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Title: Three-Dimensional Co-Culture Systems for Vascularization of Cardiac Tissue
Creator: Rodriguez Arias, Jessica A.
Date: 2023
Description: Myocardial Infarction (MI) is the partial or complete blockage of blood flow to the myocardial tissue resulting in damage and therefore loss...
Show moreMyocardial Infarction (MI) is the partial or complete blockage of blood flow to the myocardial tissue resulting in damage and therefore loss of heart function. In the U.S. every 40 seconds, someone will suffer from MI and the only available treatment is medication to treat the symptoms of heart function loss, but do not treat the underlying cause. Some attempts to treat the underlying cause have arisen in the last decades including cell-based therapies or tissue engineering therapies such as spheroid-based cardiac patches that have shown to be promising. Improvement in the mechanical properties to create suturable engineered tissues remain to be improved for ease of implantation purposes. Cell-laden hydrogel scaffolds can provide improved mechanical properties compared to biomaterial free cell-based therapies but need to allow for vascularization of the engineered tissue. Thus, the goal of this thesis is to provide preliminary studies for the use of a cell adhesive, proteolytically degradable PEG hydrogel scaffold that eventually would be used as an invitro model to evaluate engineered tissue vascularization for cardiac tissue engineering. To construct this model, important cell spheroid parameters on vascular invasion in 3D culture were investigated including the total number of cells/spheroid, the supporting cell for endothelial cells. In order to scale-up scaffolds to size of clinically relevant dimensions, a multilayered hydrogel construct visible light free-radical polymerization approach encapsulating vascular spheroids in multiple layers was also investigated. Results indicate that a total cell number of 5000 cells/spheroid aggregate were feasible due to cell sourcing. In addition, co-cultures of endothelial and mesenchymal stem cells led to maximized vascular invasion of the spheroids compared to fibroblast/endothelial co-culture and endothelial monoculture of spheroids in the hydrogel. Finally, the extent of vascularization of spheroids in each layer of the multilayered hydrogel constructs varied due to the observed differences in mechanical properties and swelling ratio of each layer due to incomplete polymerization of layers. This study demonstrated the importance of support cells and hydrogel mechanical properties in promoting vascularization of spheroid which serves as basis for building cell-laden hydrogel scaffolds for vascularization for cardiac tissues.
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Title: Population Dynamics of Listeria monocytogenes in Nut, Seed and Legume Butters
Creator: Zhang, Xinyuan
Date: 2020
Description: Nut, seed, and legume butters are low water activity foods and do not support the growth of foodborne pathogens. Research has determined that...
Show moreNut, seed, and legume butters are low water activity foods and do not support the growth of foodborne pathogens. Research has determined that some pathogens, such as Listeria monocytogenes, can survive for long periods of time in butters, such as almond butter. However, information on the persistence of L. monocytogenes in butters is lacking. The purpose of this study was to determine the population dynamics of L. monocytogenes in butters stored at 5 and 25°C. Nut (almond, hazelnut, pecan), seed (pumpkin, sesame, sunflower), legume (peanut and soy) and butters containing chocolate (hazelnut and peanut) were inoculated with a 4-strain cocktail of rifampicin-resistant L. monocytogenes at 4 (high inoculation) or 1 log CFU/g (low inoculation). High inoculation butters were mixed by hand for 15 min and 100-g portions were weighed into deli-style containers with lids and stored at 5 or 25°C for 12 mo (370 d). Low inoculation butters were stored in 25- g portions in stomacher bags at 25°C for 6 mo (180 d). During storage, 25 g from the 100- g high inoculation portion or 25 g from the low inoculation samples, in triplicate, were homogenized with 225 mL BPB (or BLEB for FDA BAM enrichments when necessary) and serial dilutions of the homogenate were plated onto BHIA with rifampicin for enumeration of L. monocytogenes. Data were statistically analyzed using Student’s t-test (α=0.05). The average initial population of L. monocytogenes in the butters was 3.58±0.25 log CFU/g for the high inoculation butters; L. monocytogenes was detected through enrichments for all low inoculation butters. After 12 mo storage at 5°C, the population of L. monocytogenes decreased by 1.34, 1.27, 1.72, 2.04 and 0.93 log CFU/g in almond, hazelnut, peanut with chocolate, hazelnut with chocolate and pecan butter, respectively, when inoculated at the higher level. Significantly less population reduction was observed in pumpkin, sesame, soy, peanut and sunflower butters (1.08, 0.61, 0.84, 0.05 and 0.40 log CFU/g, respectively). After 12 mo storage at 25°C, the L. monocytogenes population in all butters, with the exception of sunflower butter, decreased to below the limit of enumeration (1.67 log CFU/g), but the pathogen was still present via enrichment. For low inoculation butters, L. monocytogenes was present as determined by enrichment in all butters in at least one of two trials after 6 mo. The results of this study provide information on the survival of L. monocytogenes in different butter types when stored at different temperatures.
