In-situ Plasma Analysis of Ion Kinetics in the Solar Wind and Hermean Magnetosphere

The heating of the solar wind and its interaction with the unique planetary magnetosphere of Mercury is the primary focus of this work. The first aspect of this study focused on the heavy ion population of the solar wind (A > 4 amu), and how well the signature of the heating process responsible for creating the solar wind is preserved in this heavy ion population. We found that this signature in the heavy ion population is primarily erased (thermalized) via Coulomb collisional interactions with solar wind protons. The heavy ions observed in collisionally young solar wind reveal a clear, stable dependence on mass, along with non-thermal heating that is not in agreement with current predictions based on turbulent transport and kinetic dissipation. Due to its weak magnetic dipole, the solar wind can impinge on the surface of Mercury, one of the processes contributing to the desorption of neutrals and, through ionization, ions that make up the planet’s exosphere. Differentiating between surface mechanisms and analyzing magnetospheric plasma dynamics requires the quantification of a variety of ion species. A detailed forward model and a robust statistical method were created to identify new ion signatures in the measurement space of the FIPS instrument, formerly orbiting Mercury onboard the MESSENGER spacecraft. The recovery of new heavy ions species, including Al, Ne, Si, and Mg, along with tentative recoveries of S, Ar, K, and C, enable in depth studies of the plasma dynamics in the Hermean magnetosphere. The interaction of the solar wind with the bow shock of the Hermean magnetosphere leads to the creation of a foreshock region. New tools and methods were created to enable the analysis of the diffuse and Field Aligned Beam (FAB) populations in unique parameter regime of the Hermean foreshock. One result suggests that the energization process for the observed FABs can be explained by Shock Drift Acceleration, and not limited by the small spatial size of Mercury’s bow shock. Analysis of diffuse populations shows that a connection time limited diffusive shock acceleration is likely responsible for the behavior of the observed energy distributions.PHDAtmospheric, Oceanic & Space ScienceUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/135753/1/ptracy_1.pd

Ion Transport in Temperature Sensitive Polyelectrolytes

Temperature sensors are widely employed and play a key role in many industries, such as automotive vehicles, medical devices, environmental monitoring, and process control. The state-of-the-art thermal sensing elements are made of rigid and costly inorganic materials, such as vanadium oxide and platinum. These materials have limitations for emerging applications such as wearable devices and prosthetic devices. Ideal temperature sensing materials for such applications need to be flexible, reliable under mechanical deformation, and suitable for large-area production. Electrical conductive polymers were found to be a promising solution because of their flexibility and solution processability. However, they often lag in temperature resolution compared to their inorganic counterparts. A recent discovery revealed that the ionic conductivity of crosslinked pectin, a biopolymer extracted from plant cell walls, has a record-high temperature response. It is biocompatible, flexible when hydrated, and solution-processable, making it a strong candidate for wearable temperature sensing and conformal temperature mapping. However, open questions remain about the origin of its temperature sensitivity and the principles governing its ion transport. Furthermore, the heterogeneity of the complex molecular structure of pectin presents challenges to its integration in sensing devices. In this thesis, we study the origin of the high thermal sensitivity in pectin and develop a synthetic polyelectrolyte that mimics its key structure and properties. In Chapter 3, we focus on the ion transport mechanism in crosslinked pectin. We show that the binding between multivalent ions and certain chemical functional groups of pectin plays a critical role in its temperature sensitivity. In Chapter 4, the impact of water content on the ion transport and dielectric processes in crosslinked pectin is also investigated. In the following chapter, we present a novel synthetic polyelectrolyte designed to mimic pectin with a simpler structure. It has superior flexibility, high temperature sensitivity, and is stable under mechanical deformation. To further study this new material, we examine its ion transport dynamics under varying humidity and temperature conditions in Chapter 7. We discover that temperature and humidity have a similar effect on ion transport. Overall, we showed a biomimetic approach to design temperature sensitive polymers where the strong ion-polymer binding is the key to the ultrahigh temperature response.</p

