Assessing Importance and Satisfaction Judgments of Intermodal Work Commuters with Electronic Survey Methodology, MTI Report WP 12-01

Recent advances in multivariate methodology provide an opportunity to further the assessment of service offerings in public transportation for work commuting. We offer methodologies that are alternative to direct rating scale and have advantages in the quality and precision of measurement. The alternative of methodology for adaptive conjoint analysis for the measurement of the importance of attributes in service offering is implemented. Rasch scaling methodology is used for the measurement of satisfaction with these attributes. Advantages that these methodologies introduce for assessment of the respective constructs and use of the assessment are discussed. In a first study, the conjoint derived weights were shown to have predictive capabilities in applications to respondent distributions of a fixed total budget to improve overall service offerings. Results with the Rasch model indicate that the attribute measures are reliable and can adequately constitute a composite measure of satisfaction. The Rasch items were also shown to provide a basis to discriminate between privately owned vehicles (POVs) and public transport commuters. Dissatisfaction with uncertainty in travel time and income level of respondents were the best predictors of POV commuting

Tree Function and Habitat Niche Partitioning in Tropical Forests: Implications for Responses to Environmental Change

Tropical forests possess exceptional levels of tree species richness but explaining this diversity has presented a long existing challenge. Habitat niche partitioning provides a hypothesis for species co-existence, whereby species avoid competitive exclusion by partitioning demands on multiple resources within an environment. However, limited understanding concerning how tree function is influenced by multiple environmental variables has limited the support for this hypothesis. This knowledge gap also limits our ability to predict how tropical forest tree communities will respond to environmental change, given multiple dimensions of a species’ niche are likely to be affected. In this thesis, I investigate the role of niche partitioning in supporting co-existence of species and the turnover of species across edaphic gradients, as well as how long-term changes to the environment from selective logging and drought affect niche space of tropical tree species. I use species distribution models and measurements of leaf physiological traits to determine the key dimensions of tree species’ niches in primary forests. In chapter 2 I demonstrate niche partitioning is strong within tropical forests with at least 60-86% of abundant species occupying their own unique niche. Species partition a wide range of abiotic environments, including soil nutrient, topographic and light environments, with greater environmental heterogeneity enhancing the scope for niche partitioning. Building on this, in chapter 3 I find that variation in nutrient availability explains more variation in leaf physiology and habitat preferences than light availability of species from the Dipterocarpaceae family that dominates South-East Asian forests. This highlights the importance of edaphic environments in structuring tropical forest communities. I also find different leaf nutrients are related to photosynthetic capacity in different forest types, revealing that multiple different nutrients may limit productivity and affect species distributions in tropical forests. Many tropical forest tree species are highly specialised with limited ability to adjust their traits between environments, underlining their potential vulnerability to environmental change. In chapter 4 I show seedlings from selectively logged Bornean forests have different community weighted mean trait values, with greater belowground investment in logged forests. These adaptations are sufficient to overcome soil stress and to maintain foliar nutrient concentrations. However, I show seedlings of species that dominate old-growth forests are less able to adapt their traits and experience elevated mortality rates in logged forests. I attribute this to greater soil nutrient limitation as they are unable to maintain leaf nutrient concentrations. Selective logging will therefore likely drive shifts in species composition towards greater dominance of earlier-successional species that have traits capable of surviving in disturbed environments. This could result in local-scale reductions in species diversity and functional diversity, which could reduce long-term resilience to environmental change. In contrast, in Chapter 5 I demonstrate small trees in Amazonian forests are able to respond to changes in their environment following long-term drought conditions. Following mortality of large canopy trees, small trees can respond to increased light availability even under reduced water availability by adjusting resource allocation and by increasing nutrient use efficiency. Despite evidence of resilience to long-term drought conditions, hyper-dominant species show a greater capacity to respond, which may further enhance the dominance of these species under future climates. In conclusion my results highlight the importance of habitat niche partitioning in structuring tropical forest tree communities and identify key environmental variables that determine species distribution and tree function. My results have important implications for the conservation and restoration of tropical forests under environmental change. Avoidance of environmental homogenisation and changes to as few environmental conditions as possible is likely to be important in maintaining high species diversity in tropical forests and to avoid increased dominance by few generalist species. Many current conservation and restoration projects focus on recovering vegetation, but my research highlights the additional need to maintain and restore soil environments, especially for the long-term persistence of highly specialist species

