Energy harvesting system design and optimization for wireless sensor networks

Wireless sensor networks (WSN) are becoming widely adopted for many applications including complicated tasks like building energy management. However, one major concern for WSN technologies is the short lifetime and high maintenance cost due to the limited battery energy. One of the solutions is to scavenge ambient energy, which is then rectified to power the WSN. The objective of this thesis was to investigate the feasibility of an ultra-low energy consumption power management system suitable for harvesting sub-mW photovoltaic and thermoelectric energy to power WSNs. To achieve this goal, energy harvesting system architectures have been analyzed. Detailed analysis of energy storage units (ESU) have led to an innovative ESU solution for the target applications. Battery-less, long-lifetime ESU and its associated power management circuitry, including fast-charge circuit, self-start circuit, output voltage regulation circuit and hybrid ESU, using a combination of super-capacitor and thin film battery, were developed to achieve continuous operation of energy harvester. Low start-up voltage DC/DC converters have been developed for 1mW level thermoelectric energy harvesting. The novel method of altering thermoelectric generator (TEG) configuration in order to match impedance has been verified in this work. Novel maximum power point tracking (MPPT) circuits, exploring the fractional open circuit voltage method, were particularly developed to suit the sub-1mW photovoltaic energy harvesting applications. The MPPT energy model has been developed and verified against both SPICE simulation and implemented prototypes. Both indoor light and thermoelectric energy harvesting methods proposed in this thesis have been implemented into prototype devices. The improved indoor light energy harvester prototype demonstrates 81% MPPT conversion efficiency with 0.5mW input power. This important improvement makes light energy harvesting from small energy sources (i.e. credit card size solar panel in 500lux indoor lighting conditions) a feasible approach. The 50mm × 54mm thermoelectric energy harvester prototype generates 0.95mW when placed on a 60oC heat source with 28% conversion efficiency. Both prototypes can be used to continuously power WSN for building energy management applications in typical office building environment. In addition to the hardware development, a comprehensive system energy model has been developed. This system energy model not only can be used to predict the available and consumed energy based on real-world ambient conditions, but also can be employed to optimize the system design and configuration. This energy model has been verified by indoor photovoltaic energy harvesting system prototypes in long-term deployed experiments.

Voltage properties of optically injected long wavelength VCSELs: Theory and experiment

Future high speed communications networks will transmit data predominantly over optical fibres. As consumer and enterprise computing will remain the domain of electronics, the electro-optical conversion will get pushed further downstream towards the end user. Consequently, efficient tools are needed for this conversion and due to many potential advantages, including low cost and high output powers, long wavelength Vertical Cavity Surface Emitting Lasers (VCSELs) are a viable option. Drawbacks, such as broader linewidths than competing options, can be mitigated through the use of additional techniques such as Optical Injection Locking (OIL) which can require significant expertise and expensive equipment. This thesis addresses these issues by removing some of the experimental barriers to achieving performance increases via remote OIL. Firstly, numerical simulations of the phase and the photon and carrier numbers of an OIL semiconductor laser allowed the classification of the stable locking phase limits into three distinct groups. The frequency detuning of constant phase values (ø) was considered, in particular ø = 0 where the modulation response parameters were shown to be independent of the linewidth enhancement factor, α. A new method to estimate α and the coupling rate in a single experiment was formulated. Secondly, a novel technique to remotely determine the locked state of a VCSEL based on voltage variations of 2mV−30mV during detuned injection has been developed which can identify oscillatory and locked states. 2D & 3D maps of voltage, optical and electrical spectra illustrate corresponding behaviours. Finally, the use of directly modulated VCSELs as light sources for passive optical networks was investigated by successful transmission of data at 10 Gbit/s over 40km of single mode fibre (SMF) using cost effective electronic dispersion compensation to mitigate errors due to wavelength chirp. A widely tuneable MEMS-VCSEL was established as a good candidate for an externally modulated colourless source after a record error free transmission at 10 Gbit/s over 50km of SMF across a 30nm single mode tuning range. The ability to remotely set the emission wavelength using the novel methods developed in this thesis was demonstrated.

