Accumulating evidence points to a fundamental connection between sleep and feeding behavior. However, the temporal, genetic, and neuronal architecture that defines these relationships is poorly understood. Drosophila are amenable to high-throughput studies and offer numerous genetic tools which have advanced our understanding of the mechanistic relationships between these behaviors. However, certain features of the sleep-feeding axis have remained elusive, largely due to the separate measurement of sleep and feeding. Here, I develop a system which simultaneously measures sleep and feeding in individual animals by employing high resolution machine vision tracking and micro-controller interface functionality. Using this system, I show that food consumption drives a transient rise in sleep, which depends on food quality, quantity, and timing of a meal. The leucokinin system mediates these effects, particularly in response to protein ingestion. We further use the system to examine sleep homeostasis and demonstrate sleep dependence on energy expenditure and fat-brain communication. Collectively, these findings provide novel insight into the fundamental connections between sleep and feeding behavior. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2018. / FAU Electronic Theses and Dissertations Collection

Dysregulation of sleep and metabolism has enormous health consequences. Sleep loss is linked to increased appetite and insulin insensitivity, and epidemiological studies link chronic sleep deprivation to obesity-related disorders. Interactions between sleep and metabolism involve the integration of signalling from brain regions regulating sleep, feeding, and metabolism, as well as communication between the brain and peripheral organs. In this series of studies, using the fruit fly as a model organism, we investigated how feeding information is processed to regulate sleep, and how peripheral tissues regulate sleep through the modulation of energy stores. In order to address these questions, we performed a large RNAi screen to identify novel genetic regulators of sleep and metabolism. We found that, the mRNA/DNA binding protein, Translin (trsn), is necessary for the acute modulation of sleep in accordance with feeding state. Flies mutant for trsn or selective knockdown of trsn in Leucokinin (Lk) neurons abolishes starvation-induced sleep suppression. In addition, genetic silencing of Lk neurons or a mutation in the Lk locus also disrupts the integration between sleep and metabolism, suggesting that Lk neurons are active during starvation. We confirmed this hypothesis by measuring baseline activity during fed and starved states. We found that LHLK neurons, which have axonal projections to sleep and metabolic centers of the brain, are more active during starvation. These findings suggest that LHLK neurons are modulated in accordance with feeding state to regulate sleep. Finally, to address how peripheral tissues regulate sleep, we performed an RNAi screen, selectively knocking down genes in the fat body. We found that knockdown of Phosphoribosylformylglycinamidine synthase (Ade2), a highly conserved gene involved the biosynthesis of purines, regulates sleep and energy stores. Flies heterozygous for two Ade2 mutations are short sleepers and this effect is partially rescued by restoring Ade2 to the fly fat body. These findings suggest Ade2 functions within the fat body to promote both sleep and energy storage, providing a functional link between these processes. Together, the experimental evidence presented here provides an initial model for how the peripheral tissues communicate to the brain to modulate sleep in accordance with metabolic state. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2018. / FAU Electronic Theses and Dissertations Collection

Sleep research with adults with learning disabilities has been limited. This study considered the sleep problems experienced by adults with learning disabilities in two main sections, a survey and an intervention. The survey assessed the prevalence, nature and range of sleep problems experienced by adults with learning disabilities who live at home with their families, and investigated the relationship between sleep problems and daytime behaviour disturbance. The intervention part of the study considered whether daytime behaviour difficulties reduced following a successful sleep intervention, and whether carer stress was influenced by an improvement in sleep problems. Individuals with learning disabilities who live at home with their families had prevalence figures for sleep problems higher than those experienced by the general population. The relationship between sleep and behaviour problems was highly specific with settling problems predicting hyperactivity, lethargy, irritability and the overall score on behavioural measures. The interventions did not provide substantial evidence that sleep and behaviour were related, with only one of six participants demonstrating a decrease in behaviour problems following an improvement in sleep. Carer stress did not significantly reduce as a result of the intervention. The study has provided prevalence rates of sleep problems for a population which has not been previously studied. It concludes that the relationship between sleep and behaviour definitive conclusions can be drawn. The efficacy of behavioural interventions was demonstrated, and the clinical and theoretical implications of the results were considered.

