Environmental Tax on Products and Services Based on Their Carbon Footprint: A Case Study of the Pulp and Paper Sector

The main aim of this work is to define an environmental tax on products and services based on their carbon footprint. We examine the relevance of conventional life cycle analysis (LCA) and environmentally extended input-output analysis (EIO) as methodological tools to identify emission intensities of products and services on which the tax is based. The short-term price effects of the tax and the policy implications of considering non-GHG are also analyzed. The results from the specific case study on pulp production show that the environmental tax rate based on the LCA approach (1,8%) is higher than both EIO approaches (0,8% for product and 1,4% for industry approach), but they are comparable. Even though LCA is more product specific and provides detailed analysis, EIO would be the more relevant approach to apply economy wide environmental tax. When the environmental tax considers non-GHG emissions instead of only CO2, sectors such as agriculture, mining of coal and extraction of peat, and food exhibit higher environmental tax and price effects. Therefore, it is worthwhile for policy makers to pay attention on the implication of considering only CO2 tax or GHG emissions tax in order for such a policy measure to be effective and meaningful. Keywords: Environmental tax; Life cycle analysis; Environmental input-output analysis.

Detection of coronary stenoses with contrast enhanced, three-dimensional free breathing coronary MR angiography using the gadolinium-based intravascular contrast agent gadocoletic acid (B-22956).

PURPOSE: To determine the diagnostic value of the intravascular contrast agent gadocoletic acid (B-22956) in three-dimensional, free breathing coronary magnetic resonance angiography (MRA) for stenosis detection in patients with suspected or known coronary artery disease. METHODS: Eighteen patients underwent three-dimensional, free breathing coronary MRA of the left and right coronary system before and after intravenous application of a single dose of gadocoletic acid (B-22956) using three different dose regimens (group A 0.050 mmol/kg; group B 0.075 mmol/kg; group C 0.100 mmol/kg). Precontrast scanning followed a coronary MRA standard non-contrast T2 preparation/turbo-gradient echo sequence (T2Prep); for postcontrast scanning an inversion-recovery gradient echo sequence was used (real-time navigator correction for both scans). In pre- and postcontrast scans quantitative analysis of coronary MRA data was performed to determine the number of visible side branches, vessel length and vessel sharpness of each of the three coronary arteries (LAD, LCX, RCA). The number of assessable coronary artery segments was determined to calculate sensitivity and specificity for detection of stenosis > or = 50% on a segment-to-segment basis (16-segment-model) in pre- and postcontrast scans with x-ray coronary angiography as the standard of reference. RESULTS: Dose group B (0.075 mmol/kg) was preferable with regard to improvement of MR angiographic parameters: in postcontrast scans all MR angiographic parameters increased significantly except for the number of visible side branches of the left circumflex artery. In addition, assessability of coronary artery segments significantly improved postcontrast in this dose group (67 versus 88%, p < 0.01). Diagnostic performance (sensitivity, specificity, accuracy) was 83, 77 and 78% for precontrast and 86, 95 and 94% for postcontrast scans. CONCLUSIONS: The use of gadocoletic acid (B-22956) results in an improvement of MR angiographic parameters, asssessability of coronary segments and detection of coronary stenoses > or = 50%.

Molecular Modeling Approaches for Determining Gene Function: application to a Putative Poly-A Binding Protein from Leishmania amazonensis (LaPABP)

The great expansion in the number of genome sequencing projects has revealed the importance of computational methods to speed up the characterization of unknown genes. These studies have been improved by the use of three dimensional information from the predicted proteins generated by molecular modeling techniques. In this work, we disclose the structure-function relationship of a gene product from Leishmania amazonensis by applying molecular modeling and bioinformatics techniques. The analyzed sequence encodes a 159 aminoacids polypeptide (estimated 18 kDa) and was denoted LaPABP for its high homology with poly-A binding proteins from trypanosomatids. The domain structure, clustering analysis and a three dimensional model of LaPABP, basically obtained by homology modeling on the structure of the human poly-A binding protein, are described. Based on the analysis of the electrostatic potential mapped on the model's surface and conservation of intramolecular contacts responsible for folding stabilization we hypothesize that this protein may have less avidity to RNA than it's L. major counterpart but still account for a significant functional activity in the parasite. The model obtained will help in the design of mutagenesis experiments aimed to elucidate the mechanism of gene expression in trypanosomatids and serve as a starting point for its exploration as a potential source of targets for a rational chemotherapy.

New nonculture-based methods for the diagnosis of invasive candidiasis.

