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Traditionally, Machine Translation (MT) systems are developed by targeting fluency (i.e. output grammaticality) and adequacy (i.e. semantic equivalence with the source text) criteria that reflect the needs of human end-users. However, recent advancements in Natural Language Processing (NLP) and the introduction of NLP tools in commercial services have opened new opportunities for MT. A particularly relevant one is related to the application of NLP technologies in low-resource language settings, for which the paucity of training data reduces the possibility to train reliable services. In this specific condition, MT can come into play by enabling the so-called “translation-based” workarounds. The idea is simple: first, input texts in the low-resource language are translated into a resource-rich target language; then, the machine-translated text is processed by well-trained NLP tools in the target language; finally, the output of these downstream components is projected back to the source language. This results in a new scenario, in which the end-user of MT technology is no longer a human but another machine. We hypothesize that current MT training approaches are not the optimal ones for this setting, in which the objective is to maximize the performance of a downstream tool fed with machine-translated text rather than human comprehension. Under this hypothesis, this thesis introduces a new research paradigm, which we named “MT for machines”, addressing a number of questions that raise from this novel view of the MT problem. Are there different quality criteria for humans and machines? What makes a good translation from the machine standpoint? What are the trade-offs between the two notions of quality? How to pursue machine-oriented objectives? How to serve different downstream components with a single MT system? How to exploit knowledge transfer to operate in different language settings with a single MT system? Elaborating on these questions, this thesis: i) introduces a novel and challenging MT paradigm, ii) proposes an effective method based on Reinforcement Learning analysing its possible variants, iii) extends the proposed method to multitask and multilingual settings so as to serve different downstream applications and languages with a single MT system, iv) studies the trade-off between machine-oriented and human-oriented criteria, and v) discusses the successful application of the approach in two real-world scenarios.

Hurricane Sandy struck the New York City-New Jersey region on October 29, 2012, with severe consequences to the transportation network, including both the road network and the transit system. This study used survey data from nearly 400 commuters in the New York City Metropolitan Area to determine the transportation disruptions and socio-demographic characteristics associated with travel changes and their duration for the home-to-work commute after Hurricane Sandy. Multi-variable binary logit modeling was used to examine mode shifting, cancelling the trip to work, route changing, and modifying departure time. Transit commuters were more likely to change modes, cancel the trip, and depart earlier. Women were less likely to change modes or depart later. Carpool restrictions encouraged mode changing and earlier departures. Delays/crowding increased the probability of route changes, canceled trips, and earlier departures. Durations of commute travel changes were modeled with accelerated failure time approaches (Weibull distribution). New Jersey Transit disruptions prolonged the time to return to the normal working schedule, telecommuting time, and the time of commuting patterns alterations. Gasoline purchase restrictions extended commuting delays and the duration of alteration of normal commute patterns but decreased the duration of the change of working schedule and location. The mode used under normal commute conditions did not have an impact on the duration of the changes, even though it has a significant impact on the selected changes. The results underline the need for policy makers to account for mode-specific populations and lower income commuters during post-disaster recovery periods. / Master of Science

Hurricane Sandy hit New York City on October 29, 2012 and greatly disrupted transportation systems, power systems, work, and schools. This research used survey data from 397 respondents in the NYC Metropolitan Area to develop an agent-based model for capturing commuter behavior and adaptation after the disruption. Six different recovery scenarios were tested to find which systems are more critical to recover first to promote a faster return to productivity. Important factors in the restoration timelines depends on the normal commuting pattern of people in that area. In the NYC Metropolitan Area, transit is one of the common modes of transportation; therefore, it was found that the subway/rail system recovery is the top factor in returning to productivity. When the subway/rail system recovers earlier (with the associated power), more people are able to travel to work and be productive. The second important factor is school and daycare closure (with the associated power and water systems). Parents cannot travel unless they can find a caregiver for their children, even if the transportation system is functional. Therefore, policy makers should consider daycare and school condition as one of the important factors in recovery planning. The next most effective scenario is power restoration. Telework is a good substitute for the physical movement of people to work. By teleworking, people are productive while they skip using the disrupted transportation system. To telework, people need power and communication systems. Therefore, accelerating power restoration and encouraging companies to let their employees' telework can promote a faster return to productivity. Finally, the restoration of major crossings like bridges and tunnels is effective in the recovery process. / Master of Science / Natural and man-made disasters, cause massive destruction of property annually and disrupt the normal economic productivity of an area. Although the occurrence of these disasters cannot be controlled, society can minimize the effects with post-disaster recovery strategies. Hurricane Sandy hit New York City on October 29, 2012 and greatly disrupted transportation systems, power systems, work, and schools. In this research, commuter behavior and adaptation after the hurricane were captured by using a survey data that asked questions from people living in NYC metropolitan area about their commuting behavior before and after Hurricane Sandy. An agent-based model was developed and six different recovery strategies were tested in order to find effective factors in returning people to normal productive life faster. In the NYC Metropolitan Area, transit is one of the common modes of transportation; therefore, it was found that the subway/rail system recovery is the top factor in returning to productivity. The next important factor is school and daycare closure. Parents are responsible for their children, therefore; they may not travel to work when school and daycares are closed. The third important factor is power restoration. To telework, people need power and communication systems. By teleworking, people are productive while they skip using the disrupted transportation system. The final important factor is the restoration of major crossings like bridges and tunnels.

