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623 results on '"Casey, Michael"'

1. Medical and Surgical Management of the Failed Pancreas Transplant

Author

Casey, Michael J, Murakami, Naoka, Ong, Song, Adler, Joel T, Singh, Neeraj, Murad, Haris, Parajuli, Sandesh, Concepcion, Beatrice P, Lubetzky, Michelle, Pavlakis, Martha, Woodside, Kenneth J, Faravardeh, Arman, Basu, Arpita, Tantisattamo, Ekamol, Aala, Amtul, Gruessner, Angelika, Dadhania, Darshana, Lentine, Krista, Cooper, Matthew, Parsons, Ronald F, and Alhamad, Tarek

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Organ Transplantation, Clinical Research, Transplantation, Good Health and Well Being, Cardiovascular medicine and haematology, Clinical sciences, Immunology
Abstract

Despite the continued improvements in pancreas transplant outcomes in recent decades, a subset of recipients experience graft failure and can experience substantial morbidity and mortality. Here, we summarize what is known about the failed pancreas allograft and what factors are important for consideration of retransplantation. The current definition of pancreas allograft failure and its challenges for the transplant community are explored. The impacts of a failed pancreas allograft are presented, including patient survival and resultant morbidities. The signs, symptoms, and medical and surgical management of a failed pancreas allograft are described, whereas the options and consequences of immunosuppression withdrawal are reviewed. Medical and surgical factors necessary for successful retransplant candidacy are detailed with emphasis on how well-selected patients may achieve excellent retransplant outcomes. To achieve substantial medical mitigation and even pancreas retransplantation, patients with a failed pancreas allograft warrant special attention to their residual renal, cardiovascular, and pulmonary function. Future studies of the failed pancreas allograft will require improved reporting of graft failure from transplant centers and continued investigation from experienced centers.

Published
2024

2. Bulk Johnson-Lindenstrauss Lemmas

Author

Casey, Michael P.

Subjects
Mathematics - Probability, Computer Science - Computational Geometry, Computer Science - Information Theory, Mathematics - Metric Geometry, Mathematics - Statistics Theory, 68Q87, 68R12, 60B20 (primary) 62G30, 68T09 (secondary)
Abstract

For a set $X$ of $N$ points in $\mathbb{R}^D$, the Johnson-Lindenstrauss lemma provides random linear maps that approximately preserve all pairwise distances in $X$ -- up to multiplicative error $(1\pm \epsilon)$ with high probability -- using a target dimension of $O(\epsilon^{-2}\log(N))$. Certain known point sets actually require a target dimension this large -- any smaller dimension forces at least one distance to be stretched or compressed too much. What happens to the remaining distances? If we only allow a fraction $\eta$ of the distances to be distorted beyond tolerance $(1\pm \epsilon)$, we show a target dimension of $O(\epsilon^{-2}\log(4e/\eta)\log(N)/R)$ is sufficient for the remaining distances. With the stable rank of a matrix $A$ as $\lVert{A\rVert}_F^2/\lVert{A\rVert}^2$, the parameter $R$ is the minimal stable rank over certain $\log(N)$ sized subsets of $X-X$ or their unit normalized versions, involving each point of $X$ exactly once. The linear maps may be taken as random matrices with i.i.d. zero-mean unit-variance sub-gaussian entries. When the data is sampled i.i.d. as a given random vector $\xi$, refined statements are provided; the most improvement happens when $\xi$ or the unit normalized $\widehat{\xi-\xi'}$ is isotropic, with $\xi'$ an independent copy of $\xi$, and includes the case of i.i.d. coordinates., Comment: 29 pages, no figures, the abstract is being presented at the ISI 2023 World Statistics Conference as a contributed abstract: https://www.isi2023.org/conferences/session/556/details/

Published
2023

3. Sequential Transfer Learning to Decode Heard and Imagined Timbre from fMRI Data

Author

Paulsen, Sean and Casey, Michael

Subjects
Quantitative Biology - Quantitative Methods, Computer Science - Machine Learning
Abstract

We present a sequential transfer learning framework for transformers on functional Magnetic Resonance Imaging (fMRI) data and demonstrate its significant benefits for decoding musical timbre. In the first of two phases, we pre-train our stacked-encoder transformer architecture on Next Thought Prediction, a self-supervised task of predicting whether or not one sequence of fMRI data follows another. This phase imparts a general understanding of the temporal and spatial dynamics of neural activity, and can be applied to any fMRI dataset. In the second phase, we fine-tune the pre-trained models and train additional fresh models on the supervised task of predicting whether or not two sequences of fMRI data were recorded while listening to the same musical timbre. The fine-tuned models achieve significantly higher accuracy with shorter training times than the fresh models, demonstrating the efficacy of our framework for facilitating transfer learning on fMRI data. Additionally, our fine-tuning task achieves a level of classification granularity beyond standard methods. This work contributes to the growing literature on transformer architectures for sequential transfer learning on fMRI data, and provides evidence that our framework is an improvement over current methods for decoding timbre., Comment: Under review. arXiv admin note: substantial text overlap with arXiv:2305.09057

Published
2023

4. Self-Supervised Pretraining on Paired Sequences of fMRI Data for Transfer Learning to Brain Decoding Tasks

Author

Paulsen, Sean and Casey, Michael

Subjects
Computer Science - Machine Learning, Quantitative Biology - Neurons and Cognition
Abstract

In this work we introduce a self-supervised pretraining framework for transformers on functional Magnetic Resonance Imaging (fMRI) data. First, we pretrain our architecture on two self-supervised tasks simultaneously to teach the model a general understanding of the temporal and spatial dynamics of human auditory cortex during music listening. Our pretraining results are the first to suggest a synergistic effect of multitask training on fMRI data. Second, we finetune the pretrained models and train additional fresh models on a supervised fMRI classification task. We observe significantly improved accuracy on held-out runs with the finetuned models, which demonstrates the ability of our pretraining tasks to facilitate transfer learning. This work contributes to the growing body of literature on transformer architectures for pretraining and transfer learning with fMRI data, and serves as a proof of concept for our pretraining tasks and multitask pretraining on fMRI data., Comment: Preprint - Accepted to International Conference on Pattern Recognition, Machine Learning and Consciousness 2023