養分與睡眠的關聯是一個在睡眠科學上極具爭議性的課題。減低攝取蛋白質和碳水化合物會導致失眠，增加攝取總脂肪和油份會導致失眠。維生素和礦物質也被認為與失眠有關。此論文嘗試通過研究一般香港中國人的食習慣和失眠情況，進一步了解營養物質與失眠之間的關聯。此論文將會深入探討營養成分對失眠的影響。 / 背景和目標： 失眠是常見的睡眠障礙和公共衛生問題。失眠可分為三個亞型：難以啟動睡眠(DIM)、難以維持睡眠(DMS) 和過早覺醒類型(EMA)。然而，有關的研究多着重於外國人口。針對研究香港中國人口的失眠情況與營養成分關聯的資料相對比較少。此研究目的是找出在香港中國人口失眠與營養成分之間的關聯，有助研究失眠與營養成分之間的機制。據推測，失眠與營養成分之間於香港中國人口有關聯。香港中國人口失眠症患者的食特點跟其他地區人口會有所不同。失眠的三個亞型和營養成分之間的關聯會有所不同。 / 研究方法： 十三間學校被邀請進行了橫斷面研究。一百三十八位青少年(六十一男、七十七女) 以及一百七十三位成年人（八十四男、 八十九女）應邀參加這項研究。有關日常營養攝取量的資料，以自行申報的三天膳食記錄表取得。有關失眠症狀的評估，以自行申報的標準睡眠問卷（ISI）獲得。有關焦慮和抑鬱的評估，以自行申報的醫院焦慮抑鬱量表（HADS）取得。 / 研究結果與結論：分析顯示，失眠與減低攝取維生素A有關聯(成年人組別p = 0.02、青少年組別p = 0.01)，與減低攝取維生素D有關聯(成年人組別p = 0.02、青少年組別p = 0.01）和與減低攝取維生素E有關聯(成年人組別p = 0.02、青少年組別p = 0.01)。失眠綜合症與難以啟動睡眠(DIM)、難以維持睡眠(DMS) 和過早覺醒類型(EMA) 與減低攝取飽和脂肪、碳水化合物、維生素A 、維生素D、和維生素E有關聯。此研究證實了香港中國人口的失眠與營養成分之間有關聯。證實了香港中國人口失眠症患者的食特點跟其他地區人口有不同。證實了失眠的三個亞型和營養成分之間的關聯有不同。我們於這項研究成功找到與失眠有關的營養成分，有助研發以天然營養物質來解決香港中國人的失眠問題。 / The association of nutrients and sleep is a debatable question in sleep science. Some literatures suggest that sleep is enhanced by certain nutrients, while some other literatures suggest that sleep is deprived by certain nutrients causing insomnia. This dissertation attempts to address the association between nutrients and insomnia of Hong Kong Chinese Population. / Background and Objective: Insomnia is a common sleep disorder and a major public health issue. Insomnia could be classified into three subtypes: Difficulty in Initiating Sleep (DIS), Difficulty in Maintaining Sleep (DMS), and Early Morning Awakening (EMA). Vitamins and minerals are thought to be associated with insomnia. From literature reviews, studies in western population and in Asian population found that protein and carbohydrates, fat and oil are associated with insomnia. Insomnia could be affected by the availability of nutritional substances in individual’s diet. However, limited studies are done in Hong Kong Chinese population on the association between insomnia and nutrient components. The aim of this study is to find out the association between insomnia and nutrient components in-take in Hong Kong Chinese population. / Hypothesis: It is hypothesized insomnia and nutrient components would also have association in Hong Kong Chinese population. It is hypothesized the dietary characteristic of insomniac in Hong Kong Chinese population would be different from that of non-Hong Kong Chinese population, and it is hypothesized each insomnia subtype and nutrient components would have different association. / Method: A community-based cross-sectional study is conducted in 13 schools. There are 138 adolescents (61 male and 77 female) and 173 adults (84 male and 89 female) participated in this study. Information of daily nutrient intake is obtained by a self-administrated 3-day food diary, the assessment of insomnia symptom is obtained by a standard sleep questionnaire Insomnia Severity Index (ISI), and the assessment of anxiety and depression is obtained by Hospital Anxiety and Depression Scale (HADS). / Results and Conclusion: Agree with the hypothesis, insomnia and nutrient component have association in Hong Kong Chinese population. The dietary characteristic of insomniac in Hong Kong Chinese population is different from that of non-Hong Kong Chinese population. Each insomnia subtype and nutrient component has different association. Multivariance analysis shows insomnia subtype Difficult Initiating Sleep (DIS), Difficult Maintaining Sleep (DMS), Early Morning Awakening (EMA), and overall insomnia syndrome associate with decreased in-take of vitamin A, vitamin D and vitamin E in both adults and adolescents. Decreased intake of saturated fat associates with insomnia subtype DMS and decreased intake of carbohydrate associates with insomnia subtype EMA in this study. Information from this study shines lights on the relationship of insomnia and nutrients in-take in the general population of Hong Kong Chinese. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Lau, Yin Wah Vivien. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 82-90). / Abstracts also in Chinese. / Abstract: --- p.i-iv / Acknowledgements: --- p.v / Table of contents: --- p.vi-viii / List of Lists: --- p.ix / List of Tables: --- p.ix / List of Figures: --- p.ix / Objective --- p.1 / Chapter Chapter 1: --- Introduction / Chapter 1.1 --- Sleep Research --- p.2 / Chapter 1.1.1 --- Background and History of Sleep Research --- p.2-3 / Chapter 1.1.2 --- Sleep Function and Consequence --- p.3-4 / Chapter 1.1.3 --- Neurotransmitters and Neuromodulators --- p.4-5 / Chapter 1.2 --- Insomnia --- p.5 / Chapter 1.2.1 --- The Definition of Insomnia --- p.6 / Chapter 1.2.1.1 --- Many Different Definitions of Insomnia Diagnostic Criteria --- p.6 / Chapter 1.2.1.2 --- Diagnostic Criteria used for Insomnia in This Study --- p.6-8 / Chapter 1.2.1.3 --- Symptoms and Syndrome of Insomnia --- p.9-10 / Chapter 1.2.2 --- The Cost of Insomnia --- p.10-11 / Chapter 1.2.3 --- The Common Causes of Insomnia --- p.11 / Chapter 1.2.4 --- Cognitive-Behavioral Model of Insomnia --- p.12 / Chapter 1.2.5 --- Treatments of Insomnia --- p.14 / Chapter 1.2.6 --- Confounding Factors of Insomnia --- p.14 / Chapter Chapter 2: --- Age, Education and Body Mass Effect on Sleep Pattern / Chapter 2.1 --- Age --- p.16 / Chapter 2.2 --- Education --- p.17 / Chapter 2.3 --- Body Mass --- p.17 / Chapter Chapter 3: --- Mood, Pain, Sleep Hygiene, Drug, Caffeine and Alcohol Effect on Sleep Pattern / Chapter 3.1 --- Mood --- p.18 / Chapter 3.2 --- Pain --- p.18 / Chapter 3.3 --- Sleep Hygiene --- p.18 / Chapter 3.4 --- Drug --- p.20 / Chapter 3.5 --- Caffeine --- p.20 / Chapter 3.6 --- Alcohol --- p.20 / Chapter Chapter 4: --- Nutrient Components / Chapter 4.1 --- Macro-nutrient --- p.21 / Chapter 4.1.1 --- Carbohydrate --- p.21-22 / Chapter 4.1.2 --- Fatty Acid --- p.22-23 / Chapter 4.1.3 --- Protein --- p.23-24 / Chapter 4.2 --- Micro-nutrient --- p.24 / Chapter 4.2.1 --- Vitamin B₁ (Thiamine) --- p.24 / Chapter 4.2.2 --- Vitamin B₂ (Riboflavin) and Vitamin B₃ (Niacin) --- p.24-25 / Chapter 4.2.3 --- Vitamin B₆ (Pyridoxine) --- p.25 / Chapter 4.2.4 --- Vitamin B₁₂ (Cobalamin, Folate) --- p.25-26 / Chapter 4.2.5 --- Vitamin A and Vitamin D --- p.26-27 / Chapter 4.2.6 --- Tryptophan, Tyrosine, Choline and Phosphatidylcholine (Lecithin) --- p.27-28 / Chapter 4.2.7 --- Vitamin E and Vitamin C --- p.30 / Chapter 4.2.8 --- Iron --- p.30 / Chapter Chapter 5: --- Nutrient Components and Insomnia / Chapter 5.1 --- Introduction --- p.32 / Chapter 5.2 --- Social Perspective of Insomnia and Nutrients --- p.33 / Chapter 5.3 --- Biochemical Perspective of Insomnia and Nutrients --- p.33-34 / Chapter Chapter 6: --- Material and Method / Chapter 6.1 --- Sampling Method --- p.35 / Chapter 6.1.1 --- Background --- p.35 / Chapter 6.1.2 --- Method --- p.35 / Chapter 6.1.3 --- Population --- p.35 / Chapter 6.1.4 --- Questionnaire --- p.36 / Chapter 6.1.5 --- Food Diary --- p.36 / Chapter 6.2 --- Participant Recruitment Criteria --- p.38 / Chapter 6.2.1 --- Major Inclusion Criteria for This Study --- p.38 / Chapter 6.2.2 --- Major Exclusion Criteria for This Study --- p.38 / Chapter 6.2.3 --- Ethical Considerations --- p.38 / Chapter 6.3 --- Statistic Analysis --- p.39 / Chapter 6.4 --- Quality Assessment and Data Extraction --- p.39 / Chapter 6.5 --- Hypothesis --- p.40 / Chapter Chapter 7: --- Results / Chapter 7.1 --- Demographic Data --- p.41 / Chapter 7.2 --- Overall Insomnia --- p.43 / Chapter 7.2.1 --- Difficult Initiating Sleep (DIS) --- p.52 / Chapter 7.2.2 --- Difficulty Maintaining Sleep (DMS) --- p.52 / Chapter 7.2.3 --- Early Morning Awakening (EMA) --- p.61 / Chapter 7.2.4 --- Insomnia Syndrome --- p.61 / Chapter Chapter 8: --- Discussion and Limitation / Chapter 8.1 --- Age and Insomnia --- p.71 / Chapter 8.2 --- Alcohol and Insomnia --- p.72 / Chapter 8.3 --- Caffeine and Insomnia --- p.72 / Chapter 8.4 --- Carbohydrate and Insomnia --- p.72-73 / Chapter 8.5 --- Vitamin E and Insomnia --- p.73 / Chapter 8.6 --- Vitamin A and Insomnia --- p.74 / Chapter 8.7 --- Vitamin D and Insomnia --- p.74 / Chapter 8.8 --- Saturated Fat and Insomnia --- p.75 / Chapter 8.9 --- Summary --- p.76 / Chapter Chapter 9: --- Limitation and Implications / Chapter 9.1 --- Limitation of This Study --- p.77 / Chapter 9.2 --- Implication to Further Study --- p.77-78 / Chapter 9.3 --- Implication to Clinical Intervention --- p.78-79 / Chapter Chapter 10: --- Executive Summary --- p.80-81 / Bibliography --- p.82-90

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This thesis introduces different mechanisms for energy efficiency in Wireless Sensor Networks (WSNs) along with maintaining high levels of Network Performance (N.P) with reduced complexity. Firstly, a Machine-to-Machine (M2M) WSN is arranged hierarchically in a fixed infrastructure to support a routing protocol for energy-efficient data transmission among terminal nodes and sink nodes via cluster heads (CHs). A Multi-Level Clustering Multiple Sinks (MLCMS) routing protocol with the IPv6 protocol over Low Wireless Personal Area Networks (6LoWPAN) is proposed to prolong network lifetime. The simulation results show 93% and 147% enhancement in energy efficiency and system lifespan compared to M-LEACH and LEACH, respectively. By utilising 6LoWPAN in the proposed system, the number of packets delivered increases by 7%, with higher accessibility to the M2M nodes and a substantial extension of the network is enabled. Secondly, an adaptive sleep mode with MLCMS for an efficient lifetime of M2M WSN is introduced. The time period of the active and asleep modes for the CHs has been considered according to a mathematical function. The evaluations of the proposed scheme show that the lifetime of the system is doubled and the end-to-end delay is reduced by half. Thirdly, enhanced N.P is achieved through linear integer-based optimisation. A Self-Organising Cluster Head to Sink Algorithm (SOCHSA) is proposed, hosting Discrete Particle Swarm Optimisation (DPSO) and Genetic Algorithm (GA) as Evolutionary Algorithms (EAs) to solve the N.P optimisation problem. N.P is measured based on load fairness and average ratio residual network energy. DPSO and GA are compared with the Exhaustive Search (ES) algorithm to analyse their performances for each benchmark problem. Computational results prove that DPSO outperforms GA regarding complexity and convergence, thus it is best suited for a proactive IoT network. Both algorithms achieved optimum N.P evaluation values of 0.306287 and 0.307731 in the benchmark problems P1 and P2, respectively, for two and three sinks. The proposed mechanism satisfies different N.P requirements of M2M traffic by instant identification and dynamic rerouting to achieve optimum performance. Finally, a Power Model (PM) is essential to investigate the power efficiency of a system. Hence, a Power Consumption (PC) profile for SDN-WISE, based on IoT is developed. The outcomes of the study offer flexibility in managing the structure of an M2M system in IoT. They enable controlling the provided Network Quality of Service (NQoS), precisely by achieving physical layer throughput. In addition, it provides a schematic framework for the Application Quality of Service (AQoS), specifically, the IoT data stream payload size (from the PC point of view). It is composed of two essential parts, i.e., control signalling and data traffic PCs and the results show a 98% PC of the data plane in the total system power, whereas the control plane PC is only 2%, with a minimum Transmission Time Interval (TTI) (5 sec) and a maximum payload size of 92 Bytes.