Hardware runtime management for task-based programming models

Task-based programming models allow programmers to express applications as a collection of tasks with dependences. They are simple to use and greatly improve programmability by using software runtimes to exploit task parallelism and heterogeneity over multi-core, many-core and heterogeneous platforms. In these programming models, the runtimes guarantee correct execution order by managing tasks using task-dependence graphs (TDGs). These runtimes are powerful enough to provide high performance with coarse-grained tasks although they impose overheads on the application execution to maintain all the information they need to do their work. However, as the current trend in processor architectures keeps including more cores and heterogeneity (in fact complexity) in the systems, coarse-grained parallelism is not enough to feed all the underlying resources. Instead, fine-grained tasks are preferable as they are able to expose higher parallelism in applications but the overheads introduced by the software runtimes under these conditions prevent an efficient exploitation of fine-grained parallelism. The two most critical runtime overheads are task dependence graph management and task scheduling to heterogeneous systems. We propose a hardware architecture Picos, consisting of a hardware task dependence manager including nested task support, and a heterogeneous task scheduler, to accelerate the critical runtime functions for task-based programming models. With Picos, we aim at extending the benefit of these programming models into exploiting fine-grained task parallelism and heterogeneity. As a proof-of-concept, Three prototypes of Picos have been designed in VHDL and implemented in a System-on-chip platform consisting of regular ARM SMP cores and an integrated FPGA. They also have been analyzed with real benchmarks with OmpSs running and Linux on the platform. The first prototype is a hardware task dependence manager, which has been implemented in a Xilinx Zynq 7000 series SoCs. It is connected to a 2-core ARM Cortex A9 processor, with bare-metal OS integration. With 24 simulated workers, and running real task-dependence analysis in Picos, it scales up to 21x speedup. The second prototype Picos++ extended Picos with an exciting new feature for nested task support in hardware. To the best of our knowledge, this is the first time that such a feature has been support fully in hardware task dependence managers. This prototype is fully integrated in not only hardware, but also with a State-of-the-Art parallel programming model, and with Linux. The third prototype includes both a hardware task dependence manager and a heterogeneous task scheduler. The heterogeneous task scheduler receives ready tasks from the task-dependence manager and then schedule them to hardware execution units that have the estimated earliest finish time. It is implemented in a Xilinx Zynq Ultrascale+ MPSoC chip. In a system with 4 threads and up to 15 HW accelerators, it achieves up to 16.2x speedup for real benchmarks, and saves up to 90% of energy.Los modelos de programación basados en tareas permiten a los programadores expresar las aplicaciones como una colección de tareas con dependencias entre ellas. Dichos modelos son simples de usar y mejoran enormemente la programabilidad. Para ello se valen del uso de una runtime que en tiempo de ejecución ayuda a explotar el paralelismo de las tareas cuando se ejecutan en plataformas multi-cores, many-cores y heterogéneas. En estos modelos de programación los runtimes garantizan la ejecución de las tareas en el orden correcto mediante el uso de gráficos de dependencias entre tareas (TDG). Actualmente, los runtimes son lo suficientemente potentes para proporcionar un alto rendimiento con tareas de granularidad gruesa a pesar de que para mantener toda la información que necesitan para hacer su trabajo, introducen un sobrecoste importante en la ejecución de las aplicaciones. El problema viene dado por la tendencia actual en arquitectura de computadores a seguir incluyendo más núcleos y heterogeneidad (de hecho, complejidad) en los sistemas de procesado con lo que el paralelismo de granularidad gruesa no es suficiente para alimentar todos los recursos. En estos entornos complejos las tareas de granularidad fina son preferibles ya que son capaces de exponer un mayor paralelismo de las aplicaciones. Sin embargo, con tareas de granularidad fina, los sobrecostes introducidos por los runtimes software son mayores debido a la necesidad de manejar muchas más tareas más rápido. En general los mayores sobrecostes introducidos por los runtimes son: la administración de los grafos de dependencias que relacionan las tareas y la gestión de las tareas en sistemas heterogéneos. Proponemos una arquitectura hardware, llamada Picos, que consiste en un administrador de dependencias entre tareas incluyendo soporte para tareas anidadas y planificación de tareas heterogéneas. La función principal de dicha arquitectura es acelerar las funciones críticas de los runtimes para modelos de programación basados en tareas. Con Picos, se pretende extender el beneficio de estos modelos de programación para explotar el paralelismo y la heterogeneidad ejecutando tareas de granularidad fina. Como prueba de concepto, tres prototipos de Picos han sido diseñado en VHDL e implementado en una plataforma System-on-chip que consta de varios núcleos ARM integrados junto con una FPGA, y ademas analizados con ejecuciones reales con OmpSs y con Linux. El primer prototipo es un administrador hardware de tareas con dependencias, que se ha implementado en un SoC Xilinx Zynq serie 7000. Está conectado a un procesador ARM Cortex A9 de 2 núcleos, e integrado con el SO. Con 24 núcleos simulados y realizando el análisis real de las dependencias entre tareas en Picos, obtiene hasta un 21x sobre las mismas ejecuciones usando el entorno software. El segundo prototipo, Picos++, amplió Picos incorporando el soporte para la gestión de tareas anidadas en hardware. Hasta donde llega nuestro conocimiento, esta es la primera vez que dicha característica ha sido propuesta y/o incorporada en un administrador hardware de dependencias entre tareas. El segundo prototipo está completamente integrado en el sistema, no solo en hardware, sino también con el modelo de programación paralelo y con el sistema operativo. El tercer prototipo, incluye un administrador y planificador de tareas heterogéneas. El planificador de tareas heterogéneas recibe dichas tareas listas del administrador de dependencias entre tareas y las programa en la unidad de ejecución de hardware adecuada que tenga el tiempo de finalización estimado más corto. Este prototipo se ha implementado en un chip MPSoC Xilinx Zynq Ultrascale+. En dicho sistema con cuatro núcleos ARM y hasta 15 aceleradores HW funcionales, logra una aceleración de hasta 16.2x, y ahorra hasta el 90% de la energía con respecto al software.Postprint (published version

