From inverted pendulum to N-link chain: inertial sensors-based assessment of movement kinematics and dynamics for functional evaluation and rehabilitation

Despite several clinical tests that have been developed to qualitatively describe complex motor tasks by functional testing, these methods often depend on clinicians' interpretation, experience and training, which make the assessment results inconsistent, without the precision required to objectively assess the effect of the rehabilitative intervention. A more detailed characterization is required to fully capture the various aspects of motor control and performance during complex movements of lower and upper limbs. The need for cost-effective and clinically applicable instrumented tests would enable quantitative assessment of performance on a subject-specific basis, overcoming the limitations due to the lack of objectiveness related to individual judgment, and possibly disclosing subtle alterations that are not clearly visible to the observer. Postural motion measurements at additional locations, such as lower and upper limbs and trunk, may be necessary in order to obtain information about the inter-segmental coordination during different functional tests involved in clinical practice. With these considerations in mind, this Thesis aims: i) to suggest a novel quantitative assessment tool for the kinematics and dynamics evaluation of a multi-link kinematic chain during several functional motor tasks (i.e. squat, sit-to-stand, postural sway), using one single-axis accelerometer per segment, ii) to present a novel quantitative technique for the upper limb joint kinematics estimation, considering a 3-link kinematic chain during the Fugl-Meyer Motor Assessment and using one inertial measurement unit per segment. The suggested methods could have several positive feedbacks from clinical practice. The use of objective biomechanical measurements, provided by inertial sensor-based technique, may help clinicians to: i) objectively track changes in motor ability, ii) provide timely feedback about the effectiveness of administered rehabilitation interventions, iii) enable intervention strategies to be modified or changed if found to be ineffective, and iv) speed up the experimental sessions when several subjects are asked to perform different functional tests.

Use of shared memory in the context of embedded multi-core processors: exploration of the technology and its limits

Modern embedded systems embrace many-core shared-memory designs. Due to constrained power and area budgets, most of them feature software-managed scratchpad memories instead of data caches to increase the data locality. It is therefore programmers’ responsibility to explicitly manage the memory transfers, and this make programming these platform cumbersome. Moreover, complex modern applications must be adequately parallelized before they can the parallel potential of the platform into actual performance. To support this, programming languages were proposed, which work at a high level of abstraction, and rely on a runtime whose cost hinders performance, especially in embedded systems, where resources and power budget are constrained. This dissertation explores the applicability of the shared-memory paradigm on modern many-core systems, focusing on the ease-of-programming. It focuses on OpenMP, the de-facto standard for shared memory programming. In a first part, the cost of algorithms for synchronization and data partitioning are analyzed, and they are adapted to modern embedded many-cores. Then, the original design of an OpenMP runtime library is presented, which supports complex forms of parallelism such as multi-level and irregular parallelism. In the second part of the thesis, the focus is on heterogeneous systems, where hardware accelerators are coupled to (many-)cores to implement key functional kernels with orders-of-magnitude of speedup and energy efficiency compared to the “pure software” version. However, three main issues rise, namely i) platform design complexity, ii) architectural scalability and iii) programmability. To tackle them, a template for a generic hardware processing unit (HWPU) is proposed, which share the memory banks with cores, and the template for a scalable architecture is shown, which integrates them through the shared-memory system. Then, a full software stack and toolchain are developed to support platform design and to let programmers exploiting the accelerators of the platform. The OpenMP frontend is extended to interact with it.

