las emisiones. La metodología propuesta es un análisis de descomposición estructural (ADE), método que permite descomponer los cambios de la variable de interés entre las diferentes fuerzas y revelar la importancia de cada factor. Por otra parte, este estudio considera la importancia del comercio internacional e intenta incluir el “problema de la responsabilidad”. Es decir, a través de las relaciones comerciales internacionales, un país podría estar exportando procesos de producción contaminantes sin una reducción real de la contaminación implícita en su patrón de consumo. Con este fin, siguiendo primero un enfoque basado en la “responsabilidad del productor”, el ADE se aplica a las emisiones causadas por la producción nacional. Sucesivamente, el análisis se mueve hacia un enfoque basado en la “responsabilidad del consumidor" y la descomposición se aplica a las emisiones relacionadas con la producción nacional o la producción extranjera que satisface la demanda interna. De esta manera, el ejercicio permite una primera comprobación de la importancia del comercio internacional y pone de relieve algunos resultados a nivel global y a nivel sectorial.

Environmental Structural Decomposition Analysis of Italian Emissions, 1995-2005

[spa] El estudio analiza la evolución de los gases de efecto invernadero (GEI) y las emisiones de acidificación para Italia durante el periodo 1995-2005. Los datos muestran que mientras las emisiones que contribuyen a la acidificación han disminuido constantemente, las emisiones de GEI han aumentado debido al aumento de dióxido de carbono. El objetivo de este estudio es poner de relieve cómo diferentes factores económicos, en particular el crecimiento económico, el desarrollo de una tecnología menos contaminante y la estructura del consumo, han impulsado la evolución de las emisiones. La metodología propuesta es un análisis de descomposición estructural (ADE), método que permite descomponer los cambios de la variable de interés entre las diferentes fuerzas y revelar la importancia de cada factor. Por otra parte, este estudio considera la importancia del comercio internacional e intenta incluir el “problema de la responsabilidad”. Es decir, a través de las relaciones comerciales internacionales, un país podría estar exportando procesos de producción contaminantes sin una reducción real de la contaminación implícita en su patrón de consumo. Con este fin, siguiendo primero un enfoque basado en la “responsabilidad del productor”, el ADE se aplica a las emisiones causadas por la producción nacional. Sucesivamente, el análisis se mueve hacia un enfoque basado en la “responsabilidad del consumidor" y la descomposición se aplica a las emisiones relacionadas con la producción nacional o la producción extranjera que satisface la demanda interna. De esta manera, el ejercicio permite una primera comprobación de la importancia del comercio internacional y pone de relieve algunos resultados a nivel global y a nivel sectorial.

The causal factors of international inequality in CO2 emissions per capita: a regression-based inequality decomposition analysis

This paper uses the possibilities provided by the regression-based inequality decomposition (Fields, 2003) to explore the contribution of different explanatory factors to international inequality in CO2 emissions per capita. In contrast to previous emissions inequality decompositions, which were based on identity relationships (Duro and Padilla, 2006), this methodology does not impose any a priori specific relationship. Thus, it allows an assessment of the contribution to inequality of different relevant variables. In short, the paper appraises the relative contributions of affluence, sectoral composition, demographic factors and climate. The analysis is applied to selected years of the period 1993–2007. The results show the important (though decreasing) share of the contribution of demographic factors, as well as a significant contribution of affluence and sectoral composition.

Biases in the distribution of bilateral aid: a regional decomposition analysis

This article investigates income and population biases in the distribution of aid and decomposes recipients by geographic region. Previous analyses aggregate recipients and assume biases have an equal impact. Results demonstrate that although while a bias towards middle-income and medium-sized countries persists in the full sample, the extent of such biases differs significantly by region.

Motivational interviewing and feedback for college drinkers: Handling missing values with complete case analysis and multiple imputation