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Title: Intraoperative Assessment of Surgical Margins in Head And Neck Cancer Resection Using Time-Domain Fluorescence Imaging
Creator: Cleary, Brandon M.
Date: 2023
Description: Rapid and accurate determination of surgical margin depth in fluorescence guided surgery has been a difficult issue to overcome, leading to...
Show moreRapid and accurate determination of surgical margin depth in fluorescence guided surgery has been a difficult issue to overcome, leading to over- or under-resection of cancerous tissues and follow-up treatments such as ‘call-back’ surgery and chemotherapy. Current techniques utilizing direct measurement of tumor margins in frozen section pathology are slow, which can prevent surgeons from acting on information before a patient is sent home. Other fluorescence techniques require the measurement of margins via captured images that are overlayed with fluorescent data. This method is flawed, as measuring depth from captured images loses spatial information. Intensity-based fluorescence techniques utilizing tumor-to-background ratios do not decouple the effects of concentration from the depth information acquired. Thus, it is necessary to perform an objective measurement to determine depths of surgical margins. This thesis focuses on the theory, device design, simulation development, and overall viability of time-domain fluorescence imaging as an alternative method of determining surgical margin depths. Characteristic regressions were generated using a thresholding method on acquired time-domain fluorescence signals, which were used to convert time-domain data to a depth value. These were applied to an image space to generate a depth map of a modelled tissue sample. All modeling was performed on homogeneous media using Monte Carlo simulations, providing high accuracy at the cost of increased computational time. In practice, the imaging process should be completed within a span of under 20 minutes for a full tissue sample, rather than 20 minutes for a single slice of the sample. This thesis also explores the effects of different thresholding levels on the accuracy of depth determination, as well as the precautions to be taken regarding hardware limitations and signal noise.
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Title: Improving Niobium Superconducting Radio-Frequency Cavities by Studying Tantalum
Creator: Helfrich, Halle
Date: 2023
Description: Niobium superconducting radio-frequency (SRF) cavities are widely used accelerating structures. Improvements in both quality factor, Q0, and...
Show moreNiobium superconducting radio-frequency (SRF) cavities are widely used accelerating structures. Improvements in both quality factor, Q0, and maximum accelerating gradient, Eacc, have been made to SRF cavities by introducing new processing techniques. These breakthroughs include processes such as nitrogen doping(N-Doping) and infusion, electrochemical polishing (EP) and High Pressure Rinsing (HPR). [1] There is still abundant opportunity to improve the cavities or, rather, the material they’re primarily composed of: niobium. A focus here is the role the native oxide of Nb plays in SRF cavity performance. The values of interest in a given cavity are its quality factor Q0, maximum accelerating gradient Eacc and surface resistance Rs . This work characterizes Nb and Ta foils prepared under identical conditions using X-ray photoelectron spectroscopy (XPS) to compare surface oxides and better understand RF loss mechanisms in Nb SRF cavities and qubits. It is well established that Ta qubits experience much longer coherence times than Nb qubits, which is probably due to the larger RF losses in Nb oxide. By studying Tantalum, an element similar to Niobium, the mechanisms of the losses that originate in the oxide and suboxide layers present on the surface of Nb cavities might finally be unlocked. We find noticeable differences in the oxides of Nb and Ta formed by air exposure of clean foils. In particular, Ta does not display the TaO2 suboxide in XPS, while Nb commonly shows NbO2. This suggests that suboxides are an additional contributor of RF losses. We also suggest that thin Ta film coatings of Nb SRF cavities may be a way of increasing Q0. It is in the interest of the accelerator community to fully understand the surface impurities present in Nb SRF cavities so that strategies for mitigating the effects can be proposed.
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Title: Independence and Graphical Models for Fitting Real Data
Creator: Cho, Jason Y.
Date: 2023
Description: Given some real life dataset where the attributes of the dataset take on categorical values, with corresponding r(1) × r(2) × … × r(m)...