Electrical spectroscopy of rubrene bulk and thin film crystals

One of the most diffused electronic device is the field effect transistor (FET), contained in number of billions in each electronic device. Organic optoelectronics is an emerging field that exploits the unique properties of conjugated organic materials to develop new applications that require a combination of performance, low cost and processability. Organic single crystals are the material with best performances and purity among the variety of different form of organic semiconductors. This thesis is focused on electrical and optical characterization of Rubrene single crystal bulk and thin films. Rubrene bulk is well known but for the first time we studied thin films. The first Current-voltage characterization has been performed for the first time on three Rubrene thin films with three different thickness to extract the charge carriers mobility and to assess its crystalline structure. As results we see that mobility increase with thickness. Field effect transistor based on Rubrene thin films on $SiO_2$ have been characterize by current-voltage (I-V) analyses (at several temperatures) and reveals a hopping conduction. Hopping behavior probably is due to the lattice mismatch with the substrate or intrinsic defectivity of the thin films. To understand effects of contact resistance we tested thin films with the Transmission Line Method (TLM) method. The TLM method revealeds that contact resistance is negligible but evidenced a Schottky behavior in a limited but well determined range of T. To avoid this effect we carried out annealing treatment after the electrode evaporation iswe performed a compete I-V characterization as a function of in temperature to extract the electronic density of states (DOS) distribution through the Space Charge Limited Current (SCLC) method. The results show a DOS with an exponential trenddistribution, as expected. The measured mobility of thin films is about 0.1cm^2/Vs and it increases with the film thickness. Further studies are necessary to investigate the reason and improve performances. From photocurrent spectrum we calculated an Eg of about 2.2eV and both thin films and bulk have a good crystal order. Further measurement are necessary to solve some open problems

Mathematical Optimization Applied to Thermal and Electrical Energy Systems

This Thesis aims at building and discussing mathematical models applications focused on Energy problems, both on the thermal and electrical side. The objective is to show how mathematical programming techniques developed within Operational Research can give useful answers in the Energy Sector, how they can provide tools to support decision making processes of Companies operating in the Energy production and distribution and how they can be successfully used to make simulations and sensitivity analyses to better understand the state of the art and convenience of a particular technology by comparing it with the available alternatives. The first part discusses the fundamental mathematical background followed by a comprehensive literature review about mathematical modelling in the Energy Sector. The second part presents mathematical models for the District Heating strategic network design and incremental network design. The objective is the selection of an optimal set of new users to be connected to an existing thermal network, maximizing revenues, minimizing infrastructure and operational costs and taking into account the main technical requirements of the real world application. Results on real and randomly generated benchmark networks are discussed with particular attention to instances characterized by big networks dimensions. The third part is devoted to the development of linear programming models for optimal battery operation in off-grid solar power schemes, with consideration of battery degradation. The key contribution of this work is the inclusion of battery degradation costs in the optimisation models. As available data on relating degradation costs to the nature of charge/discharge cycles are limited, we concentrate on investigating the sensitivity of operational patterns to the degradation cost structure. The objective is to investigate the combination of battery costs and performance at which such systems become economic. We also investigate how the system design should change when battery degradation is taken into account.

Chemical exfoliation of graphene and its application in organic electronics and energy storage devices

Graphene, the thinnest two-dimensional material possible, is considered as a realistic candidate for the numerous applications in electronic, energy storage and conversion devices due to its unique properties, such as high optical transmittance, high conductivity, excellent chemical and thermal stability. However, the electronic and chemical properties of graphene are highly dependent on their preparation methods. Therefore, the development of novel chemical exfoliation process which aims at high yield synthesis of high quality graphene while maintaining good solution processability is of great concern. This thesis focuses on the solution production of high-quality graphene by wet-chemical exfoliation methods and addresses the applications of the chemically exfoliated graphene in organic electronics and energy storage devices.rnPlatinum is the most commonly used catalysts for fuel cells but they suffered from sluggish electron transfer kinetics. On the other hand, heteroatom doped graphene is known to enhance not only electrical conductivity but also long term operation stability. In this regard, a simple synthetic method is developed for the nitrogen doped graphene (NG) preparation. Moreover, iron (Fe) can be incorporated into the synthetic process. As-prepared NG with and without Fe shows excellent catalytic activity and stability compared to that of Pt based catalysts.rnHigh electrical conductivity is one of the most important requirements for the application of graphene in electronic devices. Therefore, for the fabrication of electrically conductive graphene films, a novel methane plasma assisted reduction of GO is developed. The high electrical conductivity of plasma reduced GO films revealed an excellent electrochemical performance in terms of high power and energy densities when used as an electrode in the micro-supercapacitors.rnAlthough, GO can be prepared in bulk scale, large amount of defect density and low electrical conductivity are major drawbacks. To overcome the intrinsic limitation of poor quality of GO and/or reduced GO, a novel protocol is extablished for mass production of high-quality graphene by means of electrochemical exfoliation of graphite. The prepared graphene shows high electrical conductivity, low defect density and good solution processability. Furthermore, when used as electrodes in organic field-effect transistors and/or in supercapacitors, the electrochemically exfoliated graphene shows excellent device performances. The low cost and environment friendly production of such high-quality graphene is of great importance for future generation electronics and energy storage devices. rn

