Defining Next Generation Supply Chain Sustainability

The importance of understanding supply chain sustainability is being realized by increasingly more people, including corporate managers, investors, policy makers, customers and other stakeholders. A lot of practitioners and academic researchers have addressed this issue in past few years. However, most of their studies lack systematic thinking and are not quantifiable. Thus, a systematic and quantifiable model which incorporates economic, environmental and social factors is needed. In our study, a systematic and quantifiable risk assessment model based on the concept of “Triple Bottom Line” is developed in order to solve supply chain sustainability problem from risk assessment perspectiveMaster of ScienceNatural Resources and EnvironmentUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/110983/1/276-Defining Next Generation Supply Chain Sustainability_2015.pd

The Perception/Action loop: A Study on the Bandwidth of Human Perception and on Natural Human Computer Interaction for Immersive Virtual Reality Applications

Virtual Reality (VR) is an innovating technology which, in the last decade, has had a widespread success, mainly thanks to the release of low cost devices, which have contributed to the diversification of its domains of application. In particular, the current work mainly focuses on the general mechanisms underling perception/action loop in VR, in order to improve the design and implementation of applications for training and simulation in immersive VR, especially in the context of Industry 4.0 and the medical field. On the one hand, we want to understand how humans gather and process all the information presented in a virtual environment, through the evaluation of the visual system bandwidth. On the other hand, since interface has to be a sort of transparent layer allowing trainees to accomplish a task without directing any cognitive effort on the interaction itself, we compare two state of the art solutions for selection and manipulation tasks, a touchful one, the HTC Vive controllers, and a touchless vision-based one, the Leap Motion. To this aim we have developed ad hoc frameworks and methodologies. The software frameworks consist in the creation of VR scenarios, where the experimenter can choose the modality of interaction and the headset to be used and set experimental parameters, guaranteeing experiments repeatability and controlled conditions. The methodology includes the evaluation of performance, user experience and preferences, considering both quantitative and qualitative metrics derived from the collection and the analysis of heterogeneous data, as physiological and inertial sensors measurements, timing and self-assessment questionnaires. In general, VR has been found to be a powerful tool able to simulate specific situations in a realistic and involving way, eliciting user\u2019s sense of presence, without causing severe cybersickness, at least when interaction is limited to the peripersonal and near-action space. Moreover, when designing a VR application, it is possible to manipulate its features in order to trigger or avoid triggering specific emotions and voluntarily create potentially stressful or relaxing situations. Considering the ability of trainees to perceive and process information presented in an immersive virtual environment, results show that, when people are given enough time to build a gist of the scene, they are able to recognize a change with 0.75 accuracy when up to 8 elements are in the scene. For interaction, instead, when selection and manipulation tasks do not require fine movements, controllers and Leap Motion ensure comparable performance; whereas, when tasks are complex, the first solution turns out to be more stable and efficient, also because visual and audio feedback, provided as a substitute of the haptic one, does not substantially contribute to improve performance in the touchless case

Characterisation of a phantom for multiwavelength quantitative photoacoustic imaging

Quantitative photoacoustic imaging (qPAI) has the potential to provide high- resolution in vivo images of chromophore concentration, which may be indicative of tissue function and pathology. Many strategies have been proposed recently for extracting quantitative information, but many have not been experimentally verified. Experimental phantom-based validation studies can be used to test the robustness and accuracy of such algorithms in order to ensure reliable in vivo application is possible. The phantoms used in such studies must have well-characterised optical and acoustic properties similar to tissue, and be versatile and stable. Polyvinyl chloride plastisol (PVCP) has been suggested as a phantom for quality control and system evaluation. By characterising its multiwavelength optical properties, broadband acoustic properties and thermoelastic behaviour, this paper examines its potential as a phantom for qPAI studies too. PVCP's acoustic properties were assessed for various formulations, as well as its intrinsic optical absorption, and scattering with added TiO2, over a range of wavelengths from 400-2000 nm. To change the absorption coefficient, pigment-based chromophores that are stable during the phantom fabrication process, were used. These yielded unique spectra analogous to tissue chromophores and linear with concentration. At the high peak powers typically used in photoacoustic imaging, nonlinear optical absorption was observed. The Grüneisen parameter was measured to be $\Gamma$   =  1.01  ±  0.05, larger than typically found in tissue, though useful for increased PA signal. Single and multiwavelength 3D PA imaging of various fabricated PVCP phantoms were demonstrated

Massively parallel split-step Fourier techniques for simulating quantum systems on graphics processing units

The split-step Fourier method is a powerful technique for solving partial differential equations and simulating ultracold atomic systems of various forms. In this body of work, we focus on several variations of this method to allow for simulations of one, two, and three-dimensional quantum systems, along with several notable methods for controlling these systems. In particular, we use quantum optimal control and shortcuts to adiabaticity to study the non-adiabatic generation of superposition states in strongly correlated one-dimensional systems, analyze chaotic vortex trajectories in two dimensions by using rotation and phase imprinting methods, and create stable, threedimensional vortex structures in Bose–Einstein condensates through artificial magnetic fields generated by the evanescent field of an optical nanofiber. We also discuss algorithmic optimizations for implementing the split-step Fourier method on graphics processing units. All computational methods present in this work are demonstrated on physical systems and have been incorporated into a state-of-the-art and open-source software suite known as GPUE, which is currently the fastest quantum simulator of its kind.Okinawa Institute of Science and Technology Graduate Universit

Improving the Ribozyme Toolbox: From Structure-Function Insights to Synthetic Biology Applications

Self-cleaving ribozymes are a naturally occurring class of catalytically active RNA molecules which cleave their own phosphate backbone. In nature, self-cleaving ribozymes are best known for their role in processing concatamers of viral genomes into monomers during viral replication in some RNA viruses, but to a lesser degree have also been implicated in mRNA regulation and processing in bacteria and eukaryotes. In addition to their biological relevance, these RNA enzymes have been harnessed as important biomolecular tools with a variety of applications in fields such as bioengineering. Self-cleaving ribozymes are relatively small and easy to generate in the lab using common molecular biology approaches, and have therefore been accessible and well exploited model systems used to interrogate RNA sequence-structure-function relationships. Furthermore, self-cleaving ribozymes are also being implemented as parts in the development of various biomolecular tools such as biosensors and gene regulatory elements. While much progress has been made in these areas, there are still challenges associated with the performance and implementation of such tools. The work contained in this dissertation aims to address several of these challenges and improve the ribozyme toolbox in several diverse areas. Chapter one provides an introduction to pertinent background information for this dissertation. Chapter two aims to improve the ribozyme toolbox by providing and analyzing new high-throughput sequence-structure-function data sets on five different self-cleaving ribozymes, and identifying how trends in epistasis relate to distinct structural elements. Chapter three uses such high-throughput data to train machine learning models that accurately predict the historically difficult to predict functional effects of higher order mutations in functional RNA’s. Finally, in chapter four, I developed a biologically relevant platform to study the real time performance and kinetics of self-cleaving ribozyme-based gene regulatory elements directly at the site of transcription in mammalian cells