The effectiveness of using patient-reported outcome measures as quality improvement tools

Aim: To investigate the value of using PROMs as quality improvement tools. Methods: Two systematic reviews were undertaken. The first reviewed the quantitative literature on the impact of PROMs feedback and the second reviewed the qualitative literature on the use of PROMs in practice. These reviews informed the focus of the primary research. A cluster randomised controlled trial (PROFILE) examined the impact of providing peer benchmarked PROMs feedback to consultant orthopaedic surgeons on improving outcomes for hip replacement surgery. Qualitative interviews with surgeons in the intervention arm of the trial examined the view of and reactions to the feedback. Results: The quantitative review of 17 studies found weak evidence to suggest that providing PROMs feedback to professionals improves patient outcomes. The qualitative review of 16 studies identified the barriers and facilitators to the use of PROMs based on four themes: practical considerations, attitudes towards the data, methodological concerns and the impact of feedback on care. The PROFILE trial included 11 surgeons and 215 patients in the intervention arm, and 10 surgeons and 217 patients in the control arm. The trial found no significant difference in the Oxford Hip Score between the arms (-0.7, 95% CI -1.9-0.5, p=0.2). Interviews with surgeons revealed mixed opinions about the value of the PROMs feedback and the information did not promote explicit changes to their practice. Conclusion: It is important to use PROMs which have been validated for the specific purpose of performance measurement, consult with professionals when developing a PROMs feedback intervention, communicate with professionals about the objectives of the data collection, educate professionals on the properties and interpretation of the data, and support professionals in using the information to improve care. It is also imperative that the burden of data collection and dissemination of the information is minimised.

Exploring alternatives for milk quality improvement and more efficient dairy production in a smallholder farming context – case study: Mantaro Valley (Peru)

Consumer demand is revolutionizing the way products are being produced, distributed and marketed. In relation to the dairy sector in developing countries, aspects of milk quality are receiving more attention from both society and the government. However, milk quality management needs to be better addressed in dairy production systems to guarantee the access of stakeholders, mainly small-holders, into dairy markets. The present study is focused on an analysis of the interaction of the upstream part of the dairy supply chain (farmers and dairies) in the Mantaro Valley (Peruvian central Andes), in order to understand possible constraints both stakeholders face implementing milk quality controls and practices; and evaluate “ex-ante” how different strategies suggested to improve milk quality could affect farmers and processors’ profits. The analysis is based on three complementary field studies conducted between 2012 and 2013. Our work has shown that the presence of a dual supply chain combining both formal and informal markets has a direct impact on dairy production at the technical and organizational levels, affecting small formal dairy processors’ possibilities to implement contracts, including agreements on milk quality standards. The analysis of milk quality management from farms to dairy plants highlighted the poor hygiene in the study area, even when average values of milk composition were usually high. Some husbandry practices evaluated at farm level demonstrated cost effectiveness and a big impact on hygienic quality; however, regular application of these practices was limited, since small-scale farmers do not receive a bonus for producing hygienic milk. On the basis of these two results, we co-designed with formal small-scale dairy processors a simulation tool to show prospective scenarios, in which they could select their best product portfolio but also design milk payment systems to reward farmers’ with high milk quality performances. This type of approach allowed dairy processors to realize the importance of including milk quality management in their collection and manufacturing processes, especially in a context of high competition for milk supply. We concluded that the improvement of milk quality in a smallholder farming context requires a more coordinated effort among stakeholders. Successful implementation of strategies will depend on the willingness of small-scale dairy processors to reward farmers producing high milk quality; but also on the support from the State to provide incentives to the stakeholders in the formal sector.

Formation and characterisation of ordered porous vanadium oxide inverse opal materials for Li-ion batteries

This thesis presents several routes towards achieving artificial opal templates by colloidal self-assembly of polystyrene (PS) or poly(methyl methacrylate) (PMMA) spheres and the use of these template for the fabrication of V2O5 inverse opals as cathode materials for lithium ion battery applications. First, through the manipulation of different experimental factors, several methods of affecting or directing opal growth towards realizing different structures, improving order and/or achieving faster formation on a variety of substrates are presented. The addition of the surfactant sodium dodecyl sulphate (SDS) at a concentration above the critical micelle concentration for SDS to a 5 wt% solution of PMMA spheres before dip-coating is presented as a method of achieving ordered 2D PhC monolayers on hydrophobic Au-coated silicon substrates at fast and slow rates of withdrawal. The effect that the degree of hydrophilicity of glass substrates has on the ordering of PMMA spheres is next investigated for a slow rate of withdrawal under noise agitation. Heating of the colloidal solution is also presented as a means of affecting order and thickness of opal deposits formed using fast rate dip coating. E-beam patterned substrates are shown as a means of altering the thermodynamically favoured FCC ordering of polystyrene spheres (PS) when dip coated at slow rate. Facile routes toward the synthesis of ordered V2O5 inverse opals are presented with direct infiltration of polymer sphere templates using liquid precursor. The use of different opal templates, both 2D and 3D partially ordered templates, is compared and the composition and arrangement of the subsequent IO structures post infiltration and calcination for various procedures is characterised. V2O5 IOs are also synthesised by electrodeposition from an aqueous VOSO4 solution at constant voltage. Electrochemical characterisation of these structures as cathode material for Li-ion batteries is assessed in a half cell arrangement for samples deposited on stainless steel foil substrates. Improved rate capabilities are demonstrated for these materials over bulk V2O5, with the improvement attributed to the shorter Li ion diffusion distances and increased electrolyte infiltration provided by the IO structure.

