Walkability as a concept that captures the ability to walk from one place to another has multiple dimensions. Between traversability to being a proxy for better urban places, there are also numerous measurements of walkability that attempts to quantify certain or all aspects of walkability. It is, however, unclear, through a review of available literature, how these measurements of walkability relate to each other statistically. This methodology focuses on generating a framework for analysts to evaluate and prioritize pedestrian infrastructure. WalkScore™ (WS), HCM Pedestrian Level of Service (PLOS), Average Nodal Degree (AND), and Intersection Density are the four metrics selected for this analysis that focuses on distinctive aspects of walkability (proximity, amenity, network-connectivity, respectively). A sample of 51 street segments from the County of San Luis Obispo is selected according to their respective Average Daily Traffic (ADT) volumes. Pearson’s Correlations between the six combinations of relationships are measured, and the strongest correlation between the six relationships is between WalkScore™ and Intersection Density with an R2 of 0.44. A regression model that includes external factors such as population and adjacent land use is used to analyze and predict PLOS of the street segment. Although the model is not statistically significant, the goal of this research is to identify gaps in current and potential walkability of street segments in the sample. Therefore, this framework of using established walkability metrics to predict PLOS, and then distinguishing places for improvements is proposed as a result of this research to be used by government agencies to prioritize pedestrian infrastructure.

Acoustic telemetry is an important tool when studying the spatial ecology of marine animals. First, it is important to identify the challenges of using this tool in shallow tropical marine environments before tracking marine animals. One significant issue that can influence the effectiveness of acoustic telemetry is the efficiency or detectability of acoustic signals by receivers. Understanding factors influencing detection efficiency of acoustic tags is especially important for fine-scale positioning systems (such as the VEMCO positioning system, VPS) that use detections in an overlapping receiver network to calculate geographic positions of tagged fish. I modelled the efficiency of an acoustic array in a tropical reef flat in Culebra, Puerto Rico and then tested the capability of detecting and positioning tagged permit (Trachinotus falcatus) and great barracuda (Sphyraena barracuda). Detection efficiencies were analyzed for a fine-scale array comprised of 25 receivers and 17 sync tags deployed as a fine-scale array for nearly three years. I used a generalized linear mixed-effect model Template Builder Model (glmmTMB) that helped elucidate the environmental variables that play a role in influencing the ability to detect transmitter signals. Then, I evaluated how well the fine- scale array was at detecting tagged permit (n=1) and great barracuda (n=4) using the reef flat. Once, the model was created, it was used to predict the likeliness of hourly detections of sync tags and tagged animals. Finally, the fine-scale and broad-scale array consisting of 59 receivers were used to determine the spatial movement patterns of permit and great barracuda. A glmmTMB was created to determine what environmental variables were present when each species visited the fine-scale array in the coral reef flat. The dynamic Brownian-Bridge Movement Model (DBBMM) was used to determine the fishes’ home range within the coral reef flat using X Y locations. Network connectivity was used to determine each fishes’ spatial movement patterns and community structure related to the receivers they visited. Lastly, spatial patterns throughout each diel period and season were determined. Collectively, this study revealed the benefits and limitations of using fine-scale acoustic telemetry in shallow coral reef ecosystems.

The human body encounters a number of chemical exposures on a daily basis, which may have short- or long-term health implications. Previously it has been demonstrated that the entire respiratory tract of an individual reacts to exposures like tobacco smoke in a similar manner, and that common molecular changes can be measured in airway epithelium. I propose that cataloguing the exposure of airway epithelial cells to tobacco cigarette (TCIG) smoke and its constituents, electronic cigarette (ECIG) aerosol and other drugs and small molecules can significantly increase the understanding of chemical exposure and identify common gene expression alterations. First, I determined the molecular impact of ECIG aerosol exposure on human airway epithelium in vitro, including alterations in genes related to xenobiotic metabolism, oxidative stress, and ciliated cells. These changes were generally less pronounced than the effects of TCIG exposure, and were more pronounced in ECIG products containing nicotine than those without nicotine. Furthermore, gene expression differences observed in vitro were concordant with differences observed in airway epithelium collected from ECIG users. Second, I examined the impact of TCIG exposure and TCIG constituents on premalignant airway cells, to better understand the progression or regression of precancerous lesions. These data could also identify the constituents of TCIGs and the precancerous mutations that increase the risk for malignancy. Third, in an effort to build a high-throughput methodology for chemical exposures, I exposed primary lung cell lines to small molecule therapeutics and identified lung-specific and lung cell-type-specific effects of exposure, suggesting that profiling additional cell lines would further inform airway gene expression in response to exposure and that organ-specific exposure profiling may provide valuable insight into drug discovery for common diseases. Overall, transcriptomic profiles from the airway epithelium reflect exposure to various inhaled and chemical perturbations. These gene expression profiles indicate common changes across a multitude of airway exposures as well as unique alterations specific to a given perturbation. Gene expression profiling can therefore be used to detail the potential response to a compendium of chemical exposures including those that are either well-established or potential risk factors for chronic lung diseases. / 2019-07-09T00:00:00Z

