Behavior of Turbulent Structures within a Mach 5 Mechanically Distorted Boundary Layer

High-resolution particle image velocimetry (PIV) is employed to resolve the velocity fields within a Mach 4.9 mechanically distorted turbulent boundary layer (Reθ ≈ 40,000). The goal of this study is to directly observe the mechanisms responsible for the modified turbulent stresses present in mechanically distorted boundary layers. This is achieved by measuring the effects of the mechanical distortions upon the distribution, population, size, orientation, and energy content of the turbulent structures, and how the perturbed state of these structures is manifested within the ensemble-averaged turbulent stresses. The two mechanical distortions under investigation are 1) streamline curvature-induced favorable pressure gradients (Ip = {-0.08; -0.49}), and 2) periodic arrays of diamond roughness elements (k/δ ≈ 0.07). A smooth-wall, flat-plate boundary layer is also included to establish the unperturbed state of the turbulent structures. The response of the mean turbulence statistics is investigated through ensemble-averaged profiles of Reynolds stresses, indicating the respective influences of pressure gradient effects and surface roughness upon the turbulent statistics. The distortion and reorientation of the large-scale coherent motions is quantified through the determination of the integral length scale and local structure angle from two-point correlations. Detection of individual vortices through the swirling strength criterion λci allows the population distribution of the turbulent eddies to be examined, along with the conditionally averaged hairpin structure. The baseline and rough-wall stresses showed good agreement when scaled by the smooth-wall friction velocity. Two-point correlations indicate that the reorientation of the large-scale [i.e. O(δ)] coherent structures, coupled with the modified wall-normal fluctuations, is primarily responsible for the modification of the rough-wall Reynolds stresses. The reduced Reynolds stresses observed in the favorable pressure gradients is partially due to the attenuation of the local flowfield around the near-wall hairpin structures, mitigating the mechanism for “producing” turbulence. The rotational rate of the hairpin vortices, measured through the mean prograde swirling strength, was reduced for the favorable pressure gradient models

Analysis of the supply of serviced office space

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 2001.Includes bibliographical references (leaves 66-67).The work environment has experienced tremendous change in the past few decades. Technology has been the prime catalyst to transform the demand for office space into a search for more flexible solutions in a historically inflexible asset. Serviced offices combine office space, technology and support into a global network of fully furnished, staffed and equipped offices and meeting rooms, available to occupy or vacate on flexible terms, and tailored to the specific business needs of the users. This thesis explores the objectives of these users, product and service characteristics of the serviced office space delivered to them, and the relationship between the users and the providers of serviced office space. Further, it explores the similarities and differences of big and small providers emerging as the market of serviced office space matures. The methodologies of the service profit chain are used to compare the relevant service delivery methods used by big and small serviced office providers.by Scott Peltier.S.M

Arterial cerebral blood volume–weighted functional MRI using pseudocontinuous arterial spin tagging (AVAST)

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/110725/1/mrm25220.pd

Support vector machine classification of arterial volumeâ weighted arterial spin tagging images

IntroductionIn recent years, machineâ learning techniques have gained growing popularity in medical image analysis. Temporal brainâ state classification is one of the major applications of machineâ learning techniques in functional magnetic resonance imaging (fMRI) brain data. This article explores the use of support vector machine (SVM) classification technique with motorâ visual activation paradigm to perform brainâ state classification into activation and rest with an emphasis on different acquisition techniques.MethodsImages were acquired using a recently developed variant of traditional pseudocontinuous arterial spin labeling technique called arterial volumeâ weighted arterial spin tagging (AVAST). The classification scheme is also performed on images acquired using blood oxygenationâ level dependent (BOLD) and traditional perfusionâ weighted arterial spin labeling (ASL) techniques for comparison.ResultsThe AVAST technique outperforms traditional pseudocontinuous ASL, achieving classification accuracy comparable to that of BOLD contrast images.ConclusionThis study demonstrates that AVAST has superior signalâ toâ noise ratio and improved temporal resolution as compared with traditional perfusionâ weighted ASL and reduced sensitivity to scanner drift as compared with BOLD. Owing to these characteristics, AVAST lends itself as an ideal choice for dynamic fMRI and realâ time neurofeedback experiments with sustained activation periods.In this article, we test the performance of our recently introduced method for dynamic arterial blood volume imaging (AVAST) in the context of functional MRI data classification. AVAST is compared with blood oxygenationâ level dependent (BOLD) and arterial spin labeling (ASL) perfusion data collected during a simple motor task using a support vector machine algorithm to classify the brain state. Findings suggest that the AVAST technique has similar performance as BOLD imaging, while preserving the statistical benefits of ASL techniques.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135476/1/brb3549_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/135476/2/brb3549.pd

Age Differences in Interhemispheric Interactions: Callosal Structure, Physiological Function, and Behavior