Published
2023

5. Decoding Imagined Auditory Pitch Phenomena with an Autoencoder Based Temporal Convolutional Architecture

Author

Paulsen, Sean, May, Lloyd, and Casey, Michael

Subjects
Quantitative Biology - Neurons and Cognition
Abstract

Stimulus decoding of functional Magnetic Resonance Imaging (fMRI) data with machine learning models has provided new insights about neural representational spaces and task-related dynamics. However, the scarcity of labelled (task-related) fMRI data is a persistent obstacle, resulting in model-underfitting and poor generalization. In this work, we mitigated data poverty by extending a recent pattern-encoding strategy from the visual memory domain to our own domain of auditory pitch tasks, which to our knowledge had not been done. Specifically, extracting preliminary information about participants' neural activation dynamics from the unlabelled fMRI data resulted in improved downstream classifier performance when decoding heard and imagined pitch. Our results demonstrate the benefits of leveraging unlabelled fMRI data against data poverty for decoding pitch based tasks, and yields novel significant evidence for both separate and overlapping pathways of heard and imagined pitch processing, deepening our understanding of auditory cognitive neuroscience., Comment: Awarded Best Paper at BRAININFO2021

Published
2023

7. Unsupervised inter-frame motion correction for whole-body dynamic PET using convolutional long short-term memory in a convolutional neural network

Author

Guo, Xueqi, Zhou, Bo, Pigg, David, Spottiswoode, Bruce, Casey, Michael E., Liu, Chi, and Dvornek, Nicha C.

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Signal Processing, Statistics - Applications
Abstract

Subject motion in whole-body dynamic PET introduces inter-frame mismatch and seriously impacts parametric imaging. Traditional non-rigid registration methods are generally computationally intense and time-consuming. Deep learning approaches are promising in achieving high accuracy with fast speed, but have yet been investigated with consideration for tracer distribution changes or in the whole-body scope. In this work, we developed an unsupervised automatic deep learning-based framework to correct inter-frame body motion. The motion estimation network is a convolutional neural network with a combined convolutional long short-term memory layer, fully utilizing dynamic temporal features and spatial information. Our dataset contains 27 subjects each under a 90-min FDG whole-body dynamic PET scan. With 9-fold cross-validation, compared with both traditional and deep learning baselines, we demonstrated that the proposed network obtained superior performance in enhanced qualitative and quantitative spatial alignment between parametric $K_{i}$ and $V_{b}$ images and in significantly reduced parametric fitting error. We also showed the potential of the proposed motion correction method for impacting downstream analysis of the estimated parametric images, improving the ability to distinguish malignant from benign hypermetabolic regions of interest. Once trained, the motion estimation inference time of our proposed network was around 460 times faster than the conventional registration baseline, showing its potential to be easily applied in clinical settings., Comment: Preprint submitted to Medical Image Analysis

Published
2022
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8. Feasibility of using abbreviated scan protocols with population-based input functions for accurate kinetic modeling of [18F]-FDG datasets from a long axial FOV PET scanner.

Author

Sari, Hasan, Eriksson, Lars, Mingels, Clemens, Alberts, Ian, Casey, Michael, Afshar-Oromieh, Ali, Conti, Maurizio, Cumming, Paul, Shi, Kuangyu, and Rominger, Axel

Subjects
FDG, Kinetic modeling, LAFOV PET, Parametric imaging, Humans, Fluorodeoxyglucose F18, Feasibility Studies, Positron-Emission Tomography, Arteries, Neoplasms
Abstract

BACKGROUND: Accurate kinetic modeling of 18F-fluorodeoxyglucose ([18F]-FDG) positron emission tomography (PET) data requires accurate knowledge of the available tracer concentration in the plasma during the scan time, known as the arterial input function (AIF). The gold standard method to derive the AIF requires collection of serial arterial blood samples, but the introduction of long axial field of view (LAFOV) PET systems enables the use of non-invasive image-derived input functions (IDIFs) from large blood pools such as the aorta without any need for bed movement. However, such protocols require a prolonged dynamic PET acquisition, which is impractical in a busy clinical setting. Population-based input functions (PBIFs) have previously shown potential in accurate Patlak analysis of [18F]-FDG datasets and can enable the use of shortened dynamic imaging protocols. Here, we exploit the high sensitivity and temporal resolution of a LAFOV PET system and explore the use of PBIF with abbreviated protocols in [18F]-FDG total body kinetic modeling. METHODS: Dynamic PET data were acquired in 24 oncological subjects for 65 min following the administration of [18F]-FDG. IDIFs were extracted from the descending thoracic aorta, and a PBIF was generated from 16 datasets. Five different scaled PBIFs (sPBIFs) were generated by scaling the PBIF with the AUC of IDIF curve tails using various portions of image data (35-65, 40-65, 45-65, 50-65, and 55-65 min post-injection). The sPBIFs were compared with the IDIFs using the AUCs and Patlak Ki estimates in tumor lesions and cerebral gray matter. Patlak plot start time (t*) was also varied to evaluate the performance of shorter acquisitions on the accuracy of Patlak Ki estimates. Patlak Ki estimates with IDIF and t* = 35 min were used as reference, and mean bias and precision (standard deviation of bias) were calculated to assess the relative performance of different sPBIFs. A comparison of parametric images generated using IDIF and sPBIFs was also performed. RESULTS: There was no statistically significant difference between AUCs of the IDIF and sPBIFs (Wilcoxon test: P > 0.05). Excellent agreement was shown between Patlak Ki estimates obtained using sPBIF and IDIF. Using the sPBIF55-65 with the Patlak model, 20 min of PET data (i.e., 45 to 65 min post-injection) achieved  0.99 and peak signal-to-noise ratio > 55 dB. CONCLUSION: We demonstrate the feasibility of performing accurate [18F]-FDG Patlak analysis using sPBIFs with only 20 min of PET data from a LAFOV PET scanner.