The role of structure in the electrochemical performance of nanostructured metal oxides for lithium ion battery anodes

The Li-ion battery has for a number of years been a key factor that has enabled an ever increasing number of modern consumer devices, while in recent years has also been sought to power a range of emerging electric and hybrid electric vehicles. Due to their importance and popularity, a number of characteristics of Li-ion batteries have been subjected to intense work aimed at radical improvement. Although electrode material selection intrinsically defines characteristics like maximum capacity or voltage, engineering of the electrode structure may yield significant improvements to the lifetime performance of the battery, which would not be available if the material was used in its bulk form. The body of work presented in this thesis describes the relationship between the structure of electrochemically active materials and the course of the electrochemical processes occurring within the electrode. Chapter one describes the motivation behind the research presented herein. Chapter two serves to highlight a number of key advancements which have been made and detailed in the literature over recent years, pertaining to the use of nanostructured materials in Li-ion technology. Chapter three details methods and techniques applied in developing the body of work presented in this thesis. Chapter four details structural, molecular and electrochemical characteristics of tin oxide nanoparticle based electrodes, with particular emphasis on the relationship between the size distribution and the electrode performance. Chapter five presents findings of structural, electrochemical and optical study of indium oxide nanoparticles grown on silicon by molecular beam epitaxy. In chapter 6, tin oxide inverted opal electrodes are investigated for the conduct of the electrochemical performance of the electrodes under varying rate of change of potential. Chapter 7 presents the overall conclusions drawn from the results presented in this thesis, coupled with an indication of potential future work which may be explored further.

Establishing a regional, multisite database for quality improvement and service planning in community-based palliative care and hospice.

BACKGROUND: Outpatient palliative care, an evolving delivery model, seeks to improve continuity of care across settings and to increase access to services in hospice and palliative medicine (HPM). It can provide a critical bridge between inpatient palliative care and hospice, filling the gap in community-based supportive care for patients with advanced life-limiting illness. Low capacities for data collection and quantitative research in HPM have impeded assessment of the impact of outpatient palliative care. APPROACH: In North Carolina, a regional database for community-based palliative care has been created through a unique partnership between a HPM organization and academic medical center. This database flexibly uses information technology to collect patient data, entered at the point of care (e.g., home, inpatient hospice, assisted living facility, nursing home). HPM physicians and nurse practitioners collect data; data are transferred to an academic site that assists with analyses and data management. Reports to community-based sites, based on data they provide, create a better understanding of local care quality. CURRENT STATUS: The data system was developed and implemented over a 2-year period, starting with one community-based HPM site and expanding to four. Data collection methods were collaboratively created and refined. The database continues to grow. Analyses presented herein examine data from one site and encompass 2572 visits from 970 new patients, characterizing the population, symptom profiles, and change in symptoms after intervention. CONCLUSION: A collaborative regional approach to HPM data can support evaluation and improvement of palliative care quality at the local, aggregated, and statewide levels.

Traumatic brain injury exacerbates neurodegenerative pathology: improvement with an apolipoprotein E-based therapeutic.

Cognitive impairment is common following traumatic brain injury (TBI), and neuroinflammatory mechanisms may predispose to the development of neurodegenerative disease. Apolipoprotein E (apoE) polymorphisms modify neuroinflammatory responses, and influence both outcome from acute brain injury and the risk of developing neurodegenerative disease. We demonstrate that TBI accelerates neurodegenerative pathology in double-transgenic animals expressing the common human apoE alleles and mutated amyloid precursor protein, and that pathology is exacerbated in the presence of the apoE4 allele. The administration of an apoE-mimetic peptide markedly reduced the development of neurodegenerative pathology in mice homozygous for apoE3 as well as apoE3/E4 heterozygotes. These results demonstrate that TBI accelerates the cardinal neuropathological features of neurodegenerative disease, and establishes the potential for apoE mimetic therapies in reducing pathology associated with neurodegeneration.

A randomized clinical trial of a coping improvement group intervention for HIV-infected older adults.