There is a fundamental gap in understanding how brain structural and functional network connectivity are interrelated, how they change with age, and how such changes contribute to older adults’ sensorimotor deficits. Recent neuroimaging approaches including resting state functional connectivity MRI (fcMRI) and diffusion tensor imaging (DTI) have been used to assess brain functional (fcMRI) and structural (DTI) network connectivity, allowing for more integrative assessments of distributed neural systems than in the past. Declines in corpus callosum size and microstructure with advancing age have been well documented, but their contributions to age deficits in unimanual and bimanual function are not well defined. Our recent work implicates age-related declines in callosal size and integrity as a key contributor to unimanual and bimanual control deficits. Moreover, our data provide evidence for a fundamental shift in the balance of excitatory and inhibitory interhemispheric processes that occurs with age, resulting in age differences in the relationship between functional and structural network connectivity. Training studies suggest that the balance of interhemispheric interactions can be shifted with experience, making this a viable target for future interventions

Resting state cortico-cerebellar functional connectivity networks: a comparison of anatomical and self-organizing map approaches.

The cerebellum plays a role in a wide variety of complex behaviors. In order to better understand the role of the cerebellum in human behavior, it is important to know how this structure interacts with cortical and other subcortical regions of the brain. To date, several studies have investigated the cerebellum using resting-state functional connectivity magnetic resonance imaging (fcMRI; Krienen and Buckner, 2009; O'Reilly et al., 2010; Buckner et al., 2011). However, none of this work has taken an anatomically-driven lobular approach. Furthermore, though detailed maps of cerebral cortex and cerebellum networks have been proposed using different network solutions based on the cerebral cortex (Buckner et al., 2011), it remains unknown whether or not an anatomical lobular breakdown best encompasses the networks of the cerebellum. Here, we used fcMRI to create an anatomically-driven connectivity atlas of the cerebellar lobules. Timecourses were extracted from the lobules of the right hemisphere and vermis. We found distinct networks for the individual lobules with a clear division into "motor" and "non-motor" regions. We also used a self-organizing map (SOM) algorithm to parcellate the cerebellum. This allowed us to investigate redundancy and independence of the anatomically identified cerebellar networks. We found that while anatomical boundaries in the anterior cerebellum provide functional subdivisions of a larger motor grouping defined using our SOM algorithm, in the posterior cerebellum, the lobules were made up of sub-regions associated with distinct functional networks. Together, our results indicate that the lobular boundaries of the human cerebellum are not necessarily indicative of functional boundaries, though anatomical divisions can be useful. Additionally, driving the analyses from the cerebellum is key to determining the complete picture of functional connectivity within the structure

Poster 261: Increased Functional Connectivity between Pain‐Affect and Body‐Perception Brain Regions in Fibromyalgia

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146909/1/pmr2s217.pd

Altered Resting State Cortico-Striatal Connectivity in Mild to Moderate Stage Parkinson's Disease

Parkinson's disease (PD) is a progressive neurodegenerative disorder that is characterized by dopamine depletion in the striatum. One consistent pathophysiological hallmark of PD is an increase in spontaneous oscillatory activity in the basal ganglia thalamocortical networks. We evaluated these effects using resting state functional connectivity MRI in mild to moderate stage Parkinson's patients on and off l-DOPA and age-matched controls using six different striatal seed regions. We observed an overall increase in the strength of cortico-striatal functional connectivity in PD patients off l-DOPA compared to controls. This enhanced connectivity was down-regulated by l-DOPA as shown by an overall decrease in connectivity strength, particularly within motor cortical regions. We also performed a frequency content analysis of the BOLD signal time course extracted from the six striatal seed regions. PD off l-DOPA exhibited increased power in the frequency band 0.02–0.05 Hz compared to controls and to PD on l-DOPA. The l-DOPA associated decrease in the power of this frequency range modulated the l-DOPA associated decrease in connectivity strength between striatal seeds and the thalamus. In addition, the l-DOPA associated decrease in power in this frequency band correlated with the l-DOPA associated improvement in cognitive performance. Our results demonstrate that PD and l-DOPA modulate striatal resting state BOLD signal oscillations and cortico-striatal network coherence

Lifespan Differences in Cortico-Striatal Resting State Connectivity

Distinctive cortico-striatal circuits that serve motor and cognitive functions have been recently mapped based on resting state connectivity. It has been reported that age differences in cortico-striatal connectivity relate to cognitive declines in aging. Moreover, children in their early teens (i.e., youth) already show mature motor network patterns while their cognitive networks are still developing. In the current study, we examined age differences in the frontal-striatal ?cognitive? and ?motor? circuits in children and adolescence, young adults (YAs), and older adults (OAs). We predicted that the strength of the ?cognitive? frontal-striatal circuits would follow an inverted ?U? pattern across age; children and OAs would have weaker connectivity than YAs. However, we predicted that the ?motor? circuits would show less variation in connectivity strength across the lifespan. We found that most areas in both the ?cognitive? and ?motor? circuits showed higher connectivity in YAs than children and OAs, suggesting general inverted ?U?-shaped changes across the lifespan for both the cognitive and motor frontal-striatal networks.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140317/1/brain.2013.0155.pd