PURPOSE OF REVIEW: Invasive candidiasis is a severe infectious complication occurring mostly in onco-hematologic and surgical patients. Its conventional diagnosis is insensitive and often late, leading to a delayed treatment and a high mortality. The purpose of this article is to review recent contributions in the nonconventional diagnostic approaches of invasive candidiasis, both for the detection of the epidose and the characterization of the etiologic agent. RECENT FINDINGS: Antigen-based tests to detect invasive candidiasis comprise a specific test, mannan, as well as a nonspecific test, beta-D-glucan. Both have a moderate sensitivity and a high specificity, and cannot be recommended alone as a negative screening tool or a positive syndrome driven diagnostic tool. Molecular-based tests still have not reached the stage of rapid, easy to use, standardized tests ideally complementing blood culture at the time of blood sampling. New tests (fluorescence in-situ hybridization or mass spectrometry) significantly reduce the delay of identification of Candida at the species level in positive blood cultures, and should have a positive impact on earlier appropriate antifungal therapy and possibly on outcome. SUMMARY: Both antigen-based and molecular tests appear as promising new tools to complement and accelerate the conventional diagnosis of invasive candidiasis with an expected significant impact on earlier and more focused treatment and on prognosis.

Hierarchical conditional random fields for parts based models matching

A parts based model is a parametrization of an object class using a collection of landmarks following the object structure. The matching of parts based models is one of the problems where pairwise Conditional Random Fields have been successfully applied. The main reason of their effectiveness is tractable inference and learning due to the simplicity of involved graphs, usually trees. However, these models do not consider possible patterns of statistics among sets of landmarks, and thus they sufffer from using too myopic information. To overcome this limitation, we propoese a novel structure based on a hierarchical Conditional Random Fields, which we explain in the first part of this memory. We build a hierarchy of combinations of landmarks, where matching is performed taking into account the whole hierarchy. To preserve tractable inference we effectively sample the label set. We test our method on facial feature selection and human pose estimation on two challenging datasets: Buffy and MultiPIE. In the second part of this memory, we present a novel approach to multiple kernel combination that relies on stacked classification. This method can be used to evaluate the landmarks of the parts-based model approach. Our method is based on combining responses of a set of independent classifiers for each individual kernel. Unlike earlier approaches that linearly combine kernel responses, our approach uses them as inputs to another set of classifiers. We will show that we outperform state-of-the-art methods on most of the standard benchmark datasets.

Schistosomiasis mansoni: follow-up of control program based on parasitologic and serologic methods in a Brazilian community of low endemicity

A field survey on schistosomiais was carried out in 1998, in the municipality of Pedro de Toledo, a low endemic area in the state of São Paulo, Brazil. According to the parasitologic Kato-Katz method, the prevalence rate was 1.6%, with an infection intensity of 40.9 eggs per gram of stool. By the immunofluorescence test (IFT) for detection of IgG and IgM antibodies in the serum, IgG-IFT and IgM-IFT, respectively, prevalence indices of 33.2% and 33.5% were observed. To assess the impact of the schistosomiasis control program in the area, parasitologic and serologic data obtained in 1998, analyzed according to the age, sex, and residence zone, were compared to previous data obtained in a epidemiologic study carried out in 1980, when prevalence indices were of 22.8% and 55.5%, respectively by Kato-Katz and IgG-IFT. A significant fall of the prevalence was observed, indicating that the control measures were effective. Nonetheless, residual transmission was observed, demonstrating the need for a joint effort to include new approaches for better understanding the real situation and improving the control of the disease in low endemic areas.

Molecular approaches for the detection of Schistosoma mansoni: possible applications in the detection of snail infection, monitoring of transmission sites, and diagnosis of human infection

The detection of specific DNA sequences by polymerase chain reaction (PCR) has proved extremely valuable for the analysis of genetic disorders and the diagnosis of a variety of infectious disease pathogens. However, the application to the detection of Schistosoma mansoni is rare, despite a recommendation of the World Health Organization that a major focus of research on schistosomiasis should be on the development and evaluation of new strategies and tools for control of the disease. In this context, a few studies were published for the detection of the parasite in snails, monitoring of cercariae in water bodies, and diagnosis of human infection. The present minireview describes sensitive and specific PCR based systems to detect S. mansoni, indicating possible applications in the detection of snail infection, monitoring of transmission sites, and diagnosis of human infection.

Developing new approaches for detecting and preventing Aedes aegypti population outbreaks: basis for surveillance, alert and control system

A new approach to dengue vector surveillance based on permanent egg-collection using a modified ovitrap and Bacillus thuringiensis israelensis(Bti) was evaluated in different urban landscapes in Recife, Northeast Brazil. From April 2004 to April 2005, 13 egg-collection cycles of four weeks were carried out. Geo-referenced ovitraps containing grass infusion, Bti and three paddles were placed at fixed sampling stations distributed over five selected sites. Continuous egg-collections yielded more than four million eggs laid into 464 sentinel-ovitraps over one year. The overall positive ovitrap index was 98.5% (over 5,616 trap observations). The egg density index ranged from 100 to 2,500 eggs per trap-cycle, indicating a wide spread and high density of Aedes aegypti (Diptera: Culicidae) breeding populations in all sites. Fluctuations in population density over time were observed, particularly a marked increase from January on, or later, according to site. Massive egg-collection carried out at one of the sites prevented such a population outbreak. At intra-site level, egg counts made it possible to identify spots where the vector population is consistently concentrated over the time, pinpointing areas that should be considered high priority for control activities. The results indicate that these could be promising strategies for detecting and preventing Ae. aegypti population outbreaks.