Development and testing of an asymmetric capacitor with a nickel-carbon foam positive electrode

Electrochemical capacitors (ECs), also known as supercapacitors or ultracapacitors, are energy storage devices with properties between batteries and conventional capacitors. EC have evolved through several generations. The trend in EC is to combine a double-layer electrode with a battery-type electrode in an asymmetric capacitor configuration. The double-layer electrode is usually an activated carbon (AC) since it has high surface area, good conductivity, and relatively low cost. The battery-type electrode usually consists of PbO2 or Ni(OH)2. In this research, a graphitic carbon foam was impregnated with Co-substituted Ni(OH)2 using electrochemical deposition to serve as the positive electrode in the asymmetric capacitor. The purpose was to reduce the cost and weight of the ECs while maintaining or increasing capacitance and gravimetric energy storage density. The XRD result indicated that the nickel-carbon foam electrode was a typical α-Ni(OH)2. The specific capacitance of the nickel-carbon foam electrode was 2641 F/g at 5 mA/cm2, higher than the previously reported value of 2080 F/g for a 7.5% Al-substituted α-Ni(OH)2 electrode. Three different ACs (RP-20, YP-50F, and Ketjenblack EC-600JD) were evaluated through their morphology and electrochemical performance to determine their suitability for use in ECs. The study indicated that YP-50F demonstrated the better overall performance because of the combination of micropore and mesopore structures. Therefore, YP-50F was chosen to combine with the nickel-carbon foam electrode for further evaluation. Six cells with different mass ratios of negative to positive active mass were fabricated to study the electrochemical performance. Among the different mass ratios, the asymmetric capacitor with the mass ratio of 3.71 gave the highest specific energy and specific power, 24.5 W.h/kg and 498 W/kg, respectively.

Managing server energy and reducing operational cost for online service providers

The past decade has seen the energy consumption in servers and Internet Data Centers (IDCs) skyrocket. A recent survey estimated that the worldwide spending on servers and cooling have risen to above $30 billion and is likely to exceed spending on the new server hardware . The rapid rise in energy consumption has posted a serious threat to both energy resources and the environment, which makes green computing not only worthwhile but also necessary. This dissertation intends to tackle the challenges of both reducing the energy consumption of server systems and by reducing the cost for Online Service Providers (OSPs). Two distinct subsystems account for most of IDC’s power: the server system, which accounts for 56% of the total power consumption of an IDC, and the cooling and humidifcation systems, which accounts for about 30% of the total power consumption. The server system dominates the energy consumption of an IDC, and its power draw can vary drastically with data center utilization. In this dissertation, we propose three models to achieve energy effciency in web server clusters: an energy proportional model, an optimal server allocation and frequency adjustment strategy, and a constrained Markov model. The proposed models have combined Dynamic Voltage/Frequency Scaling (DV/FS) and Vary-On, Vary-off (VOVF) mechanisms that work together for more energy savings. Meanwhile, corresponding strategies are proposed to deal with the transition overheads. We further extend server energy management to the IDC’s costs management, helping the OSPs to conserve, manage their own electricity cost, and lower the carbon emissions. We have developed an optimal energy-aware load dispatching strategy that periodically maps more requests to the locations with lower electricity prices. A carbon emission limit is placed, and the volatility of the carbon offset market is also considered. Two energy effcient strategies are applied to the server system and the cooling system respectively. With the rapid development of cloud services, we also carry out research to reduce the server energy in cloud computing environments. In this work, we propose a new live virtual machine (VM) placement scheme that can effectively map VMs to Physical Machines (PMs) with substantial energy savings in a heterogeneous server cluster. A VM/PM mapping probability matrix is constructed, in which each VM request is assigned with a probability running on PMs. The VM/PM mapping probability matrix takes into account resource limitations, VM operation overheads, server reliability as well as energy effciency. The evolution of Internet Data Centers and the increasing demands of web services raise great challenges to improve the energy effciency of IDCs. We also express several potential areas for future research in each chapter.

