Continuous Estimation of Smoking Lapse Risk from Noisy Wrist Sensor Data Using Sparse and Positive-Only Labels

Estimating the imminent risk of adverse health behaviors provides opportunities for developing effective behavioral intervention mechanisms to prevent the occurrence of the target behavior. One of the key goals is to find opportune moments for intervention by passively detecting the rising risk of an imminent adverse behavior. Significant progress in mobile health research and the ability to continuously sense internal and external states of individual health and behavior has paved the way for detecting diverse risk factors from mobile sensor data. The next frontier in this research is to account for the combined effects of these risk factors to produce a composite risk score of adverse behaviors using wearable sensors convenient for daily use. Developing a machine learning-based model for assessing the risk of smoking lapse in the natural environment faces significant outstanding challenges requiring the development of novel and unique methodologies for each of them. The first challenge is coming up with an accurate representation of noisy and incomplete sensor data to encode the present and historical influence of behavioral cues, mental states, and the interactions of individuals with their ever-changing environment. The next noteworthy challenge is the absence of confirmed negative labels of low-risk states and adequate precise annotations of high-risk states. Finally, the model should work on convenient wearable devices to facilitate widespread adoption in research and practice. In this dissertation, we develop methods that account for the multi-faceted nature of smoking lapse behavior to train and evaluate a machine learning model capable of estimating composite risk scores in the natural environment. We first develop mRisk, which combines the effects of various mHealth biomarkers such as stress, physical activity, and location history in producing the risk of smoking lapse using sequential deep neural networks. We propose an event-based encoding of sensor data to reduce the effect of noises and then present an approach to efficiently model the historical influence of recent and past sensor-derived contexts on the likelihood of smoking lapse. To circumvent the lack of confirmed negative labels (i.e., annotated low-risk moments) and only a few positive labels (i.e., sensor-based detection of smoking lapse corroborated by self-reports), we propose a new loss function to accurately optimize the models. We build the mRisk models using biomarker (stress, physical activity) streams derived from chest-worn sensors. Adapting the models to work with less invasive and more convenient wrist-based sensors requires adapting the biomarker detection models to work with wrist-worn sensor data. To that end, we develop robust stress and activity inference methodologies from noisy wrist-sensor data. We first propose CQP, which quantifies wrist-sensor collected PPG data quality. Next, we show that integrating CQP within the inference pipeline improves accuracy-yield trade-offs associated with stress detection from wrist-worn PPG sensors in the natural environment. mRisk also requires sensor-based precise detection of smoking events and confirmation through self-reports to extract positive labels. Hence, we develop rSmoke, an orientation-invariant smoking detection model that is robust to the variations in sensor data resulting from orientation switches in the field. We train the proposed mRisk risk estimation models using the wrist-based inferences of lapse risk factors. To evaluate the utility of the risk models, we simulate the delivery of intelligent smoking interventions to at-risk participants as informed by the composite risk scores. Our results demonstrate the envisaged impact of machine learning-based models operating on wrist-worn wearable sensor data to output continuous smoking lapse risk scores. The novel methodologies we propose throughout this dissertation help instigate a new frontier in smoking research that can potentially improve the smoking abstinence rate in participants willing to quit

The emergence of biofilms:Computational and experimental studies

The response of biofilms to any external stimuli is a cumulative response aggregated from individual bacteria residing within the biofilm. The organizational complexity of biofilm can be studied effectively by understanding bacterial interactions at cell level. The overall aim of the thesis is to explore the complex evolutionary behaviour of bacterial biofilms. This thesis is divided into three major studies based on the type of perturbation analysed in the study. The first study analyses the physics behind the development of mushroom-shaped structures from the influence of nutrient cues in biofilms. Glazier-Graner-Hogeweg model is used to simulate the cell characteristics. From the study, it is observed that chemotaxis of bacterial cells towards nutrient source is one of the major precursors for formation of mushroom-shaped structures. The objective of the second study is to analyse the impact of environmental conditions on the inter-biofilm quorum sensing (QS) signalling. Using a hybrid convection-diffusion-reaction model, the simulations predict the diffusivity of QS molecules, the spatiotemporal variations of QS signal concentrations and the competition outcome between QS and quorum quenching mutant bacterial communities. The mechanical effects associated with the fluid-biofilm interaction is addressed in the third study. A novel fluid-structure interaction model based on fluid dynamics and structural energy minimization is developed in the study. Model simulations are used to analyse the detachment and surface effects of the fluid stresses on the biofilm. In addition to the mechanistic models described, a separate study is carried out to estimate the computational efficiency of the biofilm simulation models