Development of methods based on voltammetry for the characterisation of liquids

The growing interest into multi-sensor systems able to determine general attributes of a process under monitoring, has recently involved the qualitative analysis of liquids; various methodologies to develop taste sensors, often referred to as “e-tongues” have been presented in the literature. The common concept in the different approaches, lies in the combination of signals originated by poorly specific sensors for the characterization of liquids. The fundamental idea of this PhD work is to investigate how an adequate signal processing approach, applied to a mature and affordable sensor technique (voltammetry), can address the issue of extracting an aggregate chemical information, useful to characterize the liquid under measurement. In this Thesis, a general description of electronic taste sensor systems is given, followed by a description of the working principles of e-tongues based on voltammetry. Then, the methodology that represents the core of this PhD Thesis work is introduced: the sensor device, the control software and the data processing approach are described in this sequence. Finally, a few case studies are shown, selected according to their relevancy with respect to the peculiarities of the approach described in this Thesis

A Generic Software Architecture For Prognostics

Prognostics is a systems engineering discipline focused on predicting end-of-life of components and systems. As a relatively new and emerging technology, there are few fielded implementations of prognostics, due in part to practitioners perceiving a large hurdle in developing the models, algorithms, architecture, and integration pieces. As a result, no open software frameworks for applying prognostics currently exist. This paper introduces the Generic Software Architecture for Prognostics (GSAP), an open-source, cross-platform, object-oriented software framework and support library for creating prognostics applications. GSAP was designed to make prognostics more accessible and enable faster adoption and implementation by industry, by reducing the effort and investment required to develop, test, and deploy prognostics. This paper describes the requirements, design, and testing of GSAP. Additionally, a detailed case study involving battery prognostics demonstrates its use

Carbon pool dynamics after variable retention harvesting in Nothofagus pumilio forests of Tierra del Fuego

Background It is necessary to determine the implications for managing forest stands using variable retention harvesting for maintaining carbon and for calculating the effects of different harvesting practices on above‑ and belowground carbon balance in forest ecosystems. In this context, forest carbon management has gained more attention among managers and policy‑makers during recent years. The aim of this study was to determine carbon pool dynamics in different forest ecosystem components after variable retention harvesting (VRH) to characterize the ecological stability and quantify the recovery rate through the years‑after‑harvesting (YAH). Methods Carbon pool compartmentalization of 14 different components was determined in 60 harvested and primary unmanaged forests during the first 18 YAH in Tierra del Fuego (Argentina). We compared them using uni‑ and multi‑variate methods, relativizing the outputs with primary unmanaged forests. Results We determined the effectiveness to retain carbon components in post‑harvested stands under different retention strategies (aggregated vs. dispersed). The balance among carbon pool components changed between managed and unmanaged stands across the YAH, and was directly related to the impact magnitude. Aggregated retention improved the ecological stability of the harvested areas, where the below‑ground components were more stable than the above‑ground components. The recovery rate was directly related to the post‑harvesting natural dynamics of the stands. The studied period was not enough to fully recover the C levels of primary unmanaged forests, but VRH showed advantages to increase the C pools in the managed stands. Conclusions Promoting VRH can improve sustainable forestry at the landscape level and in the long term, generating positive synergies with biodiversity and the provision of ecosystem services. This study provides important new insights into forest carbon management, in particular to setting standards in carbon projects and sets the groundwork for analysing the economics of the mentioned harvesting systems.EEA Santa CruzFil: Chaves, Jimena Elizabeth. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC); Argentina.Fil: Aravena Acuña, Marie Claire. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC). Laboratorio de Recursos Agroforestales; Argentina.Fil: Rodríguez‑Souilla, Julián. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC); Argentina.Fil: Cellini, Juan Manuel. Universidad Nacional de la Plata. Facultad de Ciencias Naturales y Museo. Laboratorio de Investigaciones en Maderas; Argentina.Fil: Rappa, Nolan J. University of Freiburg. Nature Conservation & Landscape Ecology; AlemaniaFil: Lencinas, María Vanessa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC); Argentina.Fil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina.Fil: Peri, Pablo Luis. Universidad Nacional de la Patagonia Austral; Argentina.Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Martínez Pastur, Guillermo José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC); Argentina