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第21919号 / 情博第702号 / 新制||情||120(附属図書館) / 京都大学大学院情報学研究科システム科学専攻 / (主査)教授 石井 信, 教授 松田 哲也, 教授 加納 学, 川人 光男 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

The research involves first conducting a "case study" of ecological data and applying the results, together with the resilience concept, to the development of a greenspace conservation planning framework for urban regions. The first part of the research investigates the relationship between forest bird abundance and the surrounding landscape characteristics, especially, forest area and its spatial configuration in urban regions at multiple scales. The results are similar for simple and multiple regression analyses across three scales. The percentage of forest cover in a landscape is positively correlated with bird abundance with some thresholds. Overall, the percentage of forest cover in the landscape, contrast-weighted forest edge density, and the similarity of land cover types to forest cover are identified as important for the conservation of the target bird species. The study points to the importance of species-specific habitat requirements even for species with similar life history traits and of maintaining some forest edges and/or edge contrast. The second part of the research involves the development of a landscape planning meta-model and its conceptual application to greenspace conservation planning, integrating the results of the first part. Administrative and planning units are recognized to exist in a nested hierarchy of neighborhood, city, and urban region, just as biodiversity can be conceived in a nested hierarchical organization of genes, populations/species, communities/ecosystems, and landscapes. Resilience thinking, especially the panarchy concept, provides a scientific basis and a metaphorical framework to develop the meta-model, integrating a proposed landscape planning "best practice" model at each planning scale. Ecological concepts such as response and functional diversity, redundancy, and connectivity across scales are identified as key concepts for conserving and increasing biodiversity and the resilience of an urban region. These concepts are then used in the meta-model to develop the greenspace conservation planning framework. Ecological processes such as pollination and dispersal, as well as social memory and bottom-up social movements---small changes collectively making a large impact at the broader scales as well as these incremental changes gaining momentum as they cascade across scales---are identified as cross-scale processes and dynamics that connect various planning scales in the meta-model.

Edge networks such as sensor, mobile, and disruption tolerant networks suffer from topological uncertainty and disconnections due to myriad of factors including limited battery capacity on client devices and mobility. Hence, providing reliable, always-on consistency for network applications in such mobile and sensor systems is non-trivial and challenging. However, the problem is of paramount importance given the proliferation of mobile phones, PDAs, laptops, and music players. This thesis identifies two fundamental deterrents to addressing the above problem. First, limited energy on client mobile and sensor devices makes high levels of consistency and availability impossible. Second, unreliable support from the network infrastructure, such as coverage holes in WiFi degrades network performance. We address these two issues in this dissertation through client and infrastructure end modifications. The first part of this thesis proposes a novel energy management architecture called Hierarchical Power Management (HPM). HPM combines platforms with diverse energy needs and capabilities into a single integrated system to provide high levels of consistency and availability at minimal energy consumption. We present two systems Triage and Turducken which are instantiations of HPM for sensor net microservers and laptops respectively. The second part of the thesis proposes and analyzes the use of additional infrastructure in the form of relays, mesh nodes, and base stations to enhance sparse and dense mobile networks. We present the design, implementation, and deployment of Throwboxes a relay system to enhance sparse mobile networks and an associated system for enhancing WiFi based mobile networks.