Published
2023

9. The Perspectives of General Nephrologists Toward Transitions of Care and Management of Failing Kidney Transplants

Author

Alhamad, Tarek, Murad, Haris, Dadhania, Darshana M, Pavlakis, Martha, Parajuli, Sandesh, Concepcion, Beatrice P, Singh, Neeraj, Murakami, Naoka, Casey, Michael J, Ji, Mengmeng, Lubetzky, Michelle, Tantisattamo, Ekamol, Alomar, Omar, Faravardeh, Arman, Blosser, Christopher D, Basu, Arpita, Gupta, Gaurav, Adler, Joel T, Adey, Deborah, Woodside, Kenneth J, Ong, Song C, Parsons, Ronald F, and Lentine, Krista L

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Clinical Research, Kidney Disease, Transplantation, Organ Transplantation, Renal and urogenital, Adult, Humans, Nephrologists, Kidney Transplantation, Nephrology, Immunosuppression Therapy, Surveys and Questionnaires, re-transplantation, failing kidney allograft, transition of care, immunosuppression management, multidisciplinary team, Surgery, Clinical sciences
Abstract

The management of failing kidney allograft and transition of care to general nephrologists (GN) remain a complex process. The Kidney Pancreas Community of Practice (KPCOP) Failing Allograft Workgroup designed and distributed a survey to GN between May and September 2021. Participants were invited via mail and email invitations. There were 103 respondents with primarily adult nephrology practices, of whom 41% had an academic affiliation. More than 60% reported listing for a second kidney as the most important concern in caring for patients with a failing allograft, followed by immunosuppression management (46%) and risk of mortality (38%), while resistant anemia was considered less of a concern. For the initial approach to immunosuppression reduction, 60% stop antimetabolites first, and 26% defer to the transplant nephrologist. Communicating with transplant centers about immunosuppression cessation was reported to occur always by 60%, and sometimes by 29%, while 12% reported making the decision independently. Nephrologists with academic appointments communicate with transplant providers more than private nephrologists (74% vs. 49%, p = 0.015). There are heterogeneous approaches to the care of patients with a failing allograft. Efforts to strengthen transitions of care and to develop practical practice guidelines are needed to improve the outcomes of this vulnerable population.

Published
2023

11. Estimating cellular redundancy in networks of genetic expression

Author

Mulas, Raffaella and Casey, Michael J.

Subjects
Quantitative Biology - Molecular Networks, Mathematics - Spectral Theory
Abstract

Networks of genetic expression can be modelled by hypergraphs with the additional structure that real coefficients are given to each vertex-edge incidence. The spectra, i.e. the multiset of the eigenvalues, of such hypergraphs, are known to encode structural information of the data. We show how these spectra can be used, in particular, in order to give an estimation of cellular redundancy, a novel measure of gene expression heterogeneity, of the network. We analyze some simulated and real data sets of gene expression for illustrating the new method proposed here.

Published
2021
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12. FAITH AND FAMILY IMPORTANT TO ROBERT F. KENNEDY'S WIDOW; The Kennedy matriarch, who was one of the last remaining members of a generation that included U.S. president John F. Kennedy, founded a non-profit centre that was dedicated to advancing human rights

Author

Casey, Michael and LeBlanc, Steve

Subjects
Kennedy, Ethel, Human rights workers, General interest, News, opinion and commentary
Abstract

Byline: MICHAEL CASEY, STEVE LEBLANC; ASSOCIATED PRESS BOSTON -- E thel Kennedy, the widow of Robert F. Kennedy who raised their 11 children after he was assassinated and remained dedicated [...]

Published
2024

13. An information-theoretic definition of cell type

Author

Casey, Michael John and Macarthur, Benjamin

Abstract

Individual cells are often classified into cell 'types' based on the expression of so-called marker genes. Such marker-based classification assumes that cells of a given type are (at least approximately) interchangeable with respect to the expression of their associated markers. This traditional approach to cellular classification has been disrupted by single-cell RNA-sequencing technologies, which are able to measure genome-wide gene expression across thousands of individual cells. While potentially providing a wealth of data for cellular classification, these technologies have revealed that cells ostensibly of the same type are often highly heterogeneous (i.e. not interchangeable) with respect to the expression of established marker genes. A myriad of single-cell clustering methods has recently been developed to overcome the issue of heterogeneity with respect to marker gene expression and identify cell types directly from single-cell expression data. These methods typically proceed via: (1) unsupervised identification of clusters from single-cell expression data sets; (2) mapping of identified clusters to known cell types based on the expression of previously established marker genes. However, this two-step cluster-based approach to cellular classification is less biologically intuitive than the traditional marker-based approach, involving substantial mathematical and biological assumptions regarding the nature of cell type. In this thesis, I formalise the traditional marker gene approach to cellular classification using notions from information theory, and show how this formalism can be applied to identifying cell types from single-cell RNA-sequencing data. Specifically, I develop a novel clustering method based on the assumption that cells of the same type should be minimally heterogeneous - i.e. approximately interchangeable - with respect to the measured expression of a set of genes. Thus, this work offers an intuitive, formal definition of cell type that unites the traditional and current approaches to cellular classification through the mathematics of information theory.

