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Testing the Inference Accuracy of Accelerator-Friendly Approximate Phylogeny Tracking

Testing the Inference Accuracy of Accelerator-Friendly Appro...

2025 IEEE Symposium on Computational Intelligence in Artificial Life and Cooperative Intelligent Systems, ALIFE-CIS 2025

作者： Moreno, Matthew Andres Ranjan, Anika Dolson, Emily Zaman, Luis University of Michigan Department of Ecology and Evolutionary Biology Ann Arbor United States Center for the Study of Complex Systems University of Michigan Ann Arbor United States Michigan Institute for Data and Ai in Society University of Michigan Ann Arbor United States Undergraduate Research Opportunities Program University of Michigan Ann Arbor United States Michigan State University Department of Computer Science and Engineering East Lansing United States Program in Ecology Evolution and Behavior Michigan State University East Lansing United States

ISBN: (纸本)9798331508371

computer simulations are an important tool for studying the mechanics of biological evolution. In particular, agent-based approaches provide an opportunity to collect high-quality records of ancestry relationships. Such phylogenies can provide insight into evolutionary dynamics within these simulations. Previous work generally tracks lineages directly, yielding an exact phylogenetic record of evolutionary history. However, challenges exist in scaling direct ancestrytracking approaches to highly-distributed, many-processor evolution in silico. An alternative approach is to estimate phylogenetic history via noncoding annotations on digital genomes, akin to how bioinformaticians build phylogenies by assessing genetic similarities between organisms. Recent work has extended this 'hereditary stratigraphy' approach to support powerful hardware accelerator platforms, such as the Cerebras Wafer-Scale Engine. Although these second-generation 'surface'-based hereditary stratigraphy algorithms have demonstrated order-ofmagnitude speedups over first-generation 'column'-based algorithms, it remains unknown how they impact the accuracy of reconstructed phylogenies. To address this question, we assessed reconstruction accuracy under alternative configurations across a matrix of evolutionary conditions varying in selection pressure, spatial structure, and ecological dynamics. Encouragingly, we find that the second-generation approaches provide higher reconstruction quality across most surveyed conditions. © 2025 IEEE.

关键词： Biostratigraphy

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Medical Image Segmentation by Improved Nested Unet 2nd

Medical Image Segmentation by Improved Nested Unet

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2nd International Conference on Intelligent Systems and Data Science, ISDS 2024

作者： Tran, Song-Toan Le, Minh-Hai Nguyen, Thai-Son Nghi, Vinh-Khanh Nguyen, Thanh-Nguyen School of Engineering and Technology Tra Vinh University Tra Vinh87000 Viet Nam Resource Development Institute Tra Vinh University Tra Vinh87000 Viet Nam PhD program in Computer Science Tra Vinh University Tra Vinh87000 Viet Nam Facilities Management Department Tien Giang University Tien Giang84000 Viet Nam

ISBN: (纸本)9789819796120

Deep learning is revolutionizing the field of medical image segmentation. The U-shaped (Unet) model, with its encoder-decoder architecture and skip connections, has become the dominant architecture for this task. However, variations like Nested-Unet are necessary to address the challenge of adapting network size for datasets of varying scales. This study proposes a novel model based on a multilayer Unet architecture that leverages all output features within nodes of a Nested Unet network. We evaluate the proposed model on four key medical image datasets: electron microscopy (EM), nuclei, polyps (CVC-ClinicDB), and skin lesions. The model achieves impressive Dice scores: 94.08% for EM, 92.68% for nuclei, 87.20% for skin lesions, and 93.02% for the CVC-ClinicDB dataset. These outstanding results demonstrate the superior performance of our proposed model compared to recent advancements in the field. Remarkably, the model achieves this performance while maintaining a size that is half that of a traditional Unet model. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Image segmentation

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A computational framework for longitudinal medication adherence prediction in breast cancer survivors: A social cognitive theory based approach

arXiv

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arXiv 2025年

作者： Kaur, Navreet Gonzales, Manuel Alcaraz, Cristian Garcia Gong, Jiaqi Wells, Kristen J. Barnes, Laura E. Department of Systems and Information Engineering University of Virginia CharlottesvilleVA United States SDSU/UC San Diego Joint Doctoral Program in Clinical Psychology San DiegoCA United States Department of Computer Science The University of Alabama TuscaloosaAL United States Department of Psychology San Diego State University San DiegoCA United States

