Brain Bases of Auditory Processing in Infants: Localization and Statistical Regularities

Honors (Bachelor's)Biopsychology, Cognition, and Neuroscience (BCN)University of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/134715/1/radhisan.pd

Biopsychosocial Data Analytics and Modeling

Sustained customisation of digital health intervention (DHI) programs, in the context of community health engagement, requires strong integration of multi-sourced interdisciplinary biopsychosocial health data. The biopsychosocial model is built upon the idea that biological, psychological and social processes are integrally and interactively involved in physical health and illness. One of the longstanding challenges of dealing with healthcare data is the wide variety of data generated from different sources and the increasing need to learn actionable insights that drive performance improvement. The growth of information and communication technology has led to the increased use of DHI programs. These programs use an observational methodology that helps researchers to study the everyday behaviour of participants during the course of the program by analysing data generated from digital tools such as wearables, online surveys and ecological momentary assessment (EMA). Combined with data reported from biological and psychological tests, this provides rich and unique biopsychosocial data. There is a strong need to review and apply novel approaches to combining biopsychosocial data from a methodological perspective. Although some studies have used data analytics in research on clinical trial data generated from digital interventions, data analytics on biopsychosocial data generated from DHI programs is limited. The study in this thesis develops and implements innovative approaches for analysing the existing unique and rich biopsychosocial data generated from the wellness study, a DHI program conducted by the School of Science, Psychology and Sport at Federation University. The characteristics of variety, value and veracity that usually describe big data are also relevant to the biopsychosocial data handled in this thesis. These historical, retrospective real-life biopsychosocial data provide fertile ground for research through the use of data analytics to discover patterns hidden in the data and to obtain new knowledge. This thesis presents the studies carried out on three aspects of biopsychosocial research. First, we present the salient traits of the three components - biological, psychological and social - of biopsychosocial research. Next, we investigate the challenges of pre-processing biopsychosocial data, placing special emphasis on the time-series data generated from wearable sensor devices. Finally, we present the application of statistical and machine learning (ML) tools to integrate variables from the biopsychosocial disciplines to build a predictive model. The first chapter presents the salient features of the biopsychosocial data for each discipline. The second chapter presents the challenges of pre-processing biopsychosocial data, focusing on the time-series data generated from wearable sensor devices. The third chapter uses statistical and ML tools to integrate variables from the biopsychosocial disciplines to build a predictive model. Among its other important analyses and results, the key contributions of the research described in this thesis include the following: 1. using gamma distribution to model neurocognitive reaction time data that presents interesting properties (skewness and kurtosis for the data distribution) 2. using novel ‘peak heart-rate’ count metric to quantify ‘biological’ stress 3. using the ML approach to evaluate DHIs 4. using a recurrent neural network (RNN) and long short-term memory (LSTM) data prediction model to predict Difficulties in Emotion Regulation Scale (DERS) and primary emotion (PE) using wearable sensor data.Doctor of Philosoph

