984 resultados para Use tax


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Since land use change can have significant impacts on regional biogeochemistry, we investigated how conversion of forest and cultivation to pasture impact soil C and N cycling. In addition to examining total soil C, we isolated soil physiochemical C fractions in order to understand the mechanisms by which soil C is sequestered or lost. Total soil C did not change significantly over time following conversion from forest, though coarse (250-2,000 mum) particulate organic matter C increased by a factor of 6 immediately after conversion. Aggregate mean weight diameter was reduced by about 50% after conversion, but values were like those under forest after 8 years under pasture. Samples collected from a long-term pasture that was converted from annual cultivation more than 50 years ago revealed that some soil physical properties negatively impacted by cultivation were very slow to recover. Finally, our results indicate that soil macroaggregates turn over more rapidly under pasture than under forest and are less efficient at stabilizing soil C, whereas microaggregates from pasture soils stabilize a larger concentration of C than forest microaggregates. Since conversion from forest to pasture has a minimal impact on total soil C content in the Piedmont region of Virginia, United States, a simple C stock accounting system could use the same base soil C stock value for either type of land use. However, since the effects of forest to pasture conversion are a function of grassland management following conversion, assessments of C sequestration rates require activity data on the extent of various grassland management practices.

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Changes in grassland management intended to increase productivity can lead to sequestration of substantial amounts of atmospheric C in soils. Management-intensive grazing (MiG) can increase forage production in mesic pastures, but potential impacts on soil C have not been evaluated. We sampled four pastures (to 50 cm depth) in Virginia, USA, under MiG and neighboring pastures that were extensively grazed or bayed to evaluate impacts of grazing management on total soil organic C and N pools, and soil C fractions. Total organic soil C averaged 8.4 Mg C ha(-1) (22%) greater under MiG; differences were significant at three of the four sites examined while total soil N was greater for two sites. Surface (0-10 cm) particulate organic matter (POM) C increased at two sites; POM C for the entire depth increment (0-50 cm) did not differ significantly between grazing treatments at any of the sites. Mineral-associated C was related to silt plus clay content and tended to be greater under MiG. Neither soil C:N ratios, POM C, or POM C:total C ratios were accurate indicators of differences in total soil C between grazing treatments, though differences in total soil C between treatments attributable to changes in POM C (43%) were larger than expected based on POM C as a percentage of total C (24.5%). Soil C sequestration rates, estimated by calculating total organic soil C differences between treatments (assuming they arose from changing grazing management and can be achieved elsewhere) and dividing by duration of treatment, averaged 0.41 Mg C ha(-1) year(-1) across the four sites.

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More than 13 Mha of nonfederal land in the southeastern U.S. are devoted to pastureland. Between 1982 and 1992, pastureland increased by 100,000 ha, with nearly 70% converted from cultivated land. We examined the potential for carbon (C) sequestration with improved pasture management and conversion into pastureland from cultivated land. Improved pasture management techniques, such as intensive grazing, fertilization, introduction of improved grass and legume species, and better irrigation systems can lead to sequestration of atmospheric C in soil. Literature values for the influence of changes in pasture management on soil C were summarized for several potential management changes in the Southeast. Soil C sequestration estimates for the Southeast were based on current pasture management practices and evaluated for a range of different adoption rates of improved practices. Conversion into pasture can also potentially sequester significant amounts of atmospheric C in soils. Land-use data from the National Resources Inventory and literature estimates of soil C changes following conversion to pasture were used to estimate historical (1982 to 1992) soil C sequestration in pastures. Potential future sequestration was estimated based on extrapolation of land-use trends between 1982 and 1992. With continued conversion into pasture and improvement of pasture management, southeastern U.S. pasture soils may be a significant C sink for several years.