Published
2021

14. An scríbhneoir agus an seanchaí : cás-staidéar ar na trasnuithe agus ar na deighiltí i ngearrscéalta iontais Shéamuis Uí Ghrianna agus saothar béil Annie Báine

Author

Casey, Michael and Smith, Peter

Subjects
Folklore, Be´aloideas, Oral theory, Teoiric, Olrik, Intersections, Divisions
Abstract

Is ar éigean, ar ndóigh, is féidir saothar Shéamuis Uí Ghrianna a chaibidil gan béaloideas a lua nó is minic a thagraítear i léirmheasanna ar an scríbhneoir do chultúr an traidisiúin bhéil a bheith mar chúlra nó d'anáil an bhéaloidis a bheith le mothachtáil ina chuid saothar. Dá mb'amhlaidh gur tharraing sé an oiread sin ó thobar an traidisiúin bhéil agus gur admhaigh na léirmheastóirí an méid sin féin, nár chóir cur chuige béaloidis a tharraingt isteach faoi raon an phlé le go dtuigfear go cruinn beacht an áit a dtrasnaíonn féith an chaomhnóra le féith na cruthaitheachta ina chuid saothar. Chonacthas dom mar sin go raibh géarghá le buntaighde ar ábhar an bhéaloidis i saothar Uí Ghrianna. Le hiniúchadh a dhéanamh air seo, d'fhéach mé le dhá shlat tomhais a tharraingt isteach. A chéad uair, baineadh úsáid as Prionsabail na n-Insintí Béil de chuid Axel Olrik mar phointí comhtheagmhála ar na gnásanna atá sa traidisiún béil. Ansin, bhain mé úsáid as deirfiúr Shéamuis, an seanchaí Annie Bhán, le féacháil ar na Prionsabail agus iad ar obair. Is é atá i gceist agam mar sin go bhfuil idir shruth béaloidis agus shruth litríochta sa tráchtas seo. Sílim go dtabharfaidh cur chuige den tseórt seo deis annamh do léinn na Gaeilge fios a bheith againn ar nósanna traidisiúnta agus ar chúrsaí stílíochta a chleacht Séamus Ó Grianna le linn a shaoil fhada scríbhneoireachta.

Published
2020

15. Linear Dimension Reduction Approximately Preserving a Function of the 1-Norm

Author

Casey, Michael P.

Subjects
Mathematics - Probability, Mathematics - Functional Analysis, 60 (Primary) 46B09, 46B85, 60E07, 60G50 (Secondary)
Abstract

For any finite point set in $D$-dimensional space equipped with the 1-norm, we present random linear embeddings to $k$-dimensional space, with a new metric, having the following properties. For any pair of points from the point set that are not too close, the distance between their images is a strictly concave increasing function of their original distance, up to multiplicative error. The target dimension $k$ need only be quadratic in the logarithm of the size of the point set to ensure the result holds with high probability. The linear embeddings are random matrices composed of standard Cauchy random variables, and the proofs rely on Chernoff bounds for sums of iid random variables. The new metric is translation invariant, but is not induced by a norm., Comment: The paper has been shortened to 34 pages with 2 appendices and accepted to the Electronic Journal of Statistics. A figure has been added to delineate the various regimes. The proof for the small regime has been corrected. All proofs have been substantially streamlined, and a dedicated section outlining the proof has been provided

Published
2019

16. Town officials shut down a boy's ice cream stand; fundraisers and death threats followed

Author

Casey, Michael

Subjects
Government regulation, Company marketing practices, Ice cream, ices, etc. -- Marketing -- Social aspects, Health boards -- Powers and duties, Fund raising -- Methods, Boys -- Beliefs, opinions and attitudes, Ice cream parlors -- Services -- Laws, regulations and rules
Abstract

Byline: MICHAEL CASEY; ASSOCIATED PRESS NORWOOD, MASS. -- Bored and looking for something to do this summer, Danny Doherty hatched a plan to raise money for his brother's hockey team [...]

Published
2024

17. Harvard to retain Sackler name on two university-owned buildings

Author

Casey, Michael

Subjects
School buildings -- Names, Memorials -- Demonstrations and protests, Psychiatrists -- Demonstrations and protests, General interest, News, opinion and commentary, Harvard University -- Beliefs, opinions and attitudes -- Buildings and facilities
Abstract

Byline: MICHAEL CASEY; ASSOCIATED PRESS BOSTON -- Harvard University has decided against removing from campus buildings the name of a family whose company makes the powerful painkiller OxyContin, despite protests [...]

Published
2024

18. Remember the ice bucket challenge? A decade later, viral campaign is again fundraising for ALS

Author

Casey, Michael

Subjects
Research grants -- Social aspects, Fund raising -- Methods -- Social aspects, Amyotrophic lateral sclerosis -- Research -- Care and treatment, General interest, News, opinion and commentary
Abstract

Byline: MICHAEL CASEY; ASSOCIATED PRESS BOSTON -- Dozens of people, including the Massachusetts Governor and several sports stars, dumped cold water on themselves at Fenway Park Thursday to mark the [...]

Published
2024

19. Americans prepare for more sweltering heat as flood waters inundate parts of U.S. Midwest

Author

Ballentine, Summer, Willingham, Leah, Walker, Julie, Todt, Ron, and Casey, Michael

Subjects
Midwestern United States -- Environmental aspects -- Social aspects, Floods -- Forecasts and trends -- Social aspects -- United States, Hot weather -- Forecasts and trends -- Social aspects, Market trend/market analysis, General interest, News, opinion and commentary
Abstract

Byline: SUMMER BALLENTINE, LEAH WILLINGHAM, JULIE WALKER, RON TODT, MICHAEL CASEY; ASSOCIATED PRESS Millions of Americans sweated through yet another scorching day as temperatures soared Sunday across the U.S., while [...]

Published
2024

22. Long-time civil-rights activist and scholar worked with Malcolm X

Author

Casey, Michael

Subjects
Strickland, William (American activist), Civil rights workers -- Biography, General interest, News, opinion and commentary
Abstract

Byline: MICHAEL CASEY; ASSOCIATED PRESS BOSTON -- William Strickland, a longtime civil-rights activist and supporter of the Black Power movement who worked with Malcolm X and other prominent leaders in [...]