HIGH VOLTAGE ELECTROPHORETIC DEPOSITION FOR ELECTROCHEMICAL ENERGY STORAGE AND OTHER APPLICATIONS

High voltage electrophoretic deposition (HVEPD) has been developed as a novel technique to obtain vertically aligned forests of one-dimensional nanomaterials for efficient energy storage. The ability to control and manipulate nanomaterials is critical for their effective usage in a variety of applications. Oriented structures of one-dimensional nanomaterials provide a unique opportunity to take full advantage of their excellent mechanical and electrochemical properties. However, it is still a significant challenge to obtain such oriented structures with great process flexibility, ease of processing under mild conditions and the capability to scale up, especially in context of efficient device fabrication and system packaging. This work presents HVEPD as a simple, versatile and generic technique to obtain vertically aligned forests of different one-dimensional nanomaterials on flexible, transparent and scalable substrates. Improvements on material chemistry and reduction of contact resistance have enabled the fabrication of high power supercapacitor electrodes using the HVEPD method. The investigations have also paved the way for further enhancements of performance by employing hybrid material systems and AC/DC pulsed deposition. Multi-walled carbon nanotubes (MWCNTs) were used as the starting material to demonstrate the HVEPD technique. A comprehensive study of the key parameters was conducted to better understand the working mechanism of the HVEPD process. It has been confirmed that HVEPD was enabled by three key factors: high deposition voltage for alignment, low dispersion concentration to avoid aggregation and simultaneous formation of holding layer by electrodeposition for reinforcement of nanoforests. A set of suitable parameters were found to obtain vertically aligned forests of MWCNTs. Compared with their randomly oriented counterparts, the aligned MWCNT forests showed better electrochemical performance, lower electrical resistance and a capability to achieve superhydrophpbicity, indicating their potential in a broad range of applications. The versatile and generic nature of the HVEPD process has been demonstrated by achieving deposition on flexible and transparent substrates, as well as aligned forests of manganese dioxide (MnO2) nanorods. A continuous roll-printing HVEPD approach was then developed to obtain aligned MWCNT forest with low contact resistance on large, flexible substrates. Such large-scale electrodes showed no deterioration in electrochemical performance and paved the way for practical device fabrication. The effect of a holding layer on the contact resistance between aligned MWCNT forests and the substrate was studied to improve electrochemical performance of such electrodes. It was found that a suitable precursor salt like nickel chloride could be used to achieve a conductive holding layer which helped to significantly reduce the contact resistance. This in turn enhanced the electrochemical performance of the electrodes. High-power scalable redox capacitors were then prepared using HVEPD. Very high power/energy densities and excellent cyclability have been achieved by synergistically combining hydrothermally synthesized, highly crystalline α-MnO2 nanorods, vertically aligned forests and reduced contact resistance. To further improve the performance, hybrid electrodes have been prepared in the form of vertically aligned forest of MWCNTs with branches of α-MnO2 nanorods on them. Large- scale electrodes with such hybrid structures were manufactured using continuous HVEPD and characterized, showing further improved power and energy densities. The alignment quality and density of MWCNT forests were also improved by using an AC/DC pulsed deposition technique. In this case, AC voltage was first used to align the MWCNTs, followed by immediate DC voltage to deposit the aligned MWCNTs along with the conductive holding layer. Decoupling of alignment from deposition was proven to result in better alignment quality and higher electrochemical performance

Band-Gap Tunable Colloidal Perovskite Nanocrystals Functionalized with Formamidinium Cation for Photodetector Application