Non-adherence to medications is a critical concern since nearly half of patients with chronic illnesses do not follow their prescribed medication regimens, leading to increased mortality, costs, and preventable human distress. Amongst stage 0-3 breast cancer survivors, adherence to long-term adjuvant endocrine therapy (i.e., Tamoxifen and aromatase inhibitors) is associated with a significant increase in recurrence-free survival. This work aims to develop multi-scale models of medication adherence to understand the significance of different factors influencing adherence across varying time frames. We introduce a computational framework guided by Social Cognitive Theory for multi-scale (daily and weekly) modeling of longitudinal medication adherence. Our models employ both dynamic medication-taking patterns in the recent past (dynamic factors) as well as less frequently changing factors (static factors) for adherence prediction. Additionally, we assess the significance of various factors in influencing adherence behavior across different time scales. Our models outperform traditional machine learning counterparts in both daily and weekly tasks in terms of both accuracy and specificity. Daily models achieved an accuracy of 87.25% (Precision – 92.04%, Recall – 93.15%, Specificity – 77.50%), and weekly models, an accuracy of 76.04% (Precision – 75.83%, Recall – 85.80%, Specificity – 72.30%). Notably, dynamic past medication-taking patterns prove most valuable for predicting daily adherence, while a combination of dynamic and static factors is significant for macro-level weekly adherence patterns. While our models exhibit strong predictive performance, they are constrained by potential cohort-specific biases, reliance on self-reported adherence data, and a limited understanding of the context around non-adherence. Future research will focus on external validation across diverse populations and explore the real-world implementation of sensor-rich systems for a more compre

关键词： Endocrinology

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Competition between Hot Carriers and Surface Electrochemistry in Gold Nanorod Dissolution

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The Journal of Physical Chemistry C 2025年第22期129卷 10154-10162页

作者： Jiamu Lin Katsuya Shiratori Claire A. West Alexander Al-Zubeidi Zhenyang Jia Hyuncheol Oh Stephan Link Christy F. Landes Department of Chemistry University of Illinois Urbana−Champaign Urbana Illinois 61801 United States；Department of Chemistry Rice University Houston Texas 77005 United States Department of Physics University of Illinois Urbana−Champaign Urbana Illinois 61801 United States；Applied Physics Graduate Program Rice University Houston Texas 77005 United States Department of Chemistry University of Illinois Urbana−Champaign Urbana Illinois 61801 United States Department of Chemistry Rice University Houston Texas 77005 United States Department of Chemical and Biomolecular Engineering University of Illinois Urbana−Champaign Urbana Illinois 61801 United States；Department of Chemical and Biomolecular Engineering Rice University Houston Texas 77005 United States Department of Chemistry University of Illinois Urbana−Champaign Urbana Illinois 61801 United States；Department of Chemistry Rice University Houston Texas 77005 United States；Department of Physics University of Illinois Urbana−Champaign Urbana Illinois 61801 United States；Applied Physics Graduate Program Rice University Houston Texas 77005 United States；Department of Electrical and Computer Engineering University of Illinois Urbana−Champaign Urbana Illinois 61801 United States；Department of Electrical and Computer Engineering Rice University Houston Texas 77005 United States；Materials Research Laboratory University of Illinois Urbana−Champaign Urbana Illinois 61801 United States Department of Chemistry University of Illinois Urbana−Champaign Urbana Illinois 61801 United States；Department of Chemistry Rice University Houston Texas 77005 United States；Department of Chemical and Biomolecular Engineering University of Illinois Urbana−Champaign Urbana Illinois 61801 United States；Department of Chemical and Biomolecular Engineering Rice University Houston Texas 77005 United States；Department of Electrical and Computer Engineering University of Illinois Urbana−Champaign Urbana Illinois 61801 United

Plasmonic nanostructures have the potential to revolutionize photocatalysis by harnessing hot carriers to drive novel chemical reactions. Precise control of reaction sites on nanoparticles remains crucial for advancing catalyst design. The influence of hot carriers, particularly in the interplay with surface electrochemistry, needs further exploration. Employing single-particle spectroelectrochemical methods, we identify the conditions that lead to tip-preferred versus isotropic dissolution. We investigate how the applied potential, excitation laser power density, and wavelength of illumination directly direct gold nanorod dissolution. There is a competition between hot carrier localization and electrochemistry in determining the dissolution anisotropy. We observe that higher potentials favor isotropic dissolution, whereas higher laser power densities drive tip-specific dissolution. The results provide new insights into the control of tuning the gold nanoparticle dissolution anisotropy.