Approaches to OER Development

OER development is becoming more sophisticated as instructors and course specialists become more familiar with the environment. Most OER development approaches for online courses have been developed from those that were appropriate in the face-to-face context. However, the OER online environment opens up new possibilities for learning as well as holding particular limitations. This paper presents some approaches that OER implementers should bear in mind when initiating and supporting OER course development projects.1. Beg, borrow, or steal courseware. Don't reinvent the wheel.2. Take what exists and build the course around it.3. Mix and match. Assemble. Don't create.4. Avoid the "not invented here" syndrome. 5. Know the content -garbage in and garbage out.6. Establish deadlines. Work to deadlines, but don't be unrealistic. 7. Estimate your costs and then double them. Double them again. 8. Be realistic in scheduling and scoping.9. The project plan must be flexible. Be prepared for major shifts.10. Build flexibly for reuse and repurposing -generalizability reduces costs 11. Provide different routes to learning. 12. Build to international standards.There are necessary features in every OER, including introduction, schedule etc. but it is most important to keep the course as simple as possible. Extreme Programming (XP) methodology can be adapted from software engineering to aid in the course development process.

A discrete forest in a continuous landscape : investigating interactions between natural resource management and sustainable development

Summary Forests are key ecosystems of the earth and associated with a large range of functions. Many of these functions are beneficial to humans and are referred to as ecosystem services. Sustainable development requires that all relevant ecosystem services are quantified, managed and monitored equally. Natural resource management therefore targets the services associated with ecosystems. The main hypothesis of this thesis is that the spatial and temporal domains of relevant services do not correspond to a discrete forest ecosystem. As a consequence, the services are not quantified, managed and monitored in an equal and sustainable manner. The thesis aims were therefore to test this hypothesis, establish an improved conceptual approach and provide spatial applications for the relevant land cover and structure variables. The study was carried out in western Switzerland and based primarily on data from a countrywide landscape inventory. This inventory is part of the third Swiss national forest inventory and assesses continuous landscape variables based on a regular sampling of true colour aerial imagery. In addition, land cover variables were derived from Landsat 5 TM passive sensor data and land structure variables from active sensor data from a small footprint laserscanning system. The results confirmed the main hypothesis, as relevant services did not scale well with the forest ecosystem. Instead, a new conceptual approach for sustainable management of natural resources was described. This concept quantifies the services as a continuous function of the landscape, rather than a discrete function of the forest ecosystem. The explanatory landscape variables are therefore called continuous fields and the forest becomes a dependent and function-driven management unit. Continuous field mapping methods were established for land cover and structure variables. In conclusion, the discrete forest ecosystem is an adequate planning and management unit. However, monitoring the state of and trends in sustainability of services requires them to be quantified as a continuous function of the landscape. Sustainable natural resource management iteratively combines the ecosystem and gradient approaches. Résumé Les forêts sont des écosystèmes-clés de la terre et on leur attribue un grand nombre de fonctions. Beaucoup de ces fonctions sont bénéfiques pour l'homme et sont nommées services écosystémiques. Le développement durable exige que ces services écosystémiques soient tous quantifiés, gérés et surveillés de façon égale. La gestion des ressources naturelles a donc pour cible les services attribués aux écosystèmes. L'hypothèse principale de cette thèse est que les domaines spatiaux et temporels des services attribués à la forêt ne correspondent pas à un écosystème discret. Par conséquent, les services ne sont pas quantifiés, aménagés et surveillés d'une manière équivalente et durable. Les buts de la thèse étaient de tester cette hypothèse, d'établir une nouvelle approche conceptuelle de la gestion des ressources naturelles et de préparer des applications spatiales pour les variables paysagères et structurelles appropriées. L'étude a été menée en Suisse occidentale principalement sur la base d'un inventaire de paysage à l'échelon national. Cet inventaire fait partie du troisième inventaire forestier national suisse et mesure de façon continue des variables paysagères sur la base d'un échantillonnage régulier sur des photos aériennes couleur. En outre, des variables de couverture ? terrestre ont été dérivées des données d'un senseur passif Landsat 5 TM, ainsi que des variables structurelles, dérivées du laserscanning, un senseur actif. Les résultats confirment l'hypothèse principale, car l'échelle des services ne correspond pas à celle de l'écosystème forestier. Au lieu de cela, une nouvelle approche a été élaborée pour la gestion durable des ressources naturelles. Ce concept représente les services comme une fonction continue du paysage, plutôt qu'une fonction discrète de l'écosystème forestier. En conséquence, les variables explicatives de paysage sont dénommées continuous fields et la forêt devient une entité dépendante, définie par la fonction principale du paysage. Des méthodes correspondantes pour la couverture terrestre et la structure ont été élaborées. En conclusion, l'écosystème forestier discret est une unité adéquate pour la planification et la gestion. En revanche, la surveillance de la durabilité de l'état et de son évolution exige que les services soient quantifiés comme fonction continue du paysage. La gestion durable des ressources naturelles joint donc l'approche écosystémique avec celle du gradient de manière itérative.