Proceedings of the Second Infrared Detector Technology Workshop

The workshop focused on infrared detector, detector array, and cryogenic electronic technologies relevant to low-background space astronomy. Papers are organized into the following categories: discrete infrared detectors and readout electronics; advanced bolometers; intrinsic integrated infrared arrays; and extrinsic integrated infrared arrays. Status reports on the Space Infrared Telescope Facility (SIRTF) and Infrared Space Observatory (ISO) programs are also included

Hardware runtime management for task-based programming models

Task-based programming models allow programmers to express applications as a collection of tasks with dependences. They are simple to use and greatly improve programmability by using software runtimes to exploit task parallelism and heterogeneity over multi-core, many-core and heterogeneous platforms. In these programming models, the runtimes guarantee correct execution order by managing tasks using task-dependence graphs (TDGs). These runtimes are powerful enough to provide high performance with coarse-grained tasks although they impose overheads on the application execution to maintain all the information they need to do their work. However, as the current trend in processor architectures keeps including more cores and heterogeneity (in fact complexity) in the systems, coarse-grained parallelism is not enough to feed all the underlying resources. Instead, fine-grained tasks are preferable as they are able to expose higher parallelism in applications but the overheads introduced by the software runtimes under these conditions prevent an efficient exploitation of fine-grained parallelism. The two most critical runtime overheads are task dependence graph management and task scheduling to heterogeneous systems. We propose a hardware architecture Picos, consisting of a hardware task dependence manager including nested task support, and a heterogeneous task scheduler, to accelerate the critical runtime functions for task-based programming models. With Picos, we aim at extending the benefit of these programming models into exploiting fine-grained task parallelism and heterogeneity. As a proof-of-concept, Three prototypes of Picos have been designed in VHDL and implemented in a System-on-chip platform consisting of regular ARM SMP cores and an integrated FPGA. They also have been analyzed with real benchmarks with OmpSs running and Linux on the platform. The first prototype is a hardware task dependence manager, which has been implemented in a Xilinx Zynq 7000 series SoCs. It is connected to a 2-core ARM Cortex A9 processor, with bare-metal OS integration. With 24 simulated workers, and running real task-dependence analysis in Picos, it scales up to 21x speedup. The second prototype Picos++ extended Picos with an exciting new feature for nested task support in hardware. To the best of our knowledge, this is the first time that such a feature has been support fully in hardware task dependence managers. This prototype is fully integrated in not only hardware, but also with a State-of-the-Art parallel programming model, and with Linux. The third prototype includes both a hardware task dependence manager and a heterogeneous task scheduler. The heterogeneous task scheduler receives ready tasks from the task-dependence manager and then schedule them to hardware execution units that have the estimated earliest finish time. It is implemented in a Xilinx Zynq Ultrascale+ MPSoC chip. In a system with 4 threads and up to 15 HW accelerators, it achieves up to 16.2x speedup for real benchmarks, and saves up to 90% of energy.Los modelos de programación basados en tareas permiten a los programadores expresar las aplicaciones como una colección de tareas con dependencias entre ellas. Dichos modelos son simples de usar y mejoran enormemente la programabilidad. Para ello se valen del uso de una runtime que en tiempo de ejecución ayuda a explotar el paralelismo de las tareas cuando se ejecutan en plataformas multi-cores, many-cores y heterogéneas. En estos modelos de programación los runtimes garantizan la ejecución de las tareas en el orden correcto mediante el uso de gráficos de dependencias entre tareas (TDG). Actualmente, los runtimes son lo suficientemente potentes para proporcionar un alto rendimiento con tareas de granularidad gruesa a pesar de que para mantener toda la información que necesitan para hacer su trabajo, introducen un sobrecoste importante en la ejecución de las aplicaciones. El problema viene dado por la tendencia actual en arquitectura de computadores a seguir incluyendo más núcleos y heterogeneidad (de hecho, complejidad) en los sistemas de procesado con lo que el paralelismo de granularidad gruesa no es suficiente para alimentar todos los recursos. En estos entornos complejos las tareas de granularidad fina son preferibles ya que son capaces de exponer un mayor paralelismo de las aplicaciones. Sin embargo, con tareas de granularidad fina, los sobrecostes introducidos por los runtimes software son mayores debido a la necesidad de manejar muchas más tareas más rápido. En general los mayores sobrecostes introducidos por los runtimes son: la administración de los grafos de dependencias que relacionan las tareas y la gestión de las tareas en sistemas heterogéneos. Proponemos una arquitectura hardware, llamada Picos, que consiste en un administrador de dependencias entre tareas incluyendo soporte para tareas anidadas y planificación de tareas heterogéneas. La función principal de dicha arquitectura es acelerar las funciones críticas de los runtimes para modelos de programación basados en tareas. Con Picos, se pretende extender el beneficio de estos modelos de programación para explotar el paralelismo y la heterogeneidad ejecutando tareas de granularidad fina. Como prueba de concepto, tres prototipos de Picos han sido diseñado en VHDL e implementado en una plataforma System-on-chip que consta de varios núcleos ARM integrados junto con una FPGA, y ademas analizados con ejecuciones reales con OmpSs y con Linux. El primer prototipo es un administrador hardware de tareas con dependencias, que se ha implementado en un SoC Xilinx Zynq serie 7000. Está conectado a un procesador ARM Cortex A9 de 2 núcleos, e integrado con el SO. Con 24 núcleos simulados y realizando el análisis real de las dependencias entre tareas en Picos, obtiene hasta un 21x sobre las mismas ejecuciones usando el entorno software. El segundo prototipo, Picos++, amplió Picos incorporando el soporte para la gestión de tareas anidadas en hardware. Hasta donde llega nuestro conocimiento, esta es la primera vez que dicha característica ha sido propuesta y/o incorporada en un administrador hardware de dependencias entre tareas. El segundo prototipo está completamente integrado en el sistema, no solo en hardware, sino también con el modelo de programación paralelo y con el sistema operativo. El tercer prototipo, incluye un administrador y planificador de tareas heterogéneas. El planificador de tareas heterogéneas recibe dichas tareas listas del administrador de dependencias entre tareas y las programa en la unidad de ejecución de hardware adecuada que tenga el tiempo de finalización estimado más corto. Este prototipo se ha implementado en un chip MPSoC Xilinx Zynq Ultrascale+. En dicho sistema con cuatro núcleos ARM y hasta 15 aceleradores HW funcionales, logra una aceleración de hasta 16.2x, y ahorra hasta el 90% de la energía con respecto al software