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Glaucoma identification with retinal fundus images using deep learning: Systematic review

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Informatics in Medicine Unlocked 2025年 56卷

作者： Meedeniya, Dulani Shyamalee, Thisara Lim, Gilbert Yogarajah, Pratheepan Department of Computer Science and Engineering University of Moratuwa Moratuwa 10400 Sri Lanka First-Year Division Faculty of Computing Sri Lanka Institute of Information Technology Malabe 10115 Sri Lanka SingHealth AI Health Program SingHealth Group Singapore 168582 Singapore School of Computing Engineering and Intelligent System Ulster University Londonderry BT48 7JL United Kingdom

Glaucoma is a leading cause of blindness, affecting millions of people worldwide. It is a chronic eye condition that damages the optic nerve and, if left untreated, can lead to vision loss and a decreased quality of life. Therefore, there is a need to explore practical and reliable mechanisms for glaucoma identification. This study systematically reviews deep-learning approaches for glaucoma identification using retinal fundus images from 2018 to 2024. Compared to existing survey studies, we cover the latest research, including several public retinal fundus image datasets, and focus on segmentation, classification based on convolutional neural networks and vision transformers, and explainability. The findings of this study, including comparisons of existing methods and key insights, will assist researchers and developers in identifying the most suitable techniques for glaucoma detection. © 2025 The Authors

关键词： Artificial intelligence Classification Deep learning Explainability Glaucoma Segmentation Trustworthiness

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Comprehensive prediction of outcomes in patients with ST elevation myocardial infarction (STEMI) using tree-based machine learning algorithms

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computers in Biology and Medicine 2025年 184卷 109439-109439页

作者： Razavi, Seyed Reza Zaremba, Alexander C. Szun, Tyler Cheung, Seth Shah, Ashish H. Moussavi, Zahra Biomedical Engineering Program University of Manitoba WinnipegMBR3T 5V6 Canada Department of Medicine Rady Faculty of Health Sciences University of Manitoba WinnipegMBR3E 3P5 Canada St Boniface Hospital University of Manitoba WinnipegMBR2H 2A6 Canada Department of Electrical and Computer Engineering University of Manitoba WinnipegMBR3T 5V6 Canada

ST elevation myocardial infarction (STEMI), a subtype of acute coronary syndrome, is one of the leading causes of morbidity and mortality. Revascularization using primary percutaneous coronary intervention (PPCI) is the gold standard treatment. Despite the restoration of myocardial blood flow, some patients experience adverse outcomes. Early detection of high-risk patients would facilitate timely management, potentially improving their morbidity, mortality, and quality of life. In-depth characterization of the aortic pressure (AP) waveform may identify a high-risk patient cohort. We present tree-based classifiers and features extracted from the AP signals to identify patients at risk of adverse outcomes. This is a single-center, retrospective cohort study that included 605 eligible STEMI patients [64.2 ± 13.2 years, 71.4 % (432) males] treated with PPCI. Outcomes, including mortality (within 30-day and 1-year), and in-hospital events such as prolonged in-hospital stay (>4 days) for medical reasons, a new diagnosis of heart failure (HF), diuretic use for more than 24 h, intubation-ventilation or BiPAP use, and inotropic and/or vasopressor use, were recorded. We extracted features mainly from denoised AP signals recorded during PPCI, followed by different feature selection algorithms and classification methods to predict outcomes. Various classifiers such as tree-based classifiers, including random forest (RF), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), and CatBoost, were used. Using recursive feature elimination (RFE) as the feature selection method and the CatBoost classifier, we achieved a receiver operating characteristic curve's area under the curve (AUC) of 80 % for all outcomes except for the new diagnosis of HF and diuretic use (>24 h). For the new diagnosis of HF and diuretic use (>24 h), the AUC values were 73 % and 79 %, respectively. In conclusion, tree-based classifiers using features extracted from AP traces can effectively identi

关键词： Adaptive boosting

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MEAN SOJOURN TIMES IN MARKOV QUEUING-NETWORKS - LITTLE FORMULA REVISITED

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IEEE TRANSACTIONS ON INFORMATION THEORY 1983年第2期29卷 233-241页