Use of a saline gradient for the diagnosis of schistosomiasis

The development of novel methods for parasitological diagnosis that are both highly sensitive and low in cost has been strongly recommended by the World Health Organization. In this study, a new technique for diagnosis of schistosomiasis mansoni is proposed based on the differential sedimentation of eggs when subjected to a slow continuous flux of 3% saline solution through a porous plaque. This influx suspends low-density faecal material, effectively cleaning the sample. The remaining sediment covering the porous plaque surface is then transferred to a glass slide and examined under a bright field microscope. Twelve Kato-Katz slides were used for comparison in the present study. Our results suggest that the saline gradient method detects a signifi-cantly higher number of eggs than the 12 Kato-Katz slides (p < 0.0001). We also found microscopic inspection to be quicker and easier with our newly described method. After cleaning the sample, the obtained sediment can also be conserved in a 10% formaldehyde solution and examined for at least 45 days later without statistically significant egg count differences.

Two approaches to discovering and developing new drugs for Chagas disease

This review will focus on two general approaches carried out at the Sandler Center, University of California, San Francisco, to address the challenge of developing new drugs for the treatment of Chagas disease. The first approach is target-based drug discovery, and two specific targets, cytochrome P450 CYP51 and cruzain (aka cruzipain), are discussed. A "proof of concept" molecule, the vinyl sulfone inhibitor K777, is now a clinical candidate. The preclinical assessment compliance for filing as an Investigational New Drug with the United States Food and Drug Administration (FDA) is presented, and an outline of potential clinical trials is given. The second approach to identifying new drug leads is parasite phenotypic screens in culture. The development of an assay allowing high throughput screening of Trypanosoma cruzi amastigotes in skeletal muscle cells is presented. This screen has the advantage of not requiring specific strains of parasites, so it could be used with field isolates, drug resistant strains or laboratory strains. It is optimized for robotic liquid handling and has been validated through a screen of a library of FDA-approved drugs identifying 65 hits.

A compositional data analysis package for R providing multiple approaches

”compositions” is a new R-package for the analysis of compositional and positive data.It contains four classes corresponding to the four different types of compositional andpositive geometry (including the Aitchison geometry). It provides means for computation,plotting and high-level multivariate statistical analysis in all four geometries.These geometries are treated in an fully analogous way, based on the principle of workingin coordinates, and the object-oriented programming paradigm of R. In this way,called functions automatically select the most appropriate type of analysis as a functionof the geometry. The graphical capabilities include ternary diagrams and tetrahedrons,various compositional plots (boxplots, barplots, piecharts) and extensive graphical toolsfor principal components. Afterwards, ortion and proportion lines, straight lines andellipses in all geometries can be added to plots. The package is accompanied by ahands-on-introduction, documentation for every function, demos of the graphical capabilitiesand plenty of usage examples. It allows direct and parallel computation inall four vector spaces and provides the beginner with a copy-and-paste style of dataanalysis, while letting advanced users keep the functionality and customizability theydemand of R, as well as all necessary tools to add own analysis routines. A completeexample is included in the appendix

An hybrid methodology for RL-based behavior coordination in a target following mission with an AUV

Proposes a behavior-based scheme for high-level control of autonomous underwater vehicles (AUVs). Two main characteristics can be highlighted in the control scheme. Behavior coordination is done through a hybrid methodology, which takes in advantages of the robustness and modularity in competitive approaches, as well as optimized trajectories

Hybrid coordination of reinforcement learning-based behaviors for AUV control

This paper proposes a hybrid coordination method for behavior-based control architectures. The hybrid method takes advantages of the robustness and modularity in competitive approaches as well as optimized trajectories in cooperative ones. This paper shows the feasibility of applying this hybrid method with a 3D-navigation to an autonomous underwater vehicle (AUV). The behaviors are learnt online by means of reinforcement learning. A continuous Q-learning implemented with a feed-forward neural network is employed. Realistic simulations were carried out. The results obtained show the good performance of the hybrid method on behavior coordination as well as the convergence of the behaviors