Show moreGiven some real life dataset where the attributes of the dataset take on categorical values, with corresponding r(1) × r(2) × … × r(m) contingency table with nonzero rows or nonzero columns, we will be testing the goodness-of-fit of various independence models to the dataset using a variation of Metropolis-Hastings that uses Markov bases as a tool to get a Monte Carlo estimate of the p-value. This variation of Metropolis-Hastings can be found in Algorithm 3.1.1. Next we will consider the problem: ``out of all possible undirected graphical models each associated to some graph with m vertices that we test to fit on our dataset, which one best fits the dataset?" Here, the m attributes are labeled as vertices for the graph. We would have to conduct 2^(mC2) goodness-of-fit tests since there are 2^(mC2) possible undirected graphs on m vertices. Instead, we consider a backwards selection method likelihood-ratio test algorithm. We first start with the complete graph G = K(m), and call the corresponding undirected graphical model ℳ(G) as the parent model. Then for each edge e in E(G), we repeatedly apply the likelihood-ratio test to test the relative fit of the model ℳ(G-e), the child model, vs. ℳ(G), the parent model, where ℳ(G-e) ⊆ℳ(G). More details on this iterative process can be found in Algorithm 4.1.3. For our dataset, we will be using the alcohol dataset found in https://www.kaggle.com/datasets/sooyoungher/smoking-drinking-dataset, where the four attributes of the dataset we will use are ``Gender" (male, female), ``Age", ``Total cholesterol (mg/dL)", and ``Drinks alcohol or not?". After testing the goodness-of-fit of three independence models corresponding to the independence statements ``Gender vs Drink or not?", ``Age vs Drink or not?", and "Total cholesterol vs Drink or not?", we found that the data came from a distribution from the two independence models corresponding to``Age vs Drink or not?" and "Total cholesterol vs Drink or not?" And after applying the backwards selection likelihood-ratio method on the alcohol dataset, we found that the data came from a distribution from the undirected graphical model associated to the complete graph minus the edge {``Total cholesterol”, ``Drink or not?”}.
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Title: Development of a Model To Investigate Inflammation Using Peripheral Blood Mononucleated Cells
Creator: Geevarghese Alex, Peter
Date: 2023
Description: Our modern culture in our society is facing one of the biggest risks in health which is high-calorie diet-related postprandial inflammation....
Show moreOur modern culture in our society is facing one of the biggest risks in health which is high-calorie diet-related postprandial inflammation. Chronic diseases may be caused if the energy-dense food is the choice meaning if it is uncontrolled, clinical studies have demonstrated this with the body's post-meal inflammatory response. We aimed to find the causes of postprandial inflammation in response to various dietary treatments and provide a model to demonstrate. We aimed to make use of in vivo and in vitro techniques and statistics to create a model. The created model would help us to design specific treatments to minimize inflammation with response to dietary. In addition to figuring out vital dietary additives, the model additionally facilitates the layout of individualized interventions to reduce inflammation, thereby improving long-time period health outcomes. We aim to understand the clinical observations of diet-induced postprandial inflammation on the molecular level. We desire to make contributions to reduce the impact of chronic inflammatory disorders that is associated with postprandial inflammation.
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Title: Large Language Model Based Machine Learning Techniques for Fake News Detection
Creator: Chen, Pin-Chien
Date: 2024
Description: With advanced technology, it’s widely recognized that everyone owns one or more personal devices. Consequently, people are evolving into...
Show moreWith advanced technology, it’s widely recognized that everyone owns one or more personal devices. Consequently, people are evolving into content creators on social media or the streaming platforms sharing their personal ideas regardless of their education or expertise level. Distinguishing fake news is becoming increasingly crucial. However, the recent research only presents comparisons of detecting fake news between one or more models across different datasets. In this work, we applied Natural Language Processing (NLP) techniques with Naïve Bayes and DistilBERT machine learning method combing and augmenting four datasets. The results show that the balanced accuracy is higher than the average in the recent studies. This suggests that our approach holds for improving fake news detection in the era of widespread content creation.
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Title: Migration of Silver from Silver Zeolite/Low-Density Polyethylene Films into Food Stimulants
Creator: Sayeed, Maryam
Date: 2023
Description: Zeolites are naturally occurring or synthetic crystalline microporous aluminosilicate structures with remarkable catalytic, adsorption, and...