Objective: In this secondary data analysis, three statistical methodologies were implemented to handle cases with missing data in a motivational interviewing and feedback study. The aim was to evaluate the impact that these methodologies have on the data analysis. ^ Methods: We first evaluated whether the assumption of missing completely at random held for this study. We then proceeded to conduct a secondary data analysis using a mixed linear model to handle missing data with three methodologies (a) complete case analysis, (b) multiple imputation with explicit model containing outcome variables, time, and the interaction of time and treatment, and (c) multiple imputation with explicit model containing outcome variables, time, the interaction of time and treatment, and additional covariates (e.g., age, gender, smoke, years in school, marital status, housing, race/ethnicity, and if participants play on athletic team). Several comparisons were conducted including the following ones: 1) the motivation interviewing with feedback group (MIF) vs. the assessment only group (AO), the motivation interviewing group (MIO) vs. AO, and the intervention of the feedback only group (FBO) vs. AO, 2) MIF vs. FBO, and 3) MIF vs. MIO.^ Results: We first evaluated the patterns of missingness in this study, which indicated that about 13% of participants showed monotone missing patterns, and about 3.5% showed non-monotone missing patterns. Then we evaluated the assumption of missing completely at random by Little's missing completely at random (MCAR) test, in which the Chi-Square test statistic was 167.8 with 125 degrees of freedom, and its associated p-value was p=0.006, which indicated that the data could not be assumed to be missing completely at random. After that, we compared if the three different strategies reached the same results. For the comparison between MIF and AO as well as the comparison between MIF and FBO, only the multiple imputation with additional covariates by uncongenial and congenial models reached different results. For the comparison between MIF and MIO, all the methodologies for handling missing values obtained different results. ^ Discussions: The study indicated that, first, missingness was crucial in this study. Second, to understand the assumptions of the model was important since we could not identify if the data were missing at random or missing not at random. Therefore, future researches should focus on exploring more sensitivity analyses under missing not at random assumption.^

The Most Complete Photometric Analysis of 548 CALIFA Galaxies

We present an extensive photometric catalog for 548 CALIFA galaxies observed as of the summer of 2015. CALIFA is currently lacking photometry matching the scale and diversity of its spectroscopy; this work is intended to meet all photometric needs for CALIFA galaxies while also identifying best photometric practices for upcoming integral field spectroscopy surveys such as SAMI and MaNGA. This catalog comprises gri surface brightness profiles derived from Sloan Digital Sky Survey (SDSS) imaging, a variety of non-parametric quantities extracted from these pro files, and parametric models fitted to the i-band pro files (1D) and original galaxy images (2D). To compliment our photometric analysis, we contrast the relative performance of our 1D and 2D modelling approaches. The ability of each measurement to characterize the global properties of galaxies is quantitatively assessed, in the context of constructing the tightest scaling relations. Where possible, we compare our photometry with existing photometrically or spectroscopically obtained measurements from the literature. Close agreement is found with Walcher et al. (2014), the current source of basic photometry and classifications of CALIFA galaxies, while comparisons with spectroscopically derived quantities reveals the effect of CALIFA's limited field of view compared to broadband imaging surveys such as the SDSS. The colour-magnitude diagram, star formation main sequence, and Tully-Fisher relation of CALIFA galaxies are studied, to give a small example of the investigations possible with this rich catalog. We conclude with a discussion of points of concern for ongoing integral field spectroscopy surveys and directions for future expansion and exploitation of this work.

Assessment of Energy Conservation in Indian Cement Industry and Forecasting of Co2 Emissions