Yes / This paper presents the design of a multi-agent framework that aids engineers in the adaptation of modular production systems. The framework includes general implementations of agents and other software components for self-learning and adaptation, sensor data analysis, system modelling and simulation, as well as human-computer interaction. During an adaptation process, operators make changes to the production system, in order to increase capacity or manufacture a product variant. These changes are automatically captured and evaluated by the framework, building an experience base of adjustments that is then used to infer adaptation knowledge. The architecture of the framework consists of agents divided in two layers: the agents in the lower layer are associated with individual production modules, whereas the agents in the higher layer are associated with the entire production line. Modelling, learning, and adaptations can be performed at both levels, using a semantic model to specify the structure and capabilities of the production system. An evaluation of a prototype implementation has been conducted on an industrial assembly system. The results indicate that the use of the framework in a typical adaptation process provides a significant reduction in time and resources required. / This work was supported in part by the European Commission [grant agreement n. 314762].

No / The design of a network architecture that can efficiently integrate WLAN and cellular networks is a challenging task, particularly when the objective is to make the interoperation between the two networks as seamless and as efficient as possible. To provide end-to-end quality of service (QoS) support is one of the key stages towards such a goal. Due to various constraints, such as the unbalanced capacity of the two systems, handoff from user mobility and unreliable transmission media, end-to-end QoS is difficult to guarantee. In this paper, we propose a generic reservation-based QoS model for the integrated cellular and WLAN networks. It uses an adaptation mechanism to address the above issues and to support end-to-end QoS. The validity of the proposed scheme is demonstrated via simulation experiments. The performance results reveal that this new scheme can considerably improve the system resource utilization and reduce the call blocking probability and handoff dropping probability of the integrated networks while maintaining acceptable QoS to the end users.

Darwin first proposed sexual selection as a process to explain the evolution of extravagant morphological traits in males. Despite being potentially detrimental to individual survival, such traits evolve because they increase a male's reproductive success, and provide a net benefit to their fitness. Mate competition is the source of sexual selection, and healthier, more vigorous males are likely to be superior competitors. Because most genes are likely to impact an individual’s health/vigour, sexual selection should act across much of the genome to favour the same alleles as natural selection, thereby promoting adaptation. On the other side of the coin, adaptation to an environment should enhance male sexual fitness, since it is likely to increase the overall health/vigour of individuals within a population, though tests of this prediction are rare and results are mixed. Taking advantage of a long-term evolution experiment involving replicate populations of Drosophila melanogaster, I performed a reciprocal transplant in which the sexual fitness of males was compared when raised in an environment to which they are well adapted and in one to which they are not. I improved on past tests via a comprehensive measure of male sexual fitness that included pre- and post-copulatory reproductive success in a competitive assay under conditions that closely mirrored those to which the populations have been evolving. I found that sexual fitness was higher in locally-adapted males from these experimental populations, a result that was consistent across environments that also manipulated the context in which mate competition occurred.