Published
2024

24. Development and Evaluation of mini-EXPLORER: A Long Axial Field-of-View PET Scanner for Nonhuman Primate Imaging

Author

Berg, Eric, Zhang, Xuezhu, Bec, Julien, Judenhofer, Martin S, Patel, Brijesh, Peng, Qiyu, Kapusta, Maciej, Schmand, Matthias, Casey, Michael E, Tarantal, Alice F, Qi, Jinyi, Badawi, Ramsey D, and Cherry, Simon R

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Bioengineering, Biomedical Imaging, Animals, Equipment Design, Image Processing, Computer-Assisted, Macaca mulatta, Positron-Emission Tomography, positron emission tomography, high sensitivity, long axial field of view, total-body imaging, rhesus monkey, Nuclear Medicine & Medical Imaging, Clinical sciences
Abstract

We describe a long axial field-of-view (FOV) PET scanner for high-sensitivity and total-body imaging of nonhuman primates and present the physical performance and first phantom and animal imaging results. Methods: The mini-EXPLORER PET scanner was built using the components of a clinical scanner reconfigured with a detector ring diameter of 43.5 cm and an axial length of 45.7 cm. National Electrical Manufacturers Association (NEMA) NU-2 and NU-4 phantoms were used to measure sensitivity and count rate performance. Reconstructed spatial resolution was investigated by imaging a radially stepped point source and a Derenzo phantom. The effect of the wide acceptance angle was investigated by comparing performance with maximum acceptance angles of 14°-46°. Lastly, an initial assessment of the in vivo performance of the mini-EXPLORER was undertaken with a dynamic 18F-FDG nonhuman primate (rhesus monkey) imaging study. Results: The NU-2 total sensitivity was 5.0%, and the peak noise-equivalent count rate measured with the NU-4 monkey scatter phantom was 1,741 kcps, both obtained using the maximum acceptance angle (46°). The NU-4 scatter fraction was 16.5%, less than 1% higher than with a 14° acceptance angle. The reconstructed spatial resolution was approximately 3.0 mm at the center of the FOV, with a minor loss in axial spatial resolution (0.5 mm) when the acceptance angle increased from 14° to 46°. The rhesus monkey 18F-FDG study demonstrated the benefit of the high sensitivity of the mini-EXPLORER, including fast imaging (1-s early frames), excellent image quality (30-s and 5-min frames), and late-time-point imaging (18 h after injection), all obtained at a single bed position that captured the major organs of the rhesus monkey. Conclusion: This study demonstrated the physical performance and imaging capabilities of a long axial FOV PET scanner designed for high-sensitivity imaging of nonhuman primates. Further, the results of this study suggest that a wide acceptance angle can be used with a long axial FOV scanner to maximize sensitivity while introducing only minor trade-offs such as a small increase in scatter fraction and slightly degraded axial spatial resolution.

Published
2018

26. Log-Concave Duality in Estimation and Control

Author

Bassett, Robert, Casey, Michael, and Wets, Roger J-B

Subjects
Mathematics - Optimization and Control
Abstract

In this paper we generalize the estimation-control duality that exists in the linear-quadratic-Gaussian setting. We extend this duality to maximum a posteriori estimation of the system's state, where the measurement and dynamical system noise are independent log-concave random variables. More generally, we show that a problem which induces a convex penalty on noise terms will have a dual control problem. We provide conditions for strong duality to hold, and then prove relaxed conditions for the piecewise linear-quadratic case. The results have applications in estimation problems with nonsmooth densities, such as log-concave maximum likelihood densities. We conclude with an example reconstructing optimal estimates from solutions to the dual control problem, which has implications for sharing solution methods between the two types of problems.

Published
2016

28. Learning Representations Using Complex-Valued Nets

Author

Sarroff, Andy M., Shepardson, Victor, and Casey, Michael A.

Subjects
Computer Science - Learning, Computer Science - Neural and Evolutionary Computing
Abstract

Complex-valued neural networks (CVNNs) are an emerging field of research in neural networks due to their potential representational properties for audio, image, and physiological signals. It is common in signal processing to transform sequences of real values to the complex domain via a set of complex basis functions, such as the Fourier transform. We show how CVNNs can be used to learn complex representations of real valued time-series data. We present methods and results using a framework that can compose holomorphic and non-holomorphic functions in a multi-layer network using a theoretical result called the Wirtinger derivative. We test our methods on a representation learning task for real-valued signals, recurrent complex-valued networks and their real-valued counterparts. Our results show that recurrent complex-valued networks can perform as well as their real-valued counterparts while learning filters that are representative of the domain of the data.

Published
2015

29. A RECKONING LOOMS FOR AMERICA'S 50-YEAR FINANCIAL SURVEILLANCE SYSTEM

Author

Casey, Michael J.

Subjects
United States. Financial Crimes Enforcement Network -- Reports, Tax evasion -- Reports, Money laundering -- Reports, Political science, Bank Secrecy Act of 1970
Abstract

For all the upheaval of 2020, it's perhaps not surprising that the 50-year anniversary of a major piece of financial legislation came and went with little fanfare. But the 1970 [...]