Cement industry ranks 2nd in energy consumption among the industries in India. It is one of the major emitter of CO2, due to combustion of fossil fuel and calcination process. As the huge amount of CO2 emissions cause severe environment problems, the efficient and effective utilization of energy is a major concern in Indian cement industry. The main objective of the research work is to assess the energy cosumption and energy conservation of the Indian cement industry and to predict future trends in cement production and reduction of CO2 emissions. In order to achieve this objective, a detailed energy and exergy analysis of a typical cement plant in Kerala was carried out. The data on fuel usage, electricity consumption, amount of clinker and cement production were also collected from a few selected cement industries in India for the period 2001 - 2010 and the CO2 emissions were estimated. A complete decomposition method was used for the analysis of change in CO2 emissions during the period 2001 - 2010 by categorising the cement industries according to the specific thermal energy consumption. A basic forecasting model for the cement production trend was developed by using the system dynamic approach and the model was validated with the data collected from the selected cement industries. The cement production and CO2 emissions from the industries were also predicted with the base year as 2010. The sensitivity analysis of the forecasting model was conducted and found satisfactory. The model was then modified for the total cement production in India to predict the cement production and CO2 emissions for the next 21 years under three different scenarios. The parmeters that influence CO2 emissions like population and GDP growth rate, demand of cement and its production, clinker consumption and energy utilization are incorporated in these scenarios. The existing growth rate of the population and cement production in the year 2010 were used in the baseline scenario. In the scenario-1 (S1) the growth rate of population was assumed to be gradually decreasing and finally reach zero by the year 2030, while in scenario-2 (S2) a faster decline in the growth rate was assumed such that zero growth rate is achieved in the year 2020. The mitigation strategiesfor the reduction of CO2 emissions from the cement production were identified and analyzed in the energy management scenarioThe energy and exergy analysis of the raw mill of the cement plant revealed that the exergy utilization was worse than energy utilization. The energy analysis of the kiln system showed that around 38% of heat energy is wasted through exhaust gases of the preheater and cooler of the kiln sysetm. This could be recovered by the waste heat recovery system. A secondary insulation shell was also recommended for the kiln in the plant in order to prevent heat loss and enhance the efficiency of the plant. The decomposition analysis of the change in CO2 emissions during 2001- 2010 showed that the activity effect was the main factor for CO2 emissions for the cement industries since it is directly dependent on economic growth of the country. The forecasting model showed that 15.22% and 29.44% of CO2 emissions reduction can be achieved by the year 2030 in scenario- (S1) and scenario-2 (S2) respectively. In analysing the energy management scenario, it was assumed that 25% of electrical energy supply to the cement plants is replaced by renewable energy. The analysis revealed that the recovery of waste heat and the use of renewable energy could lead to decline in CO2 emissions 7.1% for baseline scenario, 10.9 % in scenario-1 (S1) and 11.16% in scenario-2 (S2) in 2030. The combined scenario considering population stabilization by the year 2020, 25% of contribution from renewable energy sources of the cement industry and 38% thermal energy from the waste heat streams shows that CO2 emissions from Indian cement industry could be reduced by nearly 37% in the year 2030. This would reduce a substantial level of greenhouse gas load to the environment. The cement industry will remain one of the critical sectors for India to meet its CO2 emissions reduction target. India’s cement production will continue to grow in the near future due to its GDP growth. The control of population, improvement in plant efficiency and use of renewable energy are the important options for the mitigation of CO2 emissions from Indian cement industries

Elemental analysis of nuts and seeds by axially viewed ICP OES

A method for the multi-elemental determination of metals (Al, Ba, Ca, Cu, Fe, K, Mg, Mn, Sr and Zn), metalloids (B and Si), and non-metals (Cl, P and 5) in the babassu nut and mesocarp, sapucaia nut, coconut pulp, cupuassu pulp and seed, and cashew nut by axially viewed inductively coupled plasma optical emission spectrometry is presented. A diluted oxidant mixture (2 ml HNO(3) + 1 ml H(2)O(2) + 3 ml H(2)O) was used to achieve the complete decomposition of the organic matrix in a closed-vessel microwave oven. The accuracy of the entire proposed method was confirmed by standard reference material analysis (peach leaves-NIST SRM1547). The certified values showed a good agreement at a 95% confidence limit (Student`s t-test). The average RSD for repeatability of calibration solutions measurements were in the range of 1.1-6.7%. Limits of quantification (LOQ = 10 x LOD) were in the level of 0.00072-0.0532 mg/l. The macro and micronutrient ranges in the different nuts and seeds did not exceed the dietary reference intake (DRI), except for Mn in the babassu nut. (C) 2010 Published by Elsevier Ltd.

Analysis of Masticatory Cycle Efficiency in Complete Denture Wearers

Purpose: This study assessed masticatory efficiency and duration of the masticatory cycle in 14 asymptomatic patients with severe bone resorption. All patients had worn complete dentures for over 10 years. Recall visits were scheduled at 5 months and 1 year after receiving new dentures.Materials and Methods: Fourteen patients were evaluated in this study. The Research Diagnostic Criteria questionnaire and tests of the efficiency and duration of the masticatory cycle were performed with artificial food before, 5 months after, and 1 year after new dentures were delivered. Masticatory efficiency was assessed using a sieve system; artificial food was ground for 35 masticatory cycles and monitored by the operator.Results: Masticatory efficiency at 5 months was significantly improved for the 0.42-mm mesh. An improvement in masticatory efficiency and a reduction in mastication time were observed with the new dentures after 1 year.Conclusion: The results of this study indicated that 5 months did not allow enough time to demonstrate improved muscular capacity and ability after receiving new dentures. After 1 year, the duration of the masticatory cycle was reduced, and masticatory efficiency was significantly improved.