PROGRAM and PROCEEDINGS THE NEBRASKA ACADEMY OF SCIENCES 1880-2017 Including the Nebraska Association of Teachers of Science (NATS) Division Nebraska Junior Academy of Sciences (NJAS) Affiliate and Affiliated Societies

FRIDAY, APRIL 21, 2017 7:30 a.m. REGISTRATION FOR ACADEMY, Lobby of Lecture wing, Olin Hall 8:00 Aeronautics and Space Science, Session A, Olin 249 Aeronautics and Space Science, Session B, Olin 224 Chemistry and Physics, Section A, Chemistry, Olin A Collegiate Academy, Biology, Session A, Olin B Collegiate Academy, Biology, Session B, Olin 112 Collegiate Academy, Chemistry and Physics, Session A, Olin 324 8:30 Biological and Medical Sciences, Session A, Smith Callen Conference Center 9:10 Aeronautics and Space Science, Poster Session, Olin 249 9:40 Applied Science and Technology, Olin 325 10:00 Chemistry and Physics, Physics, Section B, Planetarium 10:30 Aeronautics and Space Science, Poster Session, Olin 249 11:00 MAIBEN MEMORIAL LECTURE, OLIN B – Scholarship and Friend of Science Recipients also announced. 12:00 LUNCH, PATIO ROOM, STORY STUDENT CENTER Aeronautics Group, Sunflower Room 1:00 p.m. Anthropology, Olin 111 Biological and Medical Sciences, Session B, Smith Callen Conference Center Collegiate Academy, Biology, Session A, Olin B Collegiate Academy, Biology, Session B, Olin 112 Collegiate Academy, Chemistry and Physics, Session B, Olin 324 Earth Science, Olin 249 1:05 Applied Science and Technology, Olin 325 1:15 Teaching of Science and Math, Olin 224 Chemistry and Physics, Section A, Chemistry, Olin A 2:45 Environmental Sciences, Olin 249 4:30 BUSINESS MEETING, OLIN B Abstracts of papers 2016-2017 EXECUTIVE COMMITTEE 2016-2017 PROGRAM COMMITTEE 2016-2017 POLICY COMMITTEE FRIENDS OF THE ACADEMY FRIEND OF SCIENCE AWARD WINNERS FRIEND OF SCIENCE AWARD TO KACIE BAUM FRIEND OF SCIENCE AWARD TO TODD YOUNG Author Index 141 p

Recent Application in Biometrics

In the recent years, a number of recognition and authentication systems based on biometric measurements have been proposed. Algorithms and sensors have been developed to acquire and process many different biometric traits. Moreover, the biometric technology is being used in novel ways, with potential commercial and practical implications to our daily activities. The key objective of the book is to provide a collection of comprehensive references on some recent theoretical development as well as novel applications in biometrics. The topics covered in this book reflect well both aspects of development. They include biometric sample quality, privacy preserving and cancellable biometrics, contactless biometrics, novel and unconventional biometrics, and the technical challenges in implementing the technology in portable devices. The book consists of 15 chapters. It is divided into four sections, namely, biometric applications on mobile platforms, cancelable biometrics, biometric encryption, and other applications. The book was reviewed by editors Dr. Jucheng Yang and Dr. Norman Poh. We deeply appreciate the efforts of our guest editors: Dr. Girija Chetty, Dr. Loris Nanni, Dr. Jianjiang Feng, Dr. Dongsun Park and Dr. Sook Yoon, as well as a number of anonymous reviewers

Aerospace Medicine and Biology: A continuing bibliography with indexes, supplement 159

This bibliography lists 257 reports, articles, and other documents introduced into the NASA scientific and technical information system in September 1976

Oxygen sensing mechanisms in retinal vascular development and disease.