Solar cells , PhotodetectorColloidal quantum dots of lead halide perovskites (PQDs) have drawn much attention in the field of various optoelectronic applications such as solar cells, lasers and light emitting diodes (LEDs) due to their size- and composition-dependent optical bandgaps (Eg), high absorption coefficient, defect tolerance band structure and narrow band emission. Various PQDs such as CsPbI3, FAPbI3, and Cs1-xFAxPbI3 have been largely used as a photovoltaic absorber in room-temperature and solution-processed thin film solar cells because of the use of pre-crystallized PQDs while fabricating the PQD thin films, which lead to the absence of thermal an-nealing process normally used in conventional perovskite thin film approach. For analysing the charge transport properties, the PQDs could be employed on photodetectors. Because of low trap density, long carrier life time and diffusion length, PQDs are an ideal material to improve the performance of the photodetectors. PQDs are used a semiconducting material in the photodetector which absorbs the incident photon and gener-ate the electron-hole pair. Photocurrent is generated as result of extraction of the charge carries with the ap-plication of external or build-in electric field. In particular, transistor-type photodetector is used, as the pho-toresponsivity of the material increases without the loss of response speed. During the operation of the device, the high mobility of the material is obtained through the accumulation of charge carriers across the channel. Also, due to the reduced recombination rate of the photogenerated electron-hole pair, the carrier life time is increased. In this work, we introduce a strategy to improve the inherent charge transporting of the PQDs thin film by selective removal of anionic oleates and cationic oleylammonium. First, to study on the optical properties of the PQDs, CsPbI3 and FAPbI3 are synThesesed through hot injection method. The A-site interplay between the CsPbI3 and FAPbI3 leads to the formation of Cs1-xFAxPbI3 through controlled cation exchange reaction. Also, since the amount of ligands bound to each PQDs varies after the synTheses, the removal and replacement of the surface passivating long chain ligands with a short chain ligand through ligand exchange mechanism im-proves the coupling between the quantum dots. Furthermore, to study the inherent charge transport mecha-nism, incorporating the PQDs in transistor-type photodetector lead to many significant observations.openAbstract v List of contents vi-vii List of figures viii Ⅰ. Part 1 SynTheses of Bandgap Tunable Perovskite Quantum Dots 1 1. Introduction 2 1.1 Perovskite Crystal Structure 2 1.2 Solution Processing of Perovskites 4 2. Experimental Section 9 2.1 SynTheses of Cs-Oleate Precursor 9 2.2 SynTheses of FA-Oleate Precursor 9 2.3 SynTheses of CsPbI3 10 2.4 SynTheses of FAPbI3 11 2.5 SynTheses of FA1-xCsxPbI3 12 3. Characterization 13 3.1 UV-Vis Spectroscopy 13 3.2 Photoluminascence spectroscopy 13 3.3 TRPL spectroscopy 13 3.4 X-Ray Diffraction 13 3.5 Transmission Electron microscopy 13 3.6 FTIR spectroscopy 14 4. Results and Discussion 15 IⅠ. Part 2 Application of PQDs in Photodetector 25 1. Introduction 25 2. Device Fabrication 28 3. Results and Discussion 30 4. Conclusion 30 References 35할로겐화 페로브스카이트의 콜로이드 양자점 (PQD)은 태양전지, 레이저 및 발광다이오드 (LED)와 같은 다양한 광전자 분야에서 크기 및 구성 의존 광학 밴드갭 (Eg), 흡광 계수, defect tol-erance밴드 구조 및 좁은 밴드 방출과 같은 많은 장점으로 인해 관심을 받고 있습니다. PQD 박막을 제조할 때, 사전에 결정화된 PQD를 사용하고, 이는 기존 페로브스카이트 박막 제조에 필요한 열 처리가 필요하지 않기 때문에, CsPbI3, FAPbI3 및 Cs1-xFAxPbI3와 같은 PQD는 상온 및 용액공정 박막 태양전지에서 광-흡수제로 이용되어 왔습니다. 또한, 전하 수송 특성을 분석하기 위해, PQD는 광 검출기에 사용될 수 있습니다. 낮은 트랩 밀도, 긴 캐리어 수명 및 확산 길이로 인해 PQD는 광 검출기의 성능을 향상시키는데 이상적인 재료입니다. 또한, PQD는 입사광을 흡수하고 전자-정공쌍을 생성하는 광 검출기 내의 반도체 물질로 사용됩니다. 광전류는 외부 혹은 build-in전기장의 적용으로 전하 운반체를 추출한 결과로 생성됩니다. 특히, 물질의 광-투과성이 응답속도 손실 없이 증가하기 때문에 트랜지스터형 광 검출기가 사용될 수 있습니다. 소자 구동중, 전하 캐리어의 축적을 통해 높은 이동도가 얻어집니다. 또한, 광생성 전자-정공쌍의 감소된 재결합 속도로 인해, 캐리어 수명 시간이 증가됩니다. 본 연구는 음이온성 올레이트와 양이온성 올레일암모늄을 선택적으로 제거하여 PQDs 박막의 고유 전하 수송을 향상시키는 전략을 소개합니다. 먼저, PQD의 광학적 특성을 연구하기 위해, CsPbI3 및 FAPbI3는 열 주입 방법을 통해 합성되었습니다. CsPbI3과 FAPbI3 사이의 A-사이트 상호작용은 조절된 양이온 교환 반응을 통해 Cs1-xFAxPbI3의 형성을 유도합니다. 또한, 합성 후 각각의 PQD에 결합된 리간드의 양이 다르기 때문에, 표면에 흡착된 긴 체인 리간드를 짧은 체인 리간드로 제거 및 대체하는 것은 양자점 사이의 커플 링을 향상시킵니다. 또한, 고유 전하 수송 메커니즘을 연구하기 위해, 트랜지스터 타입 광 검출기에 PQD를 적용하는 것은 중요한 관찰로 이어질 수 있습니다.MasterdCollectio

Home Ownership, Savings, and Mobility Over The Life Cycle

In a Bewley model with endogenous price volatility, home ownership and mobility across locations and jobs, we assess the contribution of financial constraints, housing illiquidities and house price risk to home ownership over the life cycle. The model can explain the rise in home ownership and fall in mobility over the life cycle. While some households rent due to borrowing constraints in the mortgage market, factors that effect propensities to save and move, such as risky house values and transactions costs, are more important determinants of the ownership rate