Published
2021
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30. Medical and Surgical Management of the Failed Pancreas Transplant

Author

Casey, Michael J., primary, Murakami, Naoka, additional, Ong, Song, additional, Adler, Joel T., additional, Singh, Neeraj, additional, Murad, Haris, additional, Parajuli, Sandesh, additional, Concepcion, Beatrice P., additional, Lubetzky, Michelle, additional, Pavlakis, Martha, additional, Woodside, Kenneth J., additional, Faravardeh, Arman, additional, Basu, Arpita, additional, Tantisattamo, Ekamol, additional, Aala, Amtul, additional, Gruessner, Angelika, additional, Dadhania, Darshana, additional, Lentine, Krista, additional, Cooper, Matthew, additional, Parsons, Ronald F., additional, and Alhamad, Tarek, additional

Published
2023
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32. Validation of the SimSET simulation package for modeling the Siemens Biograph mCT PET scanner

Author

Poon, Jonathan K, Dahlbom, Magnus L, Casey, Michael E, Qi, Jinyi, Cherry, Simon R, and Badawi, Ramsey D

Subjects
Medical and Biological Physics, Physical Sciences, Biomedical Imaging, Bioengineering, Detection, screening and diagnosis, 4.2 Evaluation of markers and technologies, Algorithms, Computer Simulation, Positron-Emission Tomography, Sensitivity and Specificity, PET, simulation, SimSET, Other Physical Sciences, Biomedical Engineering, Clinical Sciences, Nuclear Medicine & Medical Imaging, Medical and biological physics
Abstract

Monte Carlo simulation provides a valuable tool in performance assessment and optimization of system design parameters for PET scanners. SimSET is a popular Monte Carlo simulation toolkit that features fast simulation time, as well as variance reduction tools to further enhance computational efficiency. However, SimSET has lacked the ability to simulate block detectors until its most recent release. Our goal is to validate new features of SimSET by developing a simulation model of the Siemens Biograph mCT PET scanner and comparing the results to a simulation model developed in the GATE simulation suite and to experimental results. We used the NEMA NU-2 2007 scatter fraction, count rates, and spatial resolution protocols to validate the SimSET simulation model and its new features. The SimSET model overestimated the experimental results of the count rate tests by 11-23% and the spatial resolution test by 13-28%, which is comparable to previous validation studies of other PET scanners in the literature. The difference between the SimSET and GATE simulation was approximately 4-8% for the count rate test and approximately 3-11% for the spatial resolution test. In terms of computational time, SimSET performed simulations approximately 11 times faster than GATE simulations. The new block detector model in SimSET offers a fast and reasonably accurate simulation toolkit for PET imaging applications.

Published
2015

33. Decline in State Chartered Banks: Causes, Concerns, and Conclusions

Author

James Hannah, Casey Michael, and Mitchell David

Subjects
banking, financial institutions, equity capital, bank charter, Business, HF5001-6182
Abstract

This paper investigates the decline of state chartered banks in the rural states Alabama, Arkansas, Nebraska, Oklahoma, and Tennessee. We use bank capital as the dependent variable for the mixed model regression analysis. We analyze both state and bank specific variables to determine which factors have more influence on bank equity capital. The findings indicate that as bank equity capital increases, the number of state chartered banks decreases. We also find that small agriculture business loans increase as equity capital increases, showing that in our sample of rural states agriculture is significant in providing a capital buffer for state chartered banks. However, we find that loans secured by farmland do not statistically influence bank equity capital.

Published
2019
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34. Biotic and Abiotic Mechanisms of Manganese (II) Oxidation in Lake Erie

Author

Casey Michael Godwin, Jessica R. Zehnpfennig, and Deric R. Learman

Subjects
manganese cycling, Mn(II), reactive oxygen species, Lake Erie, manganese oxidation, Environmental sciences, GE1-350
Abstract

Manganese (Mn), an element sensitive to redox conditions in aquatic environments, plays a role in numerous biogeochemical cycles. Although the speciation of Mn in lakes largely tracks the availability of dissolved oxygen, direct oxidation of Mn by molecular oxygen occurs slowly and, instead, the majority of Mn oxidation occurs via biotic and abiotic mechanisms involving microbes, organic matter, light, reactive oxygen species, and mineral surfaces. While each of these mechanisms is either known or likely to occur in freshwater, the relative balance and interaction among these biogeochemical pathways in an intact plankton system remains uncertain. We investigated potential abiotic and biotic mechanisms contributing to Mn oxide formation in Lake Erie, which experiences seasonal hypoxia and accumulation of Mn during seasonal stratification. Overall, Mn oxidation rates were much higher in the shallow and highly productive western basin (up to 1.5 μmoles L−1 d−1) compared to the deeper and less productive central basin, where we observed very little Mn oxidation over 7 days. Our experiments suggest that abiotic mechanisms involving mineral surfaces played a larger role than biotic mechanisms, particularly in the light where Mn oxidation was highest. Reactive oxygen species exhibited antagonistic roles: hydrogen peroxide acted as a net reductant for manganese oxides and completely masked oxidation of Mn by the superoxide free radical. These findings show that multiple mechanisms may exert control over the fate of Mn and suggest that Mn released from sediments during hypoxia can potentially remain dissolved in the water for an extended period of time. Since the severity of Lake Erie hypoxia has increased in recent years, and we are becoming increasingly aware of the health effects of Mn in drinking water sources, these findings should help inform efforts to predict when and where Mn will accumulate in the lake water.

Published
2020
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35. The Perspectives of General Nephrologists Toward Transitions of Care and Management of Failing Kidney Transplants

Author

Alhamad, Tarek, primary, Murad, Haris, additional, Dadhania, Darshana M., additional, Pavlakis, Martha, additional, Parajuli, Sandesh, additional, Concepcion, Beatrice P., additional, Singh, Neeraj, additional, Murakami, Naoka, additional, Casey, Michael J., additional, Ji, Mengmeng, additional, Lubetzky, Michelle, additional, Tantisattamo, Ekamol, additional, Alomar, Omar, additional, Faravardeh, Arman, additional, Blosser, Christopher D., additional, Basu, Arpita, additional, Gupta, Gaurav, additional, Adler, Joel T., additional, Adey, Deborah, additional, Woodside, Kenneth J., additional, Ong, Song C., additional, Parsons, Ronald F., additional, and Lentine, Krista L., additional

Published
2023
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36. The DDO IVC Distance Project

Author

Gladders, Michael D., Clarke, Tracy E., Burns, Christopher R., Attard, Allen, Casey, Michael P., Hamilton, Devon, Mallen-Ornelas, Gabriela, Karr, Jennifer L., Poirier, Sara M., Sawicki, Marcin, Barrientos, Felipe, Barkhouse, Wayne, Brodwin, Mark, Clark, Jason, McNaughton, Rosemary, Ruetalo-Pacheco, Marcelo, and Mochnacki, Stefan W.