Oxygen sensing is a fundamental biological process which is critical for appropriate development of the eye and implicated in neovascular eye disease including age-related macular degeneration, diabetic retinopathy and retinopathy of prematurity. This thesis describes a programme of work designed to investigate the role of hypoxia-inducible transcription factors (Hif’s), its downstream effector proteins, and its upstream regulator, the von Hippel Lindau protein (Vhl), in the development of the eye and neovascular eye disease. The first part of this work investigates the consequences of Hif activation in the developing retinal pigment epithelium (RPE) using a tissue specific knockout technology in mice. It demonstrates that appropriate regulation of Hif’s by Vhl is essential for normal RPE and iris development, ocular growth and vascular development and indicates that ocular hypoxia may be a previously unrecognised mechanism in the development of microphthalmia. The second part of this work studies the role of Hif1a in myeloid cells in the development of pathological neovascularisation using tissue-specific knockout technology and murine models for retinal and choroidal neovascularisation. It demonstrates that Hif1a signalling in myeloid cells contributes substantially to the development of retinal and choroidal neovascularisation and provides a rationale for developing antiangiogenic treatments that target Hif1a signalling in myeloid cells in neovascular eye disease. The third part of this work investigates the oxygen distribution in the vitreous and its relation to HIF1a and its downstream molecules in proliferative diabetic retinopathy (PDR) in man. It identifies significant intraocular oxygen gradients in PDR with areas of hyperoxia and hypoxia and demonstrates increased levels of HIF1a in the vitreous in PDR which correlate with increased levels of inflammatory and angiogenic cytokines in PDR. These findings suggest that HIF1a activation by inflammation and/or hypoxia is a central feature in the progression of PDR and that its inhibition may potentially serve as a target for therapeutic intervention

Earth resources: A continuing bibliography with indexes (issue 62)

This bibliography lists 544 reports, articles, and other documents introduced into the NASA scientific and technical information system between April 1 and June 30, 1989. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economic analysis

Zellen als lebende Materialien: Kraftspektroskopische Untersuchung der Mechanotransduktion

Mechanotransduction describes a cellular mechanism of sensing and converting mechanical cues into biochemical signals to regulate cell processes, such as adhesion, migration, proliferation and/or apoptosis. Thus, becoming an ever-growing field of research with high potential for medical applications. I present a new strategy towards reliable microindentation measurements, which is essential for investigating mechanotransduction using soft substrates. I show a precise, reproducible determination of Young’s moduli through an automatic analysis of indentation data. The algorithm presented detects Young’s moduli in a region without dependence on indentation depth while minimizing the fitting error. This strategy is a step towards a comprehensive study of soft materials on a spatial scale similar to cell interactions. It has broad applicability ranging from fundamental research to developing innovative implants that match the in vivo situation. Also, I present novel approaches for multifaceted cellular manipulation. I show that layer thickness of a soft material fixed to a stiff underlying substrate can be crucial for cell adhesion. These findings are pioneer for new implant designs and advanced application fields. I present two atomic force microscopy-based manipulation systems that allow applying specific mechanical stimuli to single cells and a subsequent correlation to whole cell detachment and single bond strengths. The unique AFM-based shear system presented combines application of shear stimuli and cell detachment measurements, whereas the AFM-based modulation system combines oscillatory pushing and pulling with cell detachment measurements. Both shear and oscillatory forces are essential in our body. Thus, the strategies presented in this thesis are of significant medical interest allowing an overarching study of mechanotransduction and may pave the way towards smart stimulation devices that allow cell adhesion on demand

Fine Art Pattern Extraction and Recognition

This is a reprint of articles from the Special Issue published online in the open access journal Journal of Imaging (ISSN 2313-433X) (available at: https://www.mdpi.com/journal/jimaging/special issues/faper2020)