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In this paper we propose a new method for utilising phase information by complementing it with traditional magnitude-only spectral subtraction speech enhancement through Complex Spectrum Subtraction (CSS). The proposed approach has the following advantages over traditional magnitude-only spectral subtraction: (a) it introduces complementary information to the enhancement algorithm; (b) it reduces the total number of algorithmic parameters, and; (c) is designed for improving clean speech magnitude spectra and is therefore suitable for both automatic speech recognition (ASR) and speech perception applications. Oracle-based ASR experiments verify this approach, showing an average of 20% relative word accuracy improvements when accurate estimates of the phase spectrum are available. Based on sinusoidal analysis and assuming stationarity between observations (which is shown to be better approximated as the frame rate is increased), this paper also proposes a novel method for acquiring the phase information called Phase Estimation via Delay Projection (PEDEP). Further oracle ASR experiments validate the potential for the proposed PEDEP technique in ideal conditions. Realistic implementation of CSS with PEDEP shows performance comparable to state of the art spectral subtraction techniques in a range of 15-20 dB signal-to-noise ratio environments. These results clearly demonstrate the potential for using phase spectra in spectral subtractive enhancement applications, and at the same time highlight the need for deriving more accurate phase estimates in a wider range of noise conditions.

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This paper uses a multivariate analysis to examine how countries‘ tax morale and institutional quality affect the shadow economy. The literature strongly emphasizes the quantitative importance of these factors in understanding the level of and changes in the shadow economy. Newly available data sources offer the unique opportunity to further illuminate a topic that has received increased attention. After controlling for a variety of potential factors, we find strong support that a higher tax morale and a higher institutional quality lead to a smaller shadow economy.

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This article reviews what international evidence exists on the impact of civil and criminal sanctions upon serious tax noncompliance by individuals. This construct lacks sharp definitional boundaries but includes large tax fraud and large-scale evasion that are not dealt with as fraud. Although substantial research and theory have been developed on general tax evasion and compliance, their conclusions might not apply to large-scale intentional fraudsters. No scientifically defensible studies directly compared civil and criminal sanctions for tax fraud, although one U.S. study reported that significantly enhanced criminal sanctions have more effects than enhanced audit levels. Prosecution is public, whereas administrative penalties are confidential, and this fact encourages those caught to pay heavy penalties to avoid publicity, a criminal record, and imprisonment.

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Expert panels have been used extensively in the development of the "Highway Safety Manual" to extract research information from highway safety experts. While the panels have been used to recommend agendas for new and continuing research, their primary role has been to develop accident modification factors—quantitative relationships between highway safety and various highway safety treatments. Because the expert panels derive quantitative information in a “qualitative” environment and because their findings can have significant impacts on highway safety investment decisions, the expert panel process should be described and critiqued. This paper is the first known written description and critique of the expert panel process and is intended to serve professionals wishing to conduct such panels.

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In order to examine time allocation patterns within household-level trip-chaining, simultaneous doubly-censored Tobit models are applied to model time-use behavior within the context of household activity participation. Using the entire sample and a sub-sample of worker households from Tucson's Household Travel Survey, two sets of models are developed to better understand the phenomena of trip-chaining behavior among five types of households: single non-worker households, single worker households, couple non-worker households, couple one-worker households, and couple two-worker households. Durations of out-of-home subsistence, maintenance, and discretionary activities within trip chains are examined. Factors found to be associated with trip-chaining behavior include intra-household interactions with the household types and their structure and household head attributes.

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This paper proposes a simple variation of the Allingham and Sandmo (1972) construct and integrates it to a dynamic general equilibrium framework with heterogeneous agents. We study an overlapping generations framework i n which agents must initially decide whether to evade taxes or not. In the event they decide to evade, they then have to decide the extent of income or wealth they wish to under-report. We find that in comparison with the basic approach, the ‘evade or not’ choice drastically reduced the extent of evasion in the economy. This outcome is the result of an anomaly intrinsic to the basic Allingham and Sandmo version of the model, which makes the evade-or-not extension a more suitable approach to modelling the issue. We also find that the basic model, and the model with and ‘evade-or-not’ choice have strikingly different political economy implications, , which suggest fruitful avenues of empirical research.

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In April 2007, the Australian Learning and Teaching Council (ALTC)commissioned a study to examine the diverse approaches to ePortfolio use by students in Australian universities. The goals were to consider the scope, penetration and reasons for use of ePortfolios, and to examine the issues associated with their implementation in higher education. One of the central research activities in the project was a national audit which sought to establish a picture of current and emerging ePortfolio activities in Australian academic institutions. The data collection activities took place in late 2007 and the findings were presented and discussed in the final project report, published in October 2008. In 2010, the idea of a ‘follow up survey’ was developed. The resulting supplementary research activity was undertaken to update the data collected by the AeP project team in late 2007. The plan behind this ‘postscript to AeP’ project was to refresh the picture of ePortfolio practice in Australia by collecting new data to identify and map the use of ePortfolios in adult learning across the higher education, vocational education and training (VET) and the adult community education (ACE) sectors. The supplementary project has been referred to as the ‘AeP PS survey’.