Show moreZeolites are naturally occurring or synthetic crystalline microporous aluminosilicate structures with remarkable catalytic, adsorption, and ion-exchange properties. Their unique framework of pores, channels, and cages with precise dimensions makes them an excellent fit for ion exchange and storage. Silver-exchanged zeolite (Ag/Y) composites may be incorporated into polymer matrices to create antimicrobial packaging materials. The slow release of Ag from nanosilver-enabled polymer nanocomposites (PNCs) may inhibit the growth of bacteria and other pathogens on the film’s surface, improving food quality and reducing food waste. However, the migration of Ag ions from the film into food matrices is of great concern as it could expose humans to high concentrations of a heavy metal from dietary sources. The amount of migration depends on various factors, including the potential form of Ag and its concentration in the film, the film thickness, and the storage conditions.The primary objective of this study is to investigate the effect of the form of Ag bound to the zeolite on the migration behavior of Ag from Ag/Y incorporated low-density polyethylene (LDPE) films. For Ag/Y-incorporated LDPE PNCs with distinct Ag species, the Ag migration into the water and Squirt (a commercial soft drink) was at least four times higher from films containing zeolites exchanged with ionic Ag versus zeolites exchanged with nanoparticulate Ag. Similarly, migration into 9 wt % aqueous Domino sugar (granulated sucrose) solution was seven times higher in the ionic silver-incorporated film than in the nanoparticulate Ag film. This study suggests that it is important to consider the form of Ag in silver-exchanged zeolite while producing packaging materials since the potential form of Ag in the PNCs might significantly affect Ag migration behavior.
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Title: Evaluating Speech Separation Through Pre-Trained Deep Neural Network Models
Creator: Prabhakar, Deeksha
Date: 2023
Description: Speaker separation involves separating individual speakers from a mixture of voices or background noise, known as the "cocktail party problem....
Show moreSpeaker separation involves separating individual speakers from a mixture of voices or background noise, known as the "cocktail party problem." This refers to the ability to focus on a specific sound while filtering out other distractions.In this analysis, we propose the idea of obtaining features present in the original data and then evaluating the impact they have on the ability of the model to separate the mixed audio streams. The dataset is prepared such that these feature values can be used as predictor variables to various models like Logistic Regression, Decision Trees, SVM (both rbf and linear kernel), XGBoost, AdaBoost, to obtain the most contributing features that is the features that will lead to a better separation. These results shall then be analyzed to conclude the features that affect separating the audio streams the most. Initially, 400 audio streams are selected from the VoxCeleb dataset and combined to form 200 single utterances. After the mixes are obtained, the pre-trained Speechbrain model, sepformer-whamr is used. This model separates the audio mixes given as input and obtain two outputs that should be as close as possible to the original ones. A feature list from the 400 chosen audios is obtained and then the effect of certain features on the model's capability to distinguish between multiple audio sources in a mixed recording is assessed. Two analysis parameters- permutation feature importance and SHAP values are used to conclude which features have more effect on separation. Our hypothesis is that the features contributing the most to a good separation are invariant across datasets. To test this hypothesis, we obtain 1,000 audio streams from the Mozilla Common Voice Dataset and perform the same experimental methodology described above. Our results demonstrate that the features we extract from VoxCeleb dataset are indeed invariant and aid in separating the audio streams of the Mozilla Common Voice dataset.
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Title: Improving self-supervised monocular depth estimation from videos using forward and backward consistency
Creator: Shen, Hui
Date: 2020
Description: Recently, there has been a rapid development in monocular depth estimation based on self-supervised learning. However, these existing self...
Show moreRecently, there has been a rapid development in monocular depth estimation based on self-supervised learning. However, these existing self-supervised learning methods are insufficient for estimating motion objects, occlusions, and large static areas. Uncertainty or vanishing easily occurs during depth inferencing. To address this problem, the model proposed in this thesis further explores the consistency in video and builds a multi-frame model for depth estimation; secondly, by taking advantage of the optical flow, a motion mask is generated, with additional photometric loss applied for those masked regions. Experiments are carried out on the KITTI dataset. The proposed model performs better than the baseline model in quantitative results, and as seen from the depth map, the scale uncertainty and depth incomplete situations are improved in motion objects and occlusions explicitly.
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Title: Factor Analysis of the Neurobehavioral Symptom Inventory in Veterans with Posttraumatic Stress Disorder
Creator: Scimeca, Lauren
Date: 2020
Description: The Neurobehavioral Symptom Inventory (NSI) is a widely used measure of postconcussive symptoms in veteran populations. Previous psychometric...