Subjects
Astrophysics
Abstract

We present the first set of distance limits from the David Dunlap Observatory Intermediate Velocity Cloud (DDO IVC) distance project. Such distance measures are crucial to understanding the origins and dynamics of IVCs, as the distances set most of the basic physical parameters for the clouds. Currently there are very few IVCs with reliably known distances. This paper describes in some detail the basic techniques used to measure distances, with particular emphasis on the the analysis of interstellar absorption line data, which forms the basis of our distance determinations. As an example, we provide a detailed description of our distance determination for the Draco Cloud. Preliminary distance limits for a total of eleven clouds are provided., Comment: 11 pages, 5 figures, to appear in 'High-Velocity Clouds', ASP Conference Series

Published
1998

38. Modelling wave-ice interactions in three-dimensions in the marginal ice zone

Author

Perrie, Will, Meylan, Michael, Toulany, Bechara, and Casey, Michael

Abstract

The study and forecasting of Arctic storms, and their ocean surface waves, are important issues, particularly with climate change, and decreasing sea ice. Our focus is three different modern wave-ice models, with particular attention for three-dimensional wave-scattering, which is challenging to implement because of required energy redistribution. These models have only recently been implemented in WAVEWATCHIII wave model, with sufficient efficiency for operational forecasts, as described by Perrie et al. (2022, doi.org/10.1098/rsta.2021.0263). We perform the simulation of large-scale ocean waves and controlled inter-comparisons, for these wave-ice models for a simple hypothetical ocean and Marginal Ice Zone (MIZ); test cases for wave development and attenuation are driven by constant winds, to identify model weaknesses. Our follow-on work compares model simulations with field measurements using relatively high-quality data, collected by wave buoys from the Sea State Boundary Layer Experiment of 2015 in the Beaufort Sea. This experiment includes several storm events and a variety of wave systems and MIZ situations, with differing ice floe sizes, concentrations and thicknesses. Results are given in this presentation.Regarding the wave-ice models, one is the Bedford Institute of Oceanography (BIO) model which involves 3-dimensional wave-ice interactions for wave attenuation and three-dimensional wave scattering. The second model (MBS) uses the full integration of the scattering kernel, (like BIO), and includes flexible ice floes, based on papers by Meylan, Bennetts and Squire. The third is like MBS, with additional energy dissipation. MBS and MBS’ models assume no ice floe submergence; BIO has rigid MIZ floes that submerge partially.&nbsp, The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

Published
2023

39. Examining the Deductibility of Unreimbursed Charitable Expenditures

Author

Watson, Stephanie F., Casey, Michael, and Bunker, Randall B.

Subjects
Financial statements, Philanthropy, Charities, Tax law, Income tax, Tax deductions, Retail trade, Criminal investigation, Organizations, Tax law, Banking, finance and accounting industries, Business
Abstract

Taxpayers who give to charitable organizations may be rewarded by a reduction in the amount of federal and state income taxes they pay. Some charitable taxpayers give money, while others [...]

Published
2019

40. UN summit reaches historic pact to protect land and water

Author

Casey, Michael

Subjects
Biological diversity -- Conferences, meetings and seminars, Environmental protection -- Conferences, meetings and seminars, Environmental issue, News, opinion and commentary, United Nations -- Conferences, meetings and seminars
Abstract

Byline: Michael Casey, Associated Press MONTREAL - Negotiators reached a historic deal at a U.N. biodiversity conference early Monday that would represent the most significant effort to protect the world's [...]

Published
2022

41. An automated size and time-resolved aerosol collector platform integrated with environmental sensors to study the vertical profile of aerosols

Author

Zezhen Cheng, Andrey Liyu, Darielle Dexheimer, Nurun Nahar Lata, Gourihar Kulkarni, Casey Michael Longbottom, Fan Mei, and Swarup China

Subjects
Chemistry (miscellaneous), Environmental Chemistry, Pollution, Analytical Chemistry
Abstract

Vertical gradient of size-resolved aerosol composition reveals various atmospheric processing at different altitudes.

Published
2022

43. Innovation Revolution at Gwinnett County Library

Author

Casey, Michael E. and Pace, Charles

Subjects
African Americans, Public libraries, Library and information science
Abstract

A strong network of partnerships is the lifeblood of the modern library system. The experience of the Gwinnett County (GA) Public Library System (GCPL) certainly supports the truth of this [...]

Published
2018

44. In blockchain we trust

Author

Casey, Michael J. and Vigna, Paul

Subjects
Cryptocurrencies -- Forecasts and trends, Bubbles (Economics) -- Forecasts and trends, Information technology -- History -- Forecasts and trends, Blockchains (Databases) -- Forecasts and trends, Information technology, Market trend/market analysis, Business, Computers and office automation industries, High technology industry
Abstract

The case for blockchain: after the bubble bursts, the foundations of a future technological industry will remain. The case against crypto-currencies: they're good for thieves and speculators, but no use [...]

Published
2018

46. COVID-19 and renal allograft rejection: insight from controlled and noncontrolled studies.

Author

Daoud, Ahmed, Soliman, Karim, Posadas Salas, Maria Aurora, Uehara, Genta, Vaishnav, Sakshi, Cheungpasitporn, Wisit, and Casey, Michael J.