This research tested if a 12-session coping improvement group intervention (n = 104) reduced depressive symptoms in HIV-infected older adults compared to an interpersonal support group intervention (n = 105) and an individual therapy upon request (ITUR) control condition (n = 86). Participants were 295 HIV-infected men and women 50-plus years of age living in New York City, Cincinnati, OH, and Columbus, OH. Using A-CASI assessment methodology, participants provided data on their depressive symptoms using the Geriatric Depression Screening Scale (GDS) at pre-intervention, post-intervention, and 4- and 8-month follow-up. Whether conducted with all participants (N = 295) or only a subset of participants diagnosed with mild, moderate, or severe depressive symptoms (N = 171), mixed models analyses of repeated measures found that both coping improvement and interpersonal support group intervention participants reported fewer depressive symptoms than ITUR controls at post-intervention, 4-month follow-up, and 8-month follow-up. The effect sizes of the differences between the two active interventions and the control group were greater when outcome analyses were limited to those participants with mild, moderate, or severe depressive symptoms. At no assessment period did coping improvement and interpersonal support group intervention participants differ in depressive symptoms.

An evaluation of remifentanil-sevoflurane response surface models in patients emerging from anesthesia: model improvement using effect-site sevoflurane concentrations.

INTRODUCTION: We previously reported models that characterized the synergistic interaction between remifentanil and sevoflurane in blunting responses to verbal and painful stimuli. This preliminary study evaluated the ability of these models to predict a return of responsiveness during emergence from anesthesia and a response to tibial pressure when patients required analgesics in the recovery room. We hypothesized that model predictions would be consistent with observed responses. We also hypothesized that under non-steady-state conditions, accounting for the lag time between sevoflurane effect-site concentration (Ce) and end-tidal (ET) concentration would improve predictions. METHODS: Twenty patients received a sevoflurane, remifentanil, and fentanyl anesthetic. Two model predictions of responsiveness were recorded at emergence: an ET-based and a Ce-based prediction. Similarly, 2 predictions of a response to noxious stimuli were recorded when patients first required analgesics in the recovery room. Model predictions were compared with observations with graphical and temporal analyses. RESULTS: While patients were anesthetized, model predictions indicated a high likelihood that patients would be unresponsive (> or = 99%). However, after termination of the anesthetic, models exhibited a wide range of predictions at emergence (1%-97%). Although wide, the Ce-based predictions of responsiveness were better distributed over a percentage ranking of observations than the ET-based predictions. For the ET-based model, 45% of the patients awoke within 2 min of the 50% model predicted probability of unresponsiveness and 65% awoke within 4 min. For the Ce-based model, 45% of the patients awoke within 1 min of the 50% model predicted probability of unresponsiveness and 85% awoke within 3.2 min. Predictions of a response to a painful stimulus in the recovery room were similar for the Ce- and ET-based models. DISCUSSION: Results confirmed, in part, our study hypothesis; accounting for the lag time between Ce and ET sevoflurane concentrations improved model predictions of responsiveness but had no effect on predicting a response to a noxious stimulus in the recovery room. These models may be useful in predicting events of clinical interest but large-scale evaluations with numerous patients are needed to better characterize model performance.

The evolving capabilities of rhodopsin-based genetically encoded voltage indicators.

Protein engineering over the past four years has made rhodopsin-based genetically encoded voltage indicators a leading candidate to achieve the task of reporting action potentials from a population of genetically targeted neurons in vivo. Rational design and large-scale screening efforts have steadily improved the dynamic range and kinetics of the rhodopsin voltage-sensing domain, and coupling these rhodopsins to bright fluorescent proteins has supported bright fluorescence readout of the large and rapid rhodopsin voltage response. The rhodopsin-fluorescent protein fusions have the highest achieved signal-to-noise ratios for detecting action potentials in neuronal cultures to date, and have successfully reported single spike events in vivo. Given the rapid pace of current development, the genetically encoded voltage indicator class is nearing the goal of robust spike imaging during live-animal behavioral experiments.

Signal Improvement and Contrast Enhancement in Magnetic Resonance Imaging

This thesis reports advances in magnetic resonance imaging (MRI), with the ultimate goal of improving signal and contrast in biomedical applications. More specifically, novel MRI pulse sequences have been designed to characterize microstructure, enhance signal and contrast in tissue, and image functional processes. In this thesis, rat brain and red bone marrow images are acquired using iMQCs (intermolecular multiple quantum coherences) between spins that are 10 μm to 500 μm apart. As an important application, iMQCs images in different directions can be used for anisotropy mapping. We investigate tissue microstructure by analyzing anisotropy mapping. At the same time, we simulated images expected from rat brain without microstructure. We compare those with experimental results to prove that the dipolar field from the overall shape only has small contributions to the experimental iMQC signal. Besides magnitude of iMQCs, phase of iMQCs should be studied as well. The phase anisotropy maps built by our method can clearly show susceptibility information in kidneys. It may provide meaningful diagnostic information. To deeply study susceptibility, the modified-crazed sequence is developed. Combining phase data of modified-crazed images and phase data of iMQCs images is very promising to construct microstructure maps. Obviously, the phase image in all above techniques needs to be highly-contrasted and clear. To achieve the goal, algorithm tools from Susceptibility-Weighted Imaging (SWI) and Susceptibility Tensor Imaging (STI) stands out superb useful and creative in our system.