Show moreThe Neurobehavioral Symptom Inventory (NSI) is a widely used measure of postconcussive symptoms in veteran populations. Previous psychometric studies used samples of veterans with mild Traumatic Brain Injury (mTBI) and high rates of comorbid Posttraumatic Stress Disorder (PTSD). The present study aims to determine the best-fitting factor structure of the NSI in veterans with PTSD and to evaluate the relationship between the best-fitting factor structure and the symptom clusters of PTSD. A confirmatory factor analysis (CFA) found that 4-factors had the best overall fit in veterans with PTSD. Correlational analyses found high rates of correspondence between the cognitive and affective factors of the NSI and the alterations in cognition and mood and hyperarousal symptom clusters of PTSD. The analyses reveal that symptoms of the NSI cluster in the same way in a sample of veterans with PTSD as they do in veterans with mTBI, suggesting that lingering postconcussive symptoms in veterans with PTSD are better characterized as non-specific generalized health symptoms on the NSI.
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Title: CONCEPTUAL COST ESTIMATION MODEL FOR BRIDGES WITH RESPECT TO ABC METHODS
Creator: Rajeei, Farshad
Date: 2020
Description: As the need for renovating and repairing structurally deficient and functionally obsolete bridges is increased, employing innovative methods...
Show moreAs the need for renovating and repairing structurally deficient and functionally obsolete bridges is increased, employing innovative methods which can lead to shorter construction time, better quality, longer durability, and less life-cycle costs become more popular in transportation agencies.Developing a model that has the capability of estimating the total construction cost of ABC projects and compare them with conventional methods costs [without using these methods] will help decision-makers at DOTs in understanding and assessing the benefits and costs of ABC methods at the planning phase of a project and in return, will lead to the elaboration in the use of ABC methods versus the conventional ones. But this decision making process is complicated since the number of executed ABC projects, especially those which done by SIBC and SPMT [two superstructure replacement method] is limited and as a result; there is a lack of historical knowledge to estimate the associated cost of these methods in future projects. Factors affecting this process include but are not limited to: construction costs, user costs, quality of work, impact on traffic, the safety of road users and construction workers, and the impact on surrounding communities and businesses. The main aim of this study is to make a model to estimate additional costs of using SIBC and SPMT methods and the saving in user costs.
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Title: PTSD Symptoms as a Potential Link Between Military Sexual Assault and Disordered Eating
Creator: Sandhu, Danielle
Date: 2020
Description: Despite increasing rates of sexual assault in the military and high rates of disordered eating and posttraumatic stress disorder (PTSD) among...
Show moreDespite increasing rates of sexual assault in the military and high rates of disordered eating and posttraumatic stress disorder (PTSD) among veterans, little is known about how these constructs are related. The present study examined whether PTSD symptoms mediate the relation between military sexual assault and disordered eating among female veterans. Prolific Academic was used to recruit 98 United States female veterans as participants for the study. Participants completed an online questionnaire of self-report measures assessing demographic characteristics, military sexual assault, PTSD symptoms, and disordered eating. Mediational analyses were conducted using the PROCESS v3 macro in IBM SPSS Statistics. Within the sample, 61% of female veterans reported being sexually assaulted while serving in the military. Military sexual assault was associated with higher levels of PTSD symptoms and disordered eating. Findings did not support the hypothesis that PTSD symptoms would mediate the relation between military sexual assault and disordered eating among women veterans. Given the heterogeneous nature of disordered eating, post-hoc mediational analyses were conducted to examine specific facets of eating pathology. Results indicated that PTSD symptoms fully mediated the relation between military sexual assault and bulimia and food preoccupation. Awareness of these psychopathological sequelae following military sexual assault may improve screening and intervention efforts at Veteran Affairs (VA) medical centers. The present study highlights the importance of future longitudinal studies that can establish temporal precedence in order to better understand the pathways leading to disordered eating in female veterans.
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Title: GROWTH KINETICS OF SALMONELLA ENTERICA DURING REHYDRATION OF DEHYDRATED PLANT FOODS AND SUBSEQUENT STORAGE
Creator: Ren, Yuying
Date: 2020
Description: Dehydrated plant foods have low water activities and do not support the growth of pathogenic bacteria like Salmonella enterica. Once...