Series Solution to the Transient Convective Diffusion Equation for a Rotating Disk Electrode

A series solution to the transient convective diffusion equation for the rotating disc electrode system is presented and compared to previously reported solutions. The solution presented here is for the entire time domain and agrees well with both the short and long time solutions presented earlier in the literature

Simulation of the Oxygen Reduction Reaction at an RDE in 0.5 M H\u3csub\u3e2\u3c/sub\u3eSO\u3csub\u3e4\u3c/sub\u3e Including an Adsorption Mechanism

Oxygen reduction on the surface of a rotating disk electrode (RDE) in 0.5 M H2SO4 is simulated by including mass transfer, adsorption, and charge transfer. A generalized model for the adsorption and reaction of several species is introduced. The oxygen reduction reaction is simulated as a limiting case where oxygen is the only species adsorbed, and oxygen reduction is the only reaction that takes place on the surface of the electrode. The model is based on the Nernst–Planck equations for mass transfer and the Butler–Volmer equation for electrochemical kinetics. The simulated polarization curves capture the change in the Tafel slopes, which are observed experimentally but cannot be explained by the normal four-electron-transfer mechanism. The adsorption model is compared with the four-electron-transfer model by fitting experimental data to both models using a nonlinear parameter estimation technique. The effects of changes in some important kinetic parameters are demonstrated

Parameter Estimation and Model Discrimination for a Lithium-Ion Cell

Two different models were used to obtain transport and kinetic parameters using nonlinear regression from experimental charge/discharge curves of a lithium-ion cell measured at 35°C under four rates, C/5, C/2, 1C, and 2C, where the C rate is 1.656A . The Levenberg-Marquardt method was used to estimate parameters in the models such as the diffusion of lithium ions in the positive electrode. A confidence interval for each parameter was also presented. The parameter values lie within their confidence intervals. The use of statistical weights to correct for the scatter in experimental data as well as to treat one set of data in preference to other is illustrated. An F-test was performed to discriminate between the goodness of fit obtained from the two models

Simulation of Polarization Curves for Oxygen Reduction Reaction in 0.5 M H\u3csub\u3e2\u3c/sub\u3eSO\u3csub\u3e4\u3c/sub\u3e at a Rotating Ring Disk Electrode

A cylindrical two-dimensional model based on the Nernst–Planck equations, the Navier–Stokes equation, and the continuity equation is used to simulate the oxygen reduction reaction in 0.5MH2SO4 at a rotating ring disk electrode. Concentration distributions and a potential profile are obtained as a function of the axial and radial distances from the center of the electrode surface. Polarization curves are simulated to interpret experimental results by studying various reaction mechanisms, i.e., the four-electron-transfer reduction of oxygen, the two-electron-transfer reduction of oxygen, a combination of the above two reactions, mechanisms with reduction of peroxide to water, and/or the heterogeneous chemical decomposition of peroxide. Special attention is devoted to the effect of peroxide

Towards machine learning approach for digital-health intervention program

Digital-Health intervention (DHI) are used by health care providers to promote engagement within community. Effective assignment of participants into DHI programs helps increasing benefits from the most suitable intervention. A major challenge with the roll-out and implementation of DHI, is in assigning participants into different interventions. The use of biopsychosocial model [18] for this purpose is not wide spread, due to limited personalized interventions formed on evidence-based data-driven models. Machine learning has changed the way data extraction and interpretation works by involving automatic sets of generic methods that have replaced the traditional statistical techniques. In this paper, we propose to investigate relevance of machine learning for this purpose and is carried out by studying different non-linear classifiers and compare their prediction accuracy to evaluate their suitability. Further, as a novel contribution, real-life biopsychosocial features are used as input in this study. The results help in developing an appropriate predictive classication model to assign participants into the most suitable DHI. We analyze biopsychosocial data generated from a DHI program and study their feature characteristics using scatter plots. While scatter plots are unable to reveal the linear relationships in the data-set, the use of classifiers can successfully identify which features are suitable predictors of mental ill health