作者： BEUTLER, FJ Computer Information and Control Engineering Program University of Michigan Ann Arbor MI USA

It is commonly supposed that, L=\lambdaW applies to "almost any" queueing system with \lambda some average customer entrance rate, L the asymptotic expectation or time average of the number of customers in the system and W some average of the sojourn time. This formula is studied for irreducible positive recurrent Markov queueing systems whose state vector Z consists of entries representing queue lengths at the respective service stations; blocking, finite capacities, batch arrivals, and variable rates of arrival and service are consistent with Z . Sojourn times are defined inan augmented Markov model Y=(Z,U) , where the customer marking process U describes the service discipline in sufficiently general terms to include most possibilities of interest. It is shown that L=\lambda W is universally applicable, if properly interpreted to take account of state-varying entrance rates, batch arrivals, and multiple customer classes. L,\lambda , and W may each be equivalently viewed as time averages, means over a regeneration cycle, or expectations with respect to the asymptotic probability structure of Z . Indeterminate forms of L=\lambda W are possible within the scope of Markov queueing networks (MQN); as is shown by some examples, these may take the form \infty \times 0 for \lambda W , or of \infty= \infty for L=\lambda W .

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OPTIMAL PERIODIC CONTROL - THE PI-TEST REVISITED

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 1980年第4期25卷 673-684页

作者： BERNSTEIN, DS GILBERT, EG Program in Computer Information and Control Engineering University of Michigan Ann Arbor MI USA

The paper examines second-order conditions for both steady-state and dynamic optimality in a periodic control problem. It centers on the π condition of Bittanti, Fronza, and Guardabassi [2] and has three main objectives: 1) to form a π "test" for a somewhat more general problem than considered in [2]; 2) to point out that certain auxiliary conditions must be added if the results of [2] are to be valid; and 3) to explore more fully the relationships between second-order conditions for steady-state optimality and second-order conditions for optimality in the dynamic problem.

关键词： Optimal control Testing Steady-state Digital filters Switching circuits Circuit analysis Circuit synthesis Signal synthesis Geophysical signal processing Petroleum

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Fixed Frequency, Variable Amplitude (FiFVA) Actuation Systems for Micro Aerial Vehicles

Fixed Frequency, Variable Amplitude (FiFVA) Actuation System...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Ratti, Jayant Jones, Emanuel Vachtsevanos, George Robotics Program School of Electrical and Computer Engineering USA

ISBN: (纸本)9781612843858

Micro Aerial Vehicles (MAVs) have gained a significant amount of research lately, with a number of universities and industry sponsors paving the way with micro flying robots to perform Intelligence, Surveillance and Reconnaissance (ISR) Missions. However, much of the work done in flapping wing MAVs till date has not shown performance improvements over their Vertical Take Off and Landing (VTOL), rotary-wing counterparts. Research and development over the years has shown that insects and birds have unmatched flying capabilities in the Low Reynolds Number Regime. Their phenomenal flight performance is attributed to among others the highly energy efficient actuation systems and their power to weight ratios. The paper proposes and illustrates new and energy-efficient actuation mechanisms and incorporating them into MAVs. The paper begins by elaborating on the background of our research and the need for energy efficiency in MAVs;followed by showcasing resonant, elastic/restorative actuation mechanisms and their control methodology to reduce flight-actuation energy requirements. In conclusion, the paper contrasts and compares all the actuation systems for power intake, scalability and mechanical complexity.

关键词： Actuators Coils Couplings Frequency modulation Gears Springs Switches

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An Analysis of Python Serialization towards Distributed Systems 19

An Analysis of Python Serialization towards Distributed Syst...

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19th International Conference on Electrical engineering/Electronics, computer, Telecommunications and Information Technology, ECTI-CON 2022

作者： Tangmunchittham, Eakasit Piromsopa, Krerk Chulalongkorn University Computer Engineering Program Department of Computer Engineering Bangkok Thailand

ISBN: (纸本)9781665485845

We explored the current state of Python serialization in the context of distributed computing. The challenging points addressed are: object-type support, speed and size, version compatibility, and implementations. There are three well-known serialization modules in our analysis. They are: standard python pickle, cloudpickle, and dill. We found that while the current serialization modules work well, there are certain fundamental issues on __reduce__ method that can be addressed. There is also a room for improvement that can have significant impacts for the community. © 2022 IEEE.

关键词： Python

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