Show moreDehydrated plant foods have low water activities and do not support the growth of pathogenic bacteria like Salmonella enterica. Once rehydration, the water activities will increase to > 0.92, and along with their neutral pHs, plant foods may be able to support the growth of S. enterica. Therefore, product assessments are required to determine the extent to which these products support growth of S. enterica. The purpose of this study was to determine the growth kinetics of S. enterica during rehydration with 5 or 25 °C water, and subsequent storage of dehydrated potatoes, carrots, and onions at 5, 10, and 25 °C. Fresh plant foods were dehydrated at 60°C (140°F) for 24 h. Dehydrated plant foods were inoculated with 4 log CFU/g of a 4-strain cocktail of S. enterica and dried for 24 h. Samples were rehydrated using 4-volumes of 5 or 25 °C water for 24 h. During rehydration, 30 g of sample was removed and drained for 10 min. Ninety mL of BPB was added to triplicate 10-g samples. Serial dilutions of the homogenate were plated onto TSA overlaid with XLD agar for enumeration of S. enterica. After 24 h rehydration, the remaining samples were drained and stored in containers at 5, 10, and 25°C for 7 d. S. enterica was enumerated at 1, 3, 5, and 7 d. Three independent trials were conducted. Growth kinetics were determined using DMFit and data were statistically analyzed using Student’s t-test (α=0.05). Overall, the growth rates of S. enterica when 5 °C water was used for rehydration were higher than when 25 °C water was used for potatoes and carrots. The highest growth rate of S. enterica was 3.74 log CFU/g per d on potatoes, leading to a 1 log CFU/g increase in S. enterica after only 0.27 d (16 h) which occurred during storage at 25 ℃ after 5℃ water rehydration. The highest growth rate on carrots was 1.98 log CFU/g per d (requiring only 0.51 d to increase 1 log CFU/g) when rehydrated with 5℃ water and stored at 25 ℃. The growth rates were the lowest during the storage of rehydrated onions. S. enterica required 12.5 d to increase 1 log CFU/g (the growth rate was 0.61 log CFU/g per d) when the onions were rehydrated with 25 ℃ water and stored at 25 ℃. The results of this study determined that S. enterica could survive and grow in dehydrated plant foods during rehydration and storage, highlighting the need for product assessments for these types of foods.
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Title: Analysis of High-Fidelity Experiments and Simulations of the Flow in Simplified Urban Environments
Creator: Stuck, Maxime
Date: 2020
Description: The mean ﬂow and turbulence statistics of the ﬂow through a simpliﬁed urban environment, which is an active research area in order to improve...
Show moreThe mean ﬂow and turbulence statistics of the ﬂow through a simpliﬁed urban environment, which is an active research area in order to improve the knowledge of turbulent ﬂow in cities, is investigated. This is useful for civil engineering, pedestrian comfort and for health concerns caused by pollutant spreading. In this work, we provide analysis of the turbulence statistics obtained both from highly-quality stereoscopic particle image-velocimetry (SPIV) measurements (from Monnier et al.) and well-resolved large eddy simulations (LES) by Torres et al. A detailed comparison of both databases reveals the impact of the geometry of the urban array on the ﬂow characteristics and provides for a good description of the turbulent features of the ﬂow around a simpliﬁed urban environment. The most prominent features of this complex ﬂow include coherent vortical structures such as the so-called arch vortex, the horseshoe vortex, or the roof vortex. These structures of the ﬂow have been identiﬁed by an analysis of the turbulence statistics. The inﬂuence of the geometry of the urban environment (and particularly the street width and the building height) on the overall ﬂow behavior has also been studied.
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Title: Retrospective Quantitative T1 Imaging to Examine Characteristics of Multiple Sclerosis Lesions
Creator: Young, Griffin James
Date: 2024
Description: Quantitative MRI plays an essential role in assessing tissue abnormality and diseaseprogression in multiple sclerosis (MS). Specifically, T1...