Improvement in visual search with practice: mapping learning-related changes in neurocognitive stages of processing.

Practice can improve performance on visual search tasks; the neural mechanisms underlying such improvements, however, are not clear. Response time typically shortens with practice, but which components of the stimulus-response processing chain facilitate this behavioral change? Improved search performance could result from enhancements in various cognitive processing stages, including (1) sensory processing, (2) attentional allocation, (3) target discrimination, (4) motor-response preparation, and/or (5) response execution. We measured event-related potentials (ERPs) as human participants completed a five-day visual-search protocol in which they reported the orientation of a color popout target within an array of ellipses. We assessed changes in behavioral performance and in ERP components associated with various stages of processing. After practice, response time decreased in all participants (while accuracy remained consistent), and electrophysiological measures revealed modulation of several ERP components. First, amplitudes of the early sensory-evoked N1 component at 150 ms increased bilaterally, indicating enhanced visual sensory processing of the array. Second, the negative-polarity posterior-contralateral component (N2pc, 170-250 ms) was earlier and larger, demonstrating enhanced attentional orienting. Third, the amplitude of the sustained posterior contralateral negativity component (SPCN, 300-400 ms) decreased, indicating facilitated target discrimination. Finally, faster motor-response preparation and execution were observed after practice, as indicated by latency changes in both the stimulus-locked and response-locked lateralized readiness potentials (LRPs). These electrophysiological results delineate the functional plasticity in key mechanisms underlying visual search with high temporal resolution and illustrate how practice influences various cognitive and neural processing stages leading to enhanced behavioral performance.

A whole-cell and single-channel study of the voltage-dependent outward potassium current in avian hepatocytes.

Voltage-dependent membrane currents were studied in dissociated hepatocytes from chick, using the patch-clamp technique. All cells had voltage-dependent outward K+ currents; in 10% of the cells, a fast, transient, tetrodotoxin-sensitive Na+ current was identified. None of the cells had voltage-dependent inward Ca2+ currents. The K+ current activated at a membrane potential of about -10 mV, had a sigmoidal time course, and did not inactivate in 500 ms. The maximum outward conductance was 6.6 +/- 2.4 nS in 18 cells. The reversal potential, estimated from tail current measurements, shifted by 50 mV per 10-fold increase in the external K+ concentration. The current traces were fitted by n2 kinetics with voltage-dependent time constants. Omitting Ca2+ from the external bath or buffering the internal Ca2+ with EGTA did not alter the outward current, which shows that Ca2+-activated K+ currents were not present. 1-5 mM 4-aminopyridine, 0.5-2 mM BaCl2, and 0.1-1 mM CdCl2 reversibly inhibited the current. The block caused by Ba was voltage dependent. Single-channel currents were recorded in cell-attached and outside-out patches. The mean unitary conductance was 7 pS, and the channels displayed bursting kinetics. Thus, avian hepatocytes have a single type of K+ channel belonging to the delayed rectifier class of K+ channels.

Computational Methods for RNA Structure Validation and Improvement.

With increasing recognition of the roles RNA molecules and RNA/protein complexes play in an unexpected variety of biological processes, understanding of RNA structure-function relationships is of high current importance. To make clean biological interpretations from three-dimensional structures, it is imperative to have high-quality, accurate RNA crystal structures available, and the community has thoroughly embraced that goal. However, due to the many degrees of freedom inherent in RNA structure (especially for the backbone), it is a significant challenge to succeed in building accurate experimental models for RNA structures. This chapter describes the tools and techniques our research group and our collaborators have developed over the years to help RNA structural biologists both evaluate and achieve better accuracy. Expert analysis of large, high-resolution, quality-conscious RNA datasets provides the fundamental information that enables automated methods for robust and efficient error diagnosis in validating RNA structures at all resolutions. The even more crucial goal of correcting the diagnosed outliers has steadily developed toward highly effective, computationally based techniques. Automation enables solving complex issues in large RNA structures, but cannot circumvent the need for thoughtful examination of local details, and so we also provide some guidance for interpreting and acting on the results of current structure validation for RNA.