Childhood is one of the most important stages for physical and cognitive growth during the life course. For young children, sleep is one of the major contributors to healthy development; poor sleep quality and short sleep duration can detrimentally affect developmental progress. In addition to physiological contributors to poor sleep, social factors may affect young children’s sleep. Prior findings suggest that demographic and socioeconomic characteristics, such as race and parent’s educational attainment, may contribute to sleep health for children. Furthermore, limited prior research suggests that neighborhood attributes may affect sleep for both children and adults alike. To my knowledge, no study exists that examines neighborhood effects and sleep for children under the age of six. Therefore, my investigation examines the effect of neighborhood disadvantage on the bedtimes of kindergarten-aged children, a proxy for sleep health. In order to examine the effects of neighborhood disadvantage on sleep, this study utilizes multilevel statistical methods to determine the influence of both individual- and neighborhood-level characteristics. The results from these analyses indicate that while individual-level demographic and socioeconomic characteristics contribute explain more variance in bedtimes than neighborhood-level attributes, neighborhoods significantly affect bedtimes—especially racial composition and overall levels of educational attainment. These findings suggest the need for further research on the effects of neighborhoods on sleep and ultimately health outcomes.

Master of Science / In this thesis, a recently developed physiologically-based model of the sleep-wake switch is analyzed and applied to a variety of clinically-relevant protocols. In contrast to phenomenological models, which have dominated sleep modeling in the past, the present work demonstrates the advantages of the physiologically-based approach. Dynamical and linear stability analyses of the Phillips-Robinson sleep model allow us to create a general framework for determining its response to arbitrary external stimuli. The effects of near-stable wake and sleep ghosts on the model’s dynamics are found to have implications for arousal during sleep, sleep deprivation, and sleep inertia. Impulsive sensory stimuli during sleep are modeled modeled according to their known physiological mechanism. The predicted arousal threshold variation matches experimental data from the literature. In simulating a sleep fragmentation protocol, the model simultaneously reproduces the body temperature and arousal threshold variation measured in another existing clinical study. In the second part of the thesis, we simulate sleep deprivation by introducing a wake-effort drive that is required to maintain wakefulness during normal sleeping periods. We interpret this drive both physiologically and psychologically, and demonstrate quantitative agreement between the model’s output and experimental subjective fatigue-related data. As well as subjective fatigue, the model is simultaneously able to reproduce adrenaline excretion and body temperature variations. In the final part of the thesis, the model is extended to include the orexinergic neurons of the lateral hypothalamic area. Due to the dynamics of the orexin group, the extended model exhibits sleep inertia, and an inhibitory circadian projection to the orexin group produces a postlunch dip in performance – both of which are well-known behavioral features. Including both homeostatic and circadian inputs to the orexin group, the model produces a waking arousal variation that quantitatively matches published clinical data.

Thesis (Ph. D.)--University of Washington, 1984. / Vita. Bibliography: leaves [73]-82.

Sleep scoring involves classification of polysomnographic data into the various sleep stages as defined by Retschaffen and Kales. This process is time-consuming and laborious as it involves experts visually scoring the data. During recent years, there has been an increasing focus on automated sleep scoring systems and professional software programs are finding increased use. However, these systems are not relied on for scoring and are often used as a tool that facilitates easy visual scoring. This thesis proposes a neural network based approach to automatic sleep scoring using LabVIEW. Effort has been made to give the sleep expert more control over key parameters such as the frequency bands, and thus come up with scores that are more in agreement with the individual scorer than being a rigid interpretation of the R&K rules. Though this thesis is limited to the development of an offline software program, given the data acquisition facilites in LabVIEW, a complete system from data acquisition to sleep hypnograms is a fair possibility.