Show moreQuantitative MRI plays an essential role in assessing tissue abnormality and diseaseprogression in multiple sclerosis (MS). Specifically, T1 relaxometry is gaining popularity as elevated T1 values have been shown to correlate with increased inflammation, demyelination, and gliosis. The predominant issue is that relaxometry requires parametric mapping through advanced imaging techniques not commonly included in standard clinical protocols. This leaves an information gap in large clinical datasets from which quantitative mapping could have been performed. We introduce T1-REQUIRE, a retrospective T1 mapping method that approximates T1 values from a single T1-weighted MR image. This method has already been shown to be accurate within 10% of a clinically available reference standard in healthy controls but will be further validated in MS cohorts. We also further aim to determine T1-REQUIRE’s statistical significance as a unique biomarker for the assessment of MS lesions as they relate to clinical disability and disease burden. A 14-subject comparison between T1-REQUIRE maps derived from 3D T1 weighted turbo field echoes (3D T1w TFE) and an inversion-recovery fast field echo (IRFFE) revealed a whole-brain voxel-wise Pearson’s correlation of r = 0.89 (p < 0.001) and mean bias of 3.99%. In MS white matter lesions, r = 0.81, R2 = 0.65 (p < 0.001, N = 159), bias = 10.07%, and in normal appearing white matter (NAWM), r = 0.82, R 2 = 0.67 (p < 0.001), bias = 9.48%. Mean lesional T1-REQUIRE and MTR correlated significantly (r = -0.68, p < 0.001, N = 587) similar to previously published literature. Median lesional MTR correlated significantly with EDSS (rho = -0.34, p = 0.037), and lesional T1-REQUIRE exhibited xiii significant correlations with global brain tissue atrophy as measured by brain parenchymal fraction (BPF) (r = -0.41, p = 0.010, N = 38). Multivariate linear regressions between T1- REQUIRE NAWM provided meaningful statistical relationships with EDSS (β = 0.03, p = 0.027, N = 38), as well as did mean MTR values in the Thalamus (β = -0.27, p = 0.037, N = 38). A new spoiled gradient echo variation of T1-REQUIRE was assessed as a proof of concept in a small 5-subject MS cohort compared with IR-FFE T1 maps, with a whole brain voxel-wise correlation of r = 0.88, R2 = 0.77 (p < 0.001), and Bias = 0.19%. Lesional T1 comparisons reached a correlation of r = 0.75, R2 = 0.56 (p < 0.001, N = 42), and Bias = 10.81%. The significance of these findings means that there is the potential to provide supplementary quantitative information in clinical datasets where quantitative protocols were not implemented. Large MS data repositories previously only containing structural T1 weighted images now may be used in big data relaxometric studies with the potential to lead to new findings in newly uncovered datasets. Furthermore, T1-REQUIRE has the potential for immediate use in clinics where standard T1 mapping sequences aren’t able to be readily implemented.
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Title: Utilizing Image Processing in Evaluation of Fibroblast Stimulation for Collagen Remodeling
Creator: Yoon, Shin Hae
Date: 2023
Description: This research delves into the realm of image processing as a pivotal component in the evaluation of fibroblast stimulation for collagen...
Show moreThis research delves into the realm of image processing as a pivotal component in the evaluation of fibroblast stimulation for collagen remodeling. The study focuses on unraveling the intricate synergy between electrospun silk fibroin-carbon nanotube (SF-CNT) fibers and electrical stimulation, working in harmony to enhance tissue regeneration. Building upon our previous work, we successfully engineered SF-CNT fibers through the electrospinning process, yielding highly aligned structures reminiscent of natural extracellular matrix proteins. These fibers were fortified with water stability through post-treatment with ethanol vapor, while subtle additions of carbon nanotubes (CNTs) significantly improved fiber alignment, strength, and conductivity without compromising biocompatibility. This innovative platform served as a cell culture matrix for fibroblasts harvested from pelvic organ prolapse (POP) patients, facilitating electrical stimulation that triggered a substantial increase in collagen production. In this study, we harnessed the power of various image-processing software tools, including ImageJ and Python, to analyze immunostained images of fibroblasts obtained from POP patients. Under carefully tailored electrical stimulation conditions, the stimulated cells exhibited an astonishing up to 11.97-fold increase in alpha-smooth muscle actin (α-SMA) expression, unequivocally signifying the successful activation of myofibroblasts. Additionally, in an animal model employing LOX-knockout mice to mimic collagen disorders associated with POP, the application of optimized electrical stimulation conditions for patient 003 led to a remarkable surge in collagen production and structural enhancement, underlining the potential of electrical stimulation in expediting tissue remodeling. Intriguingly, fibroblasts from patient 005 and patient 006 exhibited a distinct response, shedding light on the influence of POP severity on cellular behavior. This study firmly reinforces the imperative of personalized therapeutic approaches, emphasizing the need to customize treatment strategies to align with individual patient characteristics through innovative biological image analysis techniques.
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Title: Effect of organic acid treatment in reducing Salmonella on six types of sprout seeds
Creator: Yang, Dachuan
Date: 2023
Description: Fresh sprouts present a special food safety concern as their growing conditions also favor the growth of pathogens such as Salmonella....