Variability in the brain’s functional network connectivity is associated with differences in cognition. The degree to which brain networks flexibly reconfigure, or alternatively remain stable, can differ across regions of cortex, across time, and across individuals. The goal of this dissertation was to investigate how the brain’s functional network architecture is reconfigured to support abstract reasoning and rule learning. I proposed that flexibility within frontoparietal cortex, combined with a stable network core, is beneficial for effective reasoning and rule learning. Experiment One investigated the activation patterns and dynamic community structure of brain networks associated with shifting task demands during abstract reasoning. Twenty-seven subjects underwent fMRI scanning during resting state and during a subsequent abstract reasoning task. When quantifying network reconfiguration between resting and task states, I found a stable system within default and somatomotor networks alongside a more flexible frontoparietal control network. The results motivated a novel understanding of how the brain performs reasoning tasks: an underlying stable functional network acts as a cognitive control mechanism, priming task-active nodes within frontoparietal cortex to variably activate for unique task conditions. Experiment Two used a dynamic network analysis to identify changes in functional brain networks that were associated with context-dependent rule learning. During fMRI scanning, twenty-nine naïve subjects were challenged to learn a set of context-dependent rules. Successful learners showed greater stability in ventral attention and somatomotor regions, increased assortative mixing of cognitive control regions as rules were learned, and greater segregation of attention networks throughout the entire task. The results suggested that a stable ventral attention network and a flexible frontoparietal control network support sustained attention and the formation of rule representations. In Experiment Three, I carried out a separate analysis of data from Experiment 2 to characterize the functional connectivity patterns with the hippocampus that emerged during successful rule learning. The results demonstrated that the hippocampal head became increasingly functionally connected to the lateral frontal pole and caudate in successful learners. Additionally, the entire hippocampus exhibited decreased functional connectivity with the mid-cingulate and precuneus in successful learners. These three experiments demonstrated that stable functional connectivity in somatomotor and ventral attention networks, combined with flexible reconfiguration of frontoparietal cortex, is advantageous for successful rule learning and abstract reasoning. Altogether, this dissertation demonstrated that individual differences in dynamic functional connectivity are associated with learning, and that stability of brain networks across time and tasks supports higher order cognition. / 2025-01-23T00:00:00Z