Estimating greenhouse gas emissions of highway construction and rehabilitation to support pavement life cycle assessment

Highway infrastructure plays a significant role in society. The building and upkeep of America’s highways provide society the necessary means of transportation for goods and services needed to develop as a nation. However, as a result of economic and social development, vast amounts of greenhouse gas emissions (GHG) are emitted into the atmosphere contributing to global climate change. In recognizing this, future policies may mandate the monitoring of GHG emissions from public agencies and private industries in order to reduce the effects of global climate change. To effectively reduce these emissions, there must be methods that agencies can use to quantify the GHG emissions associated with constructing and maintaining the nation’s highway infrastructure. Current methods for assessing the impacts of highway infrastructure include methodologies that look at the economic impacts (costs) of constructing and maintaining highway infrastructure over its life cycle. This is known as Life Cycle Cost Analysis (LCCA). With the recognition of global climate change, transportation agencies and contractors are also investigating the environmental impacts that are associated with highway infrastructure construction and rehabilitation. A common tool in doing so is the use of Life Cycle Assessment (LCA). Traditionally, LCA is used to assess the environmental impacts of products or processes. LCA is an emerging concept in highway infrastructure assessment and is now being implemented and applied to transportation systems. This research focuses on life cycle GHG emissions associated with the construction and rehabilitation of highway infrastructure using a LCA approach. Life cycle phases of the highway section include; the material acquisition and extraction, construction and rehabilitation, and service phases. Departing from traditional approaches that tend to use LCA as a way to compare alternative pavement materials or designs based on estimated inventories, this research proposes a shift to a context sensitive process-based approach that uses actual observed construction and performance data to calculate greenhouse gas emissions associated with highway construction and rehabilitation. The goal is to support strategies that reduce long-term environmental impacts. Ultimately, this thesis outlines techniques that can be used to assess GHG emissions associated with construction and rehabilitation operations to support the overall pavement LCA.

DEVELOPMENT OF AN OPTIMIZATION MODEL FOR BIOFUEL FACILITY SIZE AND LOCATION AND A SIMULATION MODEL FOR DESIGN OF A BIOFUEL SUPPLY CHAIN

A range of societal issues have been caused by fossil fuel consumption in the transportation sector in the United States (U.S.), including health related air pollution, climate change, the dependence on imported oil, and other oil related national security concerns. Biofuels production from various lignocellulosic biomass types such as wood, forest residues, and agriculture residues have the potential to replace a substantial portion of the total fossil fuel consumption. This research focuses on locating biofuel facilities and designing the biofuel supply chain to minimize the overall cost. For this purpose an integrated methodology was proposed by combining the GIS technology with simulation and optimization modeling methods. The GIS based methodology was used as a precursor for selecting biofuel facility locations by employing a series of decision factors. The resulted candidate sites for biofuel production served as inputs for simulation and optimization modeling. As a precursor to simulation or optimization modeling, the GIS-based methodology was used to preselect potential biofuel facility locations for biofuel production from forest biomass. Candidate locations were selected based on a set of evaluation criteria, including: county boundaries, a railroad transportation network, a state/federal road transportation network, water body (rivers, lakes, etc.) dispersion, city and village dispersion, a population census, biomass production, and no co-location with co-fired power plants. The simulation and optimization models were built around key supply activities including biomass harvesting/forwarding, transportation and storage. The built onsite storage served for spring breakup period where road restrictions were in place and truck transportation on certain roads was limited. Both models were evaluated using multiple performance indicators, including cost (consisting of the delivered feedstock cost, and inventory holding cost), energy consumption, and GHG emissions. The impact of energy consumption and GHG emissions were expressed in monetary terms to keep consistent with cost. Compared with the optimization model, the simulation model represents a more dynamic look at a 20-year operation by considering the impacts associated with building inventory at the biorefinery to address the limited availability of biomass feedstock during the spring breakup period. The number of trucks required per day was estimated and the inventory level all year around was tracked. Through the exchange of information across different procedures (harvesting, transportation, and biomass feedstock processing procedures), a smooth flow of biomass from harvesting areas to a biofuel facility was implemented. The optimization model was developed to address issues related to locating multiple biofuel facilities simultaneously. The size of the potential biofuel facility is set up with an upper bound of 50 MGY and a lower bound of 30 MGY. The optimization model is a static, Mathematical Programming Language (MPL)-based application which allows for sensitivity analysis by changing inputs to evaluate different scenarios. It was found that annual biofuel demand and biomass availability impacts the optimal results of biofuel facility locations and sizes.