Show moreFresh sprouts present a special food safety concern as their growing conditions also favor the growth of pathogens such as Salmonella. Contamination in sprouts often originates from the seeds used for sprouting. The Produce Safety Rule requires that seeds used to grow sprouts be treated to reduce pathogens. The treatments may be applied by sprout growers or by seed suppliers. Although 20,000 ppm calcium hypochlorite is the most used seed treatment method, the high chlorine level can be hazardous to workers and the environment. Alternative seed treatment methods that are safe and environmentally friendly are needed. In addition, a post-treatment drying step is needed when seed suppliers are using chemical seed treatment methods. This study evaluated the efficacy of an organic acid solution for reducing Salmonella on six types of seeds (alfalfa, clover, radish, mung bean, onion, and broccoli). The impact of treatment on seed germination and sprout yield was also examined. Ten grams of seeds inoculated with a five-serotype cocktail of Salmonella were pre-rinsed with 40 ml of water twice and treated with 75.7 ml of the organic acid solution for 1 hour. The treated seeds were either not rinsed or rinsed with 40 ml of water twice before being dried in the biological safety cabinet for 24 hours. The Salmonella level, germination percentage, and sprout yield of seeds treated with water, seeds treated with the organic acid solution, seeds treated with organic acid, dried, and rinsed, and seeds treated with organic acids, dried, and not rinsed were compared. Salmonella reductions that could be achieved with this organic acid solution treatment were less than 0.5 log CFU/g without drying, 0.6-2.0 log CFU/g with drying and rinse, or 1.6-2.9 log CFU/g with drying and no rinse. Drying significantly enhanced the treatment efficacy (p < 0.05 ) on alfalfa, radish, mung bean, and onion seeds. If seeds were not rinsed after treatment, the log reductions achieved on mung bean and onion seeds were significantly higher (p < 0.05). If seeds were treated and rinsed, the germination rates of six types of seeds were not affected (p > 0.05) regardless of whether the seeds were dried or not. All treatments significantly decreased the sprout yield of clover seeds by 13% (p < 0.05 ). If seeds were not rinsed after treatment, the germination rates of clover and broccoli seeds were reduced by 7 and 9%, respectively, and the sprout yield of alfalfa seeds was reduced by 35%. Overall, the organic acid solution was ineffective when compared with 20,000 ppm calcium hypochlorite in reducing Salmonella on sprout seeds, although the drying step after treatment could improve the treatment efficacy.
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Title: IMPACT OF DATA SHAPE, FIDELITY, AND INTER-OBSERVER REPRODUCIBILITY ON CARDIAC MAGNETIC RESONANCE IMAGE PIPELINES
Creator: Obioma, Blessing Ngozi
Date: 2020
Description: Artificial Intelligence (AI) holds a great promise in the healthcare. It provides a variety of advantages with its application in clinical...
Show moreArtificial Intelligence (AI) holds a great promise in the healthcare. It provides a variety of advantages with its application in clinical diagnosis, disease prediction, and treatment, with such interests intensifying in the medical image field. AI can automate various cumbersome data processing techniques in medical imaging such as segmentation of left ventricular chambers and image-based classification of diseases. However, full clinical implementation and adaptation of emerging AI-based tools face challenges due to the inherently opaque nature of such AI algorithms based on Deep Neural Networks (DNN), for which computer-trained bias is not only difficult to detect by physician users but is also difficult to safely design in software development. In this work, we examine AI application in Cardiac Magnetic Resonance (CMR) using an automated image classification task, and thereby propose an AI quality control framework design that differentially evaluates the black-box DNN via carefully prepared input data with shape and fidelity variations to probe system responses to these variations. Two variants of the Visual Geometric Graphics with 19 neural layers (VGG19) was used for classification, with a total of 60,000 CMR images. Findings from this work provides insights on the importance of quality training data preparation and demonstrates the importance of data shape variability. It also provides gateway for computation performance optimization in training and validation time.
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Title: LOW-COVERAGE GENOMES AS AN EFFECTIVE AND ECONOMICAL APPROACH FOR LEPIDOPTERAN MICROSATELLITE ISOLATION
Creator: Liang, Huijia
Date: 2020
Description: This study aimed to verify that whether a low-coverage genome can work as an effective approach to isolate Lepidopteran microsatellites. As...
Show moreThis study aimed to verify that whether a low-coverage genome can work as an effective approach to isolate Lepidopteran microsatellites. As microsatellites are useful tool to study population genetics, and there are many Lepidopteran agriculture pests which can cause huge economic damages every year, additionally, Lepidoptera have abundant similar flanking sequences making it difficult to develop reliable microsatellites. However, there are not enough published genomes of Lepidoptera species. If low-coverage Lepidopteran genomes can be used to isolate reliable microsatellites, the low-coverage genomes would be an effective and economical approach for microsatellites isolation, because low-coverage genome sequencing is much cheaper and less time-consuming than the published genome sequencing.
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