Advances in Public Transport Platform for the Development of Sustainability Cities

Modern societies demand high and varied mobility, which in turn requires a complex transport system adapted to social needs that guarantees the movement of people and goods in an economically efficient and safe way, but all are subject to a new environmental rationality and the new logic of the paradigm of sustainability. From this perspective, an efficient and flexible transport system that provides intelligent and sustainable mobility patterns is essential to our economy and our quality of life. The current transport system poses growing and significant challenges for the environment, human health, and sustainability, while current mobility schemes have focused much more on the private vehicle that has conditioned both the lifestyles of citizens and cities, as well as urban and territorial sustainability. Transport has a very considerable weight in the framework of sustainable development due to environmental pressures, associated social and economic effects, and interrelations with other sectors. The continuous growth that this sector has experienced over the last few years and its foreseeable increase, even considering the change in trends due to the current situation of generalized crisis, make the challenge of sustainable transport a strategic priority at local, national, European, and global levels. This Special Issue will pay attention to all those research approaches focused on the relationship between evolution in the area of transport with a high incidence in the environment from the perspective of efficiency

Structural health monitoring of civil infrastructure

Structural health monitoring (SHM) is a term increasingly used in the last decade to describe a range of systems implemented on full-scale civil infrastructures and whose purposes are to assist and inform operators about continued 'fitness for purpose' of structures under gradual or sudden changes to their state, to learn about either or both of the load and response mechanisms. Arguably, various forms of SHM have been employed in civil infrastructure for at least half a century, but it is only in the last decade or two that computer-based systems are being designed for the purpose of assisting owners/operators of ageing infrastructure with timely information for their continued safe and economic operation. This paper describes the motivations for and recent history of SHM applications to various forms of civil infrastructure and provides case studies on specific types of structure. It ends with a discussion of the present state-of-the-art and future developments in terms of instrumentation, data acquisition, communication systems and data mining and presentation procedures for diagnosis of infrastructural 'health'

Approach to identify product and process state drivers in manufacturing systems using supervised machine learning

The developed concept allows identifying relevant state drivers of complex, multi-stage manufacturing systems holistically. It is able to utilize complex, diverse and high-dimensional data sets which often occur in manufacturing applications and integrate the important process intra- and inter-relations. The evaluation was conducted by using three different scenarios from distinctive manufacturing domains (aviation, chemical and semiconductor). The evaluation confirmed that it is possible to incorporate implicit process intra- and inter-relations on process as well as programme level through applying SVM based feature ranking. The analysis outcome presents a direct benefit for practitioners in form of the most important process parameters and state characteristics, so-called state drivers, of a manufacturing system. Given the increasing availability of data and information, this selection support can be directly utilized in, e.g., quality monitoring and advanced process control

Leeway for the loyal: a model of employee discretion

This article examines the factors underlying task discretion from an economist's perspective. It argues that the key axis for understanding discretion is the trade-off between the positive effects of discretion on potential output per employee and the negative effects of greater leeway on work effort. In empirical analysis using matched employer-employee data, it is shown that discretion is strongly affected by the level of employee commitment. In addition, discretion is generally greater in high-skilled jobs, although not without exceptions, and lower where employees are under-skilled. Homeworking and flexitime policies raise employee discretion. The impact of teamworking is mixed. In about half of cases team members do not jointly decide about work matters, and the net effect of teams on task discretion in these cases is negative. In other cases, where team members do decide matters jointly, the impact is found to be neutral according to employees' perceptions, or positive according to managers' perceptions. There are also significant and substantial unobserved establishment-level factors which affect task discretion