DEVELOPMENT OF THE ECOCAR 3 PROPOSAL AND GUIDELINES FOR MODELING AND DESIGN IN YEAR ONE OF ECOCAR 3

This report summarizes the work done for the Vehicle Powertrain Modeling and Design Problem Proposal portion of the EcoCAR3 proposal as specified in the Request for Proposal from Argonne National Laboratory. The results of the modeling exercises presented in the proposal showed that: An average conventional vehicle powered by a combustion engine could not meet the energy consumption target when the engine was sized to meet the acceleration target, due the relatively low thermal efficiency of the spark ignition engine. A battery electric vehicle could not meet the required range target of 320 km while keeping the vehicle weight below the gross vehicle weight rating of 2000 kg. This was due to the low energy density of the batteries which necessitated a large, and heavy, battery pack to provide enough energy to meet the range target. A series hybrid electric vehicle has the potential to meet the acceleration and energy consumption parameters when the components are optimally sized. A parallel hybrid electric vehicle has less energy conversion losses than a series hybrid electric vehicle which results in greater overall efficiency, lower energy consumption, and less emissions. For EcoCAR3, Michigan Tech proposes to develop a plug-in parallel hybrid vehicle (PPHEV) powered by a small Diesel engine operating on B20 Bio-Diesel fuel. This architecture was chosen over other options due to its compact design, lower cost, and its ability to provide performance levels and energy efficiency that meet or exceed the design targets. While this powertrain configuration requires a more complex control system and strategy than others, the student engineering team at Michigan Tech has significant recent experience with this architecture and has confidence that it will perform well in the events planned for the EcoCAR3 competition.

The "Quiet Eye" and Motor Performance: Task Demands Matter!

Evidence suggests that superior motor performance coincides with a longer duration of the last fixation before movement initiation, an observation called “quiet eye” (QE). Although the empirical findings over the last two decades underline the robustness of the phenomenon, little is known about its functional role in motor performance. Therefore, a novel paradigm is introduced, testing QE duration as an independent variable by experimentally manipulating the onset of the last fixation before movement unfolding. Furthermore, this paradigm is employed to investigate the functional mechanisms behind the QE phenomenon by manipulating the predictability of the target position and thereby the amount of information to be processed over the QE period. The results further support the assumption that QE affects motor performance, with experimentally prolonged QE durations increasing accuracy in a throwing task. However, it is only under a high information-processing load that a longer QE duration is beneficial for throwing performance. Therefore, the optimization of information processing, particularly in motor execution, turns out to be a promising candidate for explaining QE benefits on a functional level.