This dissertation concerns the alteration of functional connectivity in the human brain through different patterns of somatosensory stimulation. In particular, I distinguish whether stimuli are regular (i.e., expected by the subject) or irregular (i.e., unexpected by the subject). An emerging theory of brain function known as Predictive Coding states that the brain is continuously creating an internal model of its environment that is constantly trying to predict what is going to happen. Expected sensory input leads to model consol- idation, while unexpected input leads to model update. In this context it is assumed that central neuronal processing differs significantly between these two cases. Furthermore, in my experiments, the stimulation is applied in two more variants which are also believed to be processed in completely different ways: consciously perceptible (suprathreshold) and imperceptible (subthreshold). To measure functional connectivity in the acquired fMRI data, a method referred to as eigenvector centrality mapping (ECM) was chosen. This method has gained increasing attention in the fMRI community, as it represents a whole-brain approach that can be ap- plied for resting-state experiments. While there are a number of other centrality measures, each with their advantages and disadvantages, ECM stands out as being parameter-free and does not depend on prior assumptions. Similar to Google’s Pagerank algorithm, it assigns areas (“nodes”) in a network with a high centrality score that are closely connected to other central areas as well. Generally, increased connectivity is interpreted as of greater “importance” to the network. As there are different approaches on how to calculate ECM, I critically examine these and delve deeper into the method itself. Three main research questions guided this study: 1. Is there a brain connectivity (ECM) alteration in the human brain for somatosensory stimulation that is pattern dependent (7 Hz irregular vs. regular)? 2. Is there a brain connectivity (ECM) alteration in the human brain for somatosensory stimulation that is intensity dependent (7 Hz suprathreshold vs. subthreshold)? 3. Are these different somatosensory stimulations (subthreshold, suprathreshold, irregular, regular) accompanied by a subsequent behavioral change? Two experiments were conducted. In Experiment 1, participants were exposed to all four stimulation conditions consecutively. Results showed significant ECM alterations compared to the initial baseline, suggesting persisting effects. To counter this, Experiment 2 adopted a different approach. Here, individual stimulations were applied to separate groups, with an additional control group for comparison. The results from Experiment 2 revealed that irregular stimulation compared to regular showed decreased connectivity in specific brain regions, aligning with the Predictive Coding theory. Suprathreshold stimulation showed increased connectivity in areas related to sensory input integration, possibly linked to conscious perception. Furthermore, all participants, regardless of stimulation type, showed heightened connectivity in somatosensory regions, suggesting a shared focus on tactile anticipation. The behavioral session from Experiment 2 found that irregular suprathreshold stimulation led to a decreased sensitivity to near-threshold stimuli. However, this change wasn't mirrored in the functional connectivity data. In conclusion, this research validated the differential neural processing of various somatosensory stimulations, supporting the Predictive Coding theory. The study also underscored the challenges and considerations in using ECM, particularly urging caution with methods that combine positive and negative correlations.:1 - Personal Motivation 2 - Introduction 3 - Background 3.1 Cognitive Neuroscience 3.2 Predictive Coding and the Free Energy Principle 3.3 Functional Magnetic Resonance Imaging (fMRI) 3.4 Blood-Oxygen Level Dependent (BOLD) Signal 3.5 Resting-State Functional Connectivity (RSFC) 3.6 Eigenvector Centrality Mapping (ECM) 3.7 Previous ECM Experiments - an Overview 3.8 Statistical Remarks 4 - Materials and Methods 4.1 Experimental Setup 4.1.1 Subjects 4.1.2 Experimental Procedures 4.1.2.1 Electrical stimulation 4.1.2.2 Absolute detection threshold examination 4.1.2.3 fMRI and behavioral data acquisition 4.2 fMRI Data Preprocessing 4.2.1 Prior Steps 4.2.2 Slice Time Correction 4.2.3 Motion Correction 4.2.4 Coregistration, Segmentation and Normalization 4.2.5 Spatial Filtering 4.2.6 Temporal Filtering 4.2.7 Grey Matter, White Matter and Cerebrospinal Fluid Masking 4.2.8 Nuisance Regression 4.3 ECM Approaches 4.4 Flexible Factorial Design 4.5 Seed-Based Functional Connectivity Analysis 5 - Results 5.1 Experiment 1 5.1.1 Detailed Results 5.1.2 Summary Experiment 1 5.2 Experiment 2 - fMRI Session 5.2.1 Detailed Results - ADD Approach 5.2.2 Detailed REsults - POS / NEG / ABS approach 5.2.3 Summary Experiment 2 5.3 ECM Approach Differences Illustrated by Examples 5.4 Seed-Based Functional Connectivity Analysis 5.5 Distribution of Voxel Timie Series Correlation Foefficients 5.6 Experiment 2 - Behavioral Session 6 - Discussion 6.1 Interpretation of Experimental Results 6.1.1 Experiment 1 6.1.2 Experimemnt 2 - fMRI Session 6.1.3 Experiment 2 - Behavioral Session 6.2 ECM Approaches 6.3 Further Considerations and Future Outlook 7 - Conclusion