Prostaglandins (PGs) are important signalling factors for bone mechanotransduction. The inhibition of cyclooxygenase, responsible for the synthesis of PGs, with non-steroidal anti-inflammatory drugs (NSAIDs) has been shown to influence bone formation induced by mechanical stimulation. The purpose of this study was to examine the timing effects of NSAID administration on: 1) bone formation induced by multiple mechanical loading events in a rat model and 2) the PGE2 response of MLO-Y4 osteocyte like cells stimulated by fluid shear stress. The rat forelimb compression model was used to induce bone formation in male and female rats using a 1-month loading protocol (12 loading sessions). The right forelimbs were loaded and the left forelimbs served as non-loaded controls. NSAIDs were administered orally either before or after loading. Fluorochrome labels were administered to the rats to determine mineral apposition rate (MAR). The NSAIDs examined (indomethacin, NS-398 and ibuprofen) did not significantly affect periosteal MAR, administered either before or after loading, suggesting NSAIDs do not affect bone adaptation to multiple mechanical loading events. To examine in vitro effects of NSAIDs on PGE2 production, an orbital shaker was used to apply fluid shear stress to MLO-Y4 cells seeded in 6-well culture plates. Indomethacin was added to the culture media either before or after loading and media PGE2 concentrations were determined at various time points by enzyme immunoassay. Fluid shear stress increased PGE2 production of MLO-Y4 cells and indomethacin administration inhibited that response when administered both before and after fluid flow. However, PGE2 production was influenced by the media changes that occurred in the in vitro experiments, making it difficult to differentiate between indomethacin effects and media change effects. The in vitro experiments revealed the difficulties of modeling the timing effects of NSAID administration on MLO-Y4 PGE2 production in response to fluid flow. / Thesis / Doctor of Philosophy (PhD) / Bone is a dynamic tissue that can adapt to mechanical loading. Prostaglandins (PGs) are important signalling factors produced by osteocytes, the bone mechanosensing cells, that help to activate various cells and cell processes leading to changes in bone structure. Blocking PG signalling with non-steroidal anti-inflammatory drugs (NSAIDs) has been shown to influence bone formation induced by mechanical stimulation in animals and humans. The purpose of this study was to examine the timing effects of NSAID administration on: 1) bone formation induced by multiple mechanical loading events in rats and 2) the PG production of osteocyte like cells in response to fluid flow stimulation. The results of this study suggest that NSAIDs, administered either before or after loading, do not affect bone responses to multiple mechanical loading events. Further investigation is needed to determine the translatability of these findings to NSAID use around the time of exercise in humans.

The contribution of the human activities to climate change is well understood. Yet integration of climate change considerations in tools designed to govern activities affecting the environment, such as Environmental Impact Assessment (EIA), remains underdeveloped and inconsistently applied. There is no clear direction on what measure of consideration is sufficient for environmental decision-making on potential impacts on the climate for proposed policies, programs, plans and projects. This research reviews progress across a range of 16 EIA regimes and outlines the potential for integration of climate change considerations in EIA. The research used a desk review of EIA literature to identify and assess regulations and guidelines that have been established to promote the integration of climate change in EIA. A typology of levels of integration was developed to guide analysis across multiple EIA regimes. The findings identify a global and growing normative expectation for climate change considerations to be integrated into EIA and describe the range of ways this is done across the regimes selected. Climate change integration in EIA is typically concerned with climate change mitigation, specifically greenhouse gas emissions from proposed developments. Fewer regimes are concerned with climate change adaptation, and in general, an integration deficit is identified for regimes where climate change is partially considered. Several challenges to integrating climate change in EIA are identified, including lack of practice guidelines and regulatory frameworks. Reflecting on the variety of approaches, the discussion extends typologies of integration in EIA to examine and provide a better understanding of substantive consideration of climate change in EIA. Examples of high integration indicate that EIA holds potential to play a substantive role in environmental governance at project level decision making affecting climate change. However, the range of examples also cautions that many domestic obstacles can militate against integration including political, socio-technical, and economic imperatives – particularly those affecting sectoral and scope exclusions. Nevertheless, developments across some regimes indicate leverage points for greater integration, including the role of EIA review to establish new precedents for the relevance of climate change to EIA. Potential future research and practice directions are identified, including development of regulations and practice guidelines, inclusion of climate change adaptation aspects, strengthening postdecision monitoring, application to all relevant sectors and activities, alignment with SEA, and integration across all stages of the EIA process.

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