Food Additive

A food additive is defined as a substance not normally consumed as a food in itself and not normally used as a characteristic ingredient of food whether or not it has nutritive value. Food additives are natural or manufactured substances, which are added to food to restore colors lost during processing. They provide sweetness, prevent deterioration during storage and guard against food poisoning (preservatives). This book provides a review of traditional and non-traditional food preservation approaches and ingredients used as food additives. It also provides detailed knowledge for the evaluation of the agro-industrial wastes based on their great potential for the production of industrially relevant food additives. Furthermore the assessment of potential reproductive and developmental toxicity perspectives of some newly synthesized food additives on market has been covered. Finally, the identification of the areas relevant for future research has been pointed out indicating that there is more and more information needed to explore the possibility of the implementation of some other materials to be used as food additives

New science exploration from XFEL: a new paradigm for structural visualisation of macromolecules

X-rays have a long-standing history as an investigative probe in the sciences, and in particular their application to the biological and biomedical sciences has provided an enormous contribution to these fields. Indeed structural biology, the study of the molecules of life at an atomic scale via macromolecular crystallography, has been a major benefactor of advances in x-ray radiation sources. Currently two major bottlenecks exist within this field, the need for well diffracting crystals and radiation damage limitations. The advent of fourth generation x-ray sources, X-ray Free-electron Lasers (XFEL) heralds a shift in the way such experiments are performed. XFELs, due to their high brilliance and ultra short (fs) pulses, hope to decouple radiation dose limitations from spatial resolution by outrunning this radiation damage in short exposures, ‘diffraction before destruction’. This thesis is concerned with exploring experimental methodologies made possible by XFELs, including establishing the experimental infrastructure required at the worlds second XFEL, SACLA, and performing initial experiments. Firstly the potential of performing gas-phase small angle x-ray scattering experiments (gSAXS) is investigated. The current need for gas-phase structural information will be presented and the experimental parameters and projected signal requirements will then be explored. The results of experiments at a synchrotron radiation source with various biomolecules will be presented. It is shown that with the current experimental set-up experiments are fundamentally limited by the signal to noise ratio (SNR) pointing to the necessity of XFEL. Secondly the application of coherent diffractive imaging (CDI) to biological systems at synchrotron and XFEL sources is explored, and the development of experimental systems at both sources is outlined. A method for combining complimentary scattering experiments at both sources is demonstrated and the results of its application to the assembly mechanism of the self-assembling, non-crystalline, macromolecule, the RNAi microsponge, are presented. The microsponge is found to have a nucleating origin leading to a core-shell like nanostructure in the fully formed molecule