Resting-state fMRI (rsfMRI) has been widely used to map intrinsic brain network organization of the human brain both in health and in pathological conditions. However, the neural underpinnings and dynamic rules governing brain-wide rsfMRI coupling remain unclear. Filling this knowledge gap is of crucial importance, given our current inability to decode and reverse-engineer clinical signatures of aberrant connectivity into interpretable neurophysiological events that can help understand or diagnose brain disorders. Toward this goal, here we combined chemogenetics, rsfMRI, and in vivo electrophysiology in the mouse to investigate how regional manipulations of brain activity (i.e. neural inhibition, or excitation) causally contribute to whole-brain fMRI network organization. In a first set of proof of concept investigations, we empirically probed the widely held notion that neural inhibition of a cortical node would result in reduced fMRI coupling of the silenced area and its long-range terminals. Surprisingly, we found that chronic inhibition of the mouse medial prefrontal cortex (PFC) via viral overexpression of a potassium channel paradoxically increased fMRI connectivity between the inhibited area and its direct thalamo-cortical targets. Notably, acute chemogenetic inhibition of the PFC reproduced analogous patterns of fMRI overconnectivity. Using in vivo electrophysiology, we found that chemogenetic inhibition of the PFC enhances low frequency (0.1 - 4 Hz) oscillatory power via suppression of neural firing not phase-locked to slow rhythms, resulting in increased slow and δ band coherence between areas that exhibit fMRI overconnectivity. These results provide causal evidence that cortical inactivation can counterintuitively increase fMRI connectivity via enhanced, less-localized slow oscillatory processes, with important implications for neural modeling and interpretation of fMRI overconnectivity in brain disorders. Importantly, our observation that neural inhibition of the PFC results in fMRI overconnectivity allowed us to predict that neural activation of the same area might produce opposite results, i.e. fMRI underconnectivity and neural desynchronization. To test this hypothesis, we used chemogenetics to increase local excitatory-inhibitory (E/I) balance in the PFC. As predicted, chemogenetic stimulation of CamkII-expressing neurons, or inhibition of fast-spiking parvalbumin-expressing neurons, produced similar rsfMRI signatures of rsfMRI underconnectivity. Both manipulations produced analogous electrophysiological signatures characterized by increased firing activity and a robust LFP power shift towards higher (i.e. γ) frequencies, effectively reversing the corresponding neural signature observed in DREADD inhibition studies. Importantly, the same E/I affecting perturbations were also associated with socio-communicative deficits in behaving mice hence underscoring the behavioral relevance of the employed manipulations. These results show that excitatory/inhibitory balance critically biases brain-wide fMRI coupling, pointing at a possible unifying mechanistic link between E/I imbalance and rsfMRI connectivity disruption in developmental disorders. More broadly, these investigations reveal a set of fundamental rules linking regional brain activity to macroscale functional connectivity, offering opportunities to physiologically interpret rsfMRI signatures of functional dysconnectivity in human brain disorders.

Dams and power plants in watercourses pose a serious threat to diversity and aquatic species as they fragment habitats and create barriers. New legislation aims to facilitate the restoration of watercourses and in many places, various fish passages have been built. Evaluations of these are important in order to ensure that the desired function has been achieved. At Näkten regulation dam in Jämtland, Sweden, a combined technical and natural fishway has been built to enable migration for trout and grayling. The purpose of the study is to find out whether the technical solution has had suitable flows and gate settings for the fish that one wanted to enable migration for. To investigate this, unsteady flow analyzes were performedin HEC-RAS and then compared to field measurements as well as information from the dam owner. The results show that the gate during the study period has not been set according to recommended settings and that the flows at times have been too high to be suitable for migration. However, comparison with field measurements and previous calculations suggest that the modeled flows do not match reality but are too high in the model. The conclusion is therefore that further modeling and a more thorough comparison with field measurements is recommended to create reliable results and that one then possibly can adjust the settings on the gates. / Dammar och kraftverk i vattendrag utgör ett allvarligt hot mot diversiteten och vattenlevande arter då den fragmenterar livsmiljöer och skapar hinder. Nya lagstiftningar ska underlätta för återställning av vattendrag och på många platser har olika fiskpassager byggts. Utvärderingar av dessa är viktiga så att man kan säkerställa att önskad funktion är uppnådd. Vid Näktens regleringsdamm i Jämtlands län har ett kombinerat tekniskt oc hnaturlikt omlöp byggts för att åter möjliggöra vandring för öring och harr. Studiens syfte är att ta reda på om den tekniska lösningen har haft lämpliga flöden och luckinställningar för de fiskar som man velat möjliggöra vandring för. För att undersöka detta har flödesmodelleringar gjorts i programmet HEC-RAS och fältmätningar samt uppgifter från dammägaren har använts som referens. Resultaten visar att luckan under studieperioden inte varit inställd efter rekommenderade inställningar och att flödena ha varit för höga för att vara lämplig för vandring. Dock tyder jämförelse med fältmätningar och tidigare beräkningar att flödena inte stämmer överens med verkligheten utan blir för höga i modellen. Slutsatsen blir därför att ytterligare modellering och en grundligare jämförelse med fältmätningar rekommenderas för att skapa tillförlitliga resultat och att man därefter eventuellt kan justera inställningarna på luckorna. / <p>2023-06-02</p>