Subjects
GRAFT rejection, LITERATURE reviews, COVID-19, STATISTICAL correlation, COVID-19 pandemic
Abstract

Aim: Kidney transplant recipients (KTRs), due to their immunosuppressed status, are potentially more susceptible to both the severe effects of COVID-19 and complications in their transplanted organ. The aim of this study is to investigate whether COVID-19 infection increases the risk of rejection in kidney transplant recipients (KTRs). Methods: This study involved a detailed literature review, conducted using PubMed, with the search being completed by September 7th, 2023. The search strategy incorporated a combination of relevant keywords: ‘COVID’, ‘Renal’, ‘Kidney’, ‘Transplant’, and ‘Rejection’. The results from controlled and uncontrolled studies were separately collated and analyzed. Results: A total of 11 studies were identified, encompassing 1,179 patients. Among these, two controlled studies reported the incidence of rejection in KTRs infected with COVID-19. Pooling data from these studies revealed no significant statistical correlation between COVID-19 infection and biopsy-proven rejection (p=0.26). In addition, nine non-controlled studies were found, with rejection incidences ranging from 0% to 66.7%. The majority of these studies (eight out of nine) had small sample sizes, ranging from 3 to 75 KTRs, while the largest included 372 KTRs. The combined rejection rate across these studies was calculated to be 11.8%. Conclusion: In conclusion, the limited number of published controlled studies revealed no statistically significant association between COVID-19 infection and biopsy-proven rejection among KTRs. However, the broader analysis of non-controlled studies showed a variable rejection incidence with a pooled rejection rate of 11.8%. There is insufficient high-quality data to explore the association of COVID-19 infection and rejection. [ABSTRACT FROM AUTHOR]

Published
2024
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47. Diagnostic Performance of Dynamic Whole-Body Patlak [ 18 F]FDG-PET/CT in Patients with Indeterminate Lung Lesions and Lymph Nodes.

Author

Weissinger, Matthias, Atmanspacher, Max, Spengler, Werner, Seith, Ferdinand, Von Beschwitz, Sebastian, Dittmann, Helmut, Zender, Lars, Smith, Anne M., Casey, Michael E., Nikolaou, Konstantin, Castaneda-Vega, Salvador, and la Fougère, Christian

Subjects
LUNG diseases, LYMPH nodes, POSITRON emission tomography, LUNG tumors, SPORT utility vehicles
Abstract

Background: Static [18F]FDG-PET/CT is the imaging method of choice for the evaluation of indeterminate lung lesions and NSCLC staging; however, histological confirmation of PET-positive lesions is needed in most cases due to its limited specificity. Therefore, we aimed to evaluate the diagnostic performance of additional dynamic whole-body PET. Methods: A total of 34 consecutive patients with indeterminate pulmonary lesions were enrolled in this prospective trial. All patients underwent static (60 min p.i.) and dynamic (0–60 min p.i.) whole-body [18F]FDG-PET/CT (300 MBq) using the multi-bed-multi-timepoint technique (Siemens mCT FlowMotion). Histology and follow-up served as ground truth. Kinetic modeling factors were calculated using a two-compartment linear Patlak model (FDG influx rate constant = Ki, metabolic rate = MR-FDG, distribution volume = DV-FDG) and compared to SUV using ROC analysis. Results: MR-FDGmean provided the best discriminatory power between benign and malignant lung lesions with an AUC of 0.887. The AUC of DV-FDGmean (0.818) and SUVmean (0.827) was non-significantly lower. For LNM, the AUCs for MR-FDGmean (0.987) and SUVmean (0.993) were comparable. Moreover, the DV-FDGmean in liver metastases was three times higher than in bone or lung metastases. Conclusions: Metabolic rate quantification was shown to be a reliable method to detect malignant lung tumors, LNM, and distant metastases at least as accurately as the established SUV or dual-time-point PET scans. [ABSTRACT FROM AUTHOR]

Published
2023
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48. An Automated Size and Time-resolved Aerosol Collector (STAC) Platform Integrated Sensors to Study Vertical Profile of Aerosol

Author

Cheng, Zezhen, Liyu, Andrey, Dexheimer, Darielle, Lata, Nurun Nahar, Kulkarni, Gourihar, Longbottom, Casey Michael, Mei, Fan, and China, Swarup

Abstract

Atmospheric particles affect human health, climate, and ecosystem but assessing their impacts is still challenging. Part of that is because of the limited understanding of the size-dependence of particle properties and variation of these properties along with the vertical profile under different environmental conditions. Thus, we present an automated Size and Time-resolved Aerosol Collector (STAC) platform integrated sensors, which has been deployed on the Atmospheric Radiation Measurement’s (ARM) tethered balloon system (TBS) in several ARM campaigns in Oliktok Point (Alaska), Southern Great Plains (Oklahoma), and Crested Butte (Colorado). The STAC platform is loaded with an array of 4-stages cascade impactors to collect aerosol particles within the different aerodynamic size ranges for various atmospheric research, such as the vertical profile of size-resolved aerosol chemical composition and multi-phase chemistry at up to 20 sampling points per flight. Time-resolved sampling facilitates the study of the evolution of particles in the atmosphere. The battery-powered, lightweight automated size- and time-resolved sampling system is ideal for unmanned aerial systems (e.g., TBS) and aircraft sampling. Currently, the STAC platform is integrated with a temperature and relative humidity sensor and a pressure sensor to monitor ambient conditions, an optical particle counter to measure the aerosol size distribution, and a micro-aethalometer to measure black carbon mass concentration and light-absorption coefficient of aerosols at 375, 470, 528, 625, and 880 nm wavelength every second to investigate the dependence of aerosol properties on ambient conditions. Experimentally derived 50% cut-off sizes of each stage (stage A to D) for a standard impactor are about 2.3, 0.62, 0.42, and 0.12 μm. The impactor is adaptable to collect smaller particles with an additional replaceable Stage E with a 50% cut-off size of 0.07 μm. At each stage, we can load three different types of substrates to collect ambient aerosols for multi-modal offline analysis to probe their physical (e.g., phase state and morphology), chemical (e.g., the elemental composition of individual particles and size-resolved chemical composition), and optical (light absorption and scattering), and hygroscopic and ice nucleation properties.

Published
2022
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