A Routing Protocol Based on Energy and Link Quality for Internet of Things Applications

The Internet of Things (IoT) is attracting considerable attention from the universities, industries, citizens and governments for applications, such as healthcare, environmental monitoring and smart buildings. IoT enables network connectivity between smart devices at all times, everywhere, and about everything. In this context, Wireless Sensor Networks (WSNs) play an important role in increasing the ubiquity of networks with smart devices that are low-cost and easy to deploy. However, sensor nodes are restricted in terms of energy, processing and memory. Additionally, low-power radios are very sensitive to noise, interference and multipath distortions. In this context, this article proposes a routing protocol based on Routing by Energy and Link quality (REL) for IoT applications. To increase reliability and energy-efficiency, REL selects routes on the basis of a proposed end-to-end link quality estimator mechanism, residual energy and hop count. Furthermore, REL proposes an event-driven mechanism to provide load balancing and avoid the premature energy depletion of nodes/networks. Performance evaluations were carried out using simulation and testbed experiments to show the impact and benefits of REL in small and large-scale networks. The results show that REL increases the network lifetime and services availability, as well as the quality of service of IoT applications. It also provides an even distribution of scarce network resources and reduces the packet loss rate, compared with the performance of well-known protocols.

Hepatic gene expression involved in glucose and lipid metabolism in transition cows: effects of fat mobilization during early lactation in relation to milk performance and metabolic changes.

Insufficient feed intake during early lactation results in elevated body fat mobilization to meet energy demands for milk production. Hepatic energy metabolism is involved by increasing endogenous glucose production and hepatic glucose output for milk synthesis and by adaptation of postcalving fuel oxidation. Given that cows differ in their degree of fat mobilization around parturition, indicated by variable total liver fat concentration (LFC), the study investigated the influence of peripartum fat mobilization on hepatic gene expression involved in gluconeogenesis, fatty acid oxidation, ketogenesis, and cholesterol synthesis, as well as transcriptional factors referring to energy metabolism. German Holstein cows were grouped according to mean total LFC on d 1, 14, and 28 after parturition as low [<200mg of total fat/g of dry matter (DM); n=10], medium (200-300 mg of total fat/g of DM; n=10), and high (>300 mg of total fat/g of DM; n=7), indicating fat mobilization during early lactation. Cows were fed total mixed rations ad libitum and held under equal conditions. Liver biopsies were taken at d 56 and 15 before and d 1, 14, 28, and 49 after parturition to measure mRNA abundances of pyruvate carboxylase (PC); phosphoenolpyruvate carboxykinase; glucose-6-phosphatase; propionyl-coenzyme A (CoA) carboxylase α; carnitine palmitoyl-transferase 1A (CPT1A); acyl-CoA synthetase, long chain 1 (ASCL1); acyl-CoA dehydrogenase, very long chain; 3-hydroxy-3-methylglutaryl-CoA synthase 1 and 2; sterol regulatory element-binding factor 1; and peroxisome proliferator-activated factor α. Total LFC postpartum differed greatly among cows, and the mRNA abundance of most enzymes and transcription factors changed with time during the experimental period. Abundance of PC mRNA increased at parturition to a greater extent in high- and medium-LFC groups than in the low-LFC group. Significant LFC × time interactions for ACSL1 and CPT1A during the experimental period indicated variable gene expression depending on LFC after parturition. Correlations between hepatic gene expression and performance data and plasma concentrations of metabolites and hormones showed time-specific relations during the transition period. Elevated body fat mobilization during early lactation affected gene expression involved in gluconeogenesis to a greater extent than gene expression involved in lipid metabolism, indicating the dependence of hepatic glucose metabolism on hepatic lipid status and fat mobilization during early lactation.

Too exhausted for Operation? Anxiety, depleted self-control strength, and perceptual-motor performance

We tested the hypothesis that the interaction of self-control strength and state anxiety predicts perceptual–motor performance in a hand–eye coordination task. We predicted a stronger negative relation between anxiety and performance in a perceptual–motor task for participants whose self-control strength had been temporarily depleted compared to participants whose self-control strength was intact. In an experiment (N = 60), we manipulated self-control strength, measured state anxiety after an evaluative instruction, and assessed performance in the board game Operation as an indicator of perceptual–motor performance. The data supported our hypothesis: Only for participants whose self-control strength was temporarily depleted was there a statistically significant negative relation between anxiety and performance. Boosting self-control strength may help to prevent the potentially negative anxiety effects.