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A novel application of the popular web instruction architecture Blackboard Academic Suite® is described. The method was applied to a large number of students to assess quantitatively the accuracy of each student’s laboratory skills. The method provided immediate feedback to students on their personal skill level, replaced labour-intensive scrutiny of laboratory skills by teaching staff and identified immediately those students requiring further individual assistance in mastering the skill under evaluation. The method can be used for both formative and summative assessment. When used formatively, the assessment can be repeated by the student without penalty until the skill is mastered. When used for summative assessment, the method can save the teacher much time and effort in assessing laboratory skills of vital importance to students in the real world.

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Type unions, pointer variables and function pointers are a long standing source of subtle security bugs in C program code. Their use can lead to hard-to-diagnose crashes or exploitable vulnerabilities that allow an attacker to attain privileged access over classified data. This paper describes an automatable framework for detecting such weaknesses in C programs statically, where possible, and for generating assertions that will detect them dynamically, in other cases. Exclusively based on analysis of the source code, it identifies required assertions using a type inference system supported by a custom made symbol table. In our preliminary findings, our type system was able to infer the correct type of unions in different scopes, without manual code annotations or rewriting. Whenever an evaluation is not possible or is difficult to resolve, appropriate runtime assertions are formed and inserted into the source code. The approach is demonstrated via a prototype C analysis tool.

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Background For CAM to feature prominently in health care decision-making there is a need to expand the evidence-base and to further incorporate economic evaluation into research priorities. In a world of scarce health care resources and an emphasis on efficiency and clinical efficacy, CAM, as indeed do all other treatments, requires rigorous evaluation to be considered in budget decision-making. Methods Economic evaluation provides the tools to measure the costs and health consequences of CAM interventions and thereby inform decision making. This article offers CAM researchers an introductory framework for understanding, undertaking and disseminating economic evaluation. The types of economic evaluation available for the study of CAM are discussed, and decision modelling is introduced as a method for economic evaluation with much potential for use in CAM. Two types of decision models are introduced, decision trees and Markov models, along with a worked example of how each method is used to examine costs and health consequences. This is followed by a discussion of how this information is used by decision makers. Conclusions Undoubtedly, economic evaluation methods form an important part of health care decision making. Without formal training it can seem a daunting task to consider economic evaluation, however, multidisciplinary teams provide an opportunity for health economists, CAM practitioners and other interested researchers, to work together to further develop the economic evaluation of CAM.

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Measuring the comparative sustainability levels of cities, regions, institutions and projects is an essential procedure in creating sustainable urban futures. This paper introduces a new urban sustainability assessment model: “The Sustainable Infrastructure, Land-use, Environment and Transport Model (SILENT)”. The SILENT Model is an advanced geographic information system and indicator-based comparative urban sustainability indexing model. The model aims to assist planners and policy makers in their daily tasks in sustainable urban planning and development by providing an integrated sustainability assessment framework. The paper gives an overview of the conceptual framework and components of the model and discusses the theoretical constructs, methodological procedures, and future development of this promising urban sustainability assessment model.

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Software used by architectural and industrial designers – has moved from becoming a tool for drafting, towards use in verification, simulation, project management and project sharing remotely. In more advanced models, parameters for the designed object can be adjusted so a family of variations can be produced rapidly. With advances in computer aided design technology, numerous design options can now be generated and analyzed in real time. However the use of digital tools to support design as an activity is still at an early stage and has largely been limited in functionality with regard to the design process. To date, major CAD vendors have not developed an integrated tool that is able to both leverage specialized design knowledge from various discipline domains (known as expert knowledge systems) and support the creation of design alternatives that satisfy different forms of constraints. We propose that evolutionary computing and machine learning be linked with parametric design techniques to record and respond to a designer’s own way of working and design history. It is expected that this will lead to results that impact on future work on design support systems-(ergonomics and interface) as well as implicit constraint and problem definition for problems that are difficult to quantify.