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Articles 45721 - 45750 of 294574

Full-Text Articles in Physical Sciences and Mathematics

A Comparative Analysis Of Viral Aerosol Biological Sampling Efficiency Of A Small Unmanned Aircraft System (Suas)-Mounted Aerosol Sampler And A Reference Static Biosampler®, Jonathan D. Moroz Mar 2023

A Comparative Analysis Of Viral Aerosol Biological Sampling Efficiency Of A Small Unmanned Aircraft System (Suas)-Mounted Aerosol Sampler And A Reference Static Biosampler®, Jonathan D. Moroz

Theses and Dissertations

Bioaerosol sampling using small unmanned aerial systems (sUAS) is a rapidly developing field that may result in a paradigm shift in emergency response and industrial hygiene sampling conventions. These technologies offer decreased sample acquisition times, larger sampling area coverage, and reduced health and safety risks to traditional human sampling teams. This potential requires a comprehensive investigation of sUAS capabilities and limitations. This study is a continuation of the characterization of an AFIT-developed sUAS-mounted aerosol sampler, proven capable of collecting viable vegetative and spore-forming bacteria through previous AFIT research. Within this study, viral biological sampling efficiency (BSE) of the sUAS-mounted aerosol …

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Garbage In ≠ Garbage Out: Exploring Gan Resilience To Image Training Set Degradations, Nicholas M. Crino Mar 2023

Garbage In ≠ Garbage Out: Exploring Gan Resilience To Image Training Set Degradations, Nicholas M. Crino

Theses and Dissertations

Generative Adversarial Networks (GANs) have received increasing attention in recent years due to their ability to capture complex, high-dimensional data distributions without the need for extensive labeling. Since their conception in 2014, a wide array of GAN variants have been proposed featuring alternative architectures, optimizers, and loss functions with the goal of improving performance and training stability. While this research has yielded GAN variants robust to training set shrinkage and corruption, our research focuses on quantifying the resilience of a GAN architecture to specific modes of image degradation. We conduct systematic experimentation to determine empirically the effects of 10 fundamental …

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Hierarchical Federated Learning On Healthcare Data: An Application To Parkinson's Disease, Brandon J. Harvill Mar 2023

Hierarchical Federated Learning On Healthcare Data: An Application To Parkinson's Disease, Brandon J. Harvill

Theses and Dissertations

Federated learning (FL) is a budding machine learning (ML) technique that seeks to keep sensitive data private, while overcoming the difficulties of Big Data. Specifically, FL trains machine learning models over a distributed network of devices, while keeping the data local to each device. We apply FL to a Parkinson’s Disease (PD) telemonitoring dataset where physiological data is gathered from various modalities to determine the PD severity level in patients. We seek to optimally combine the information across multiple modalities to assess the accuracy of our FL approach, and compare to traditional ”centralized” statistical and deep learning models.

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Automated Registration Of Titanium Metal Imaging Of Aircraft Components Using Deep Learning Techniques, Nathan A. Johnston Mar 2023

Automated Registration Of Titanium Metal Imaging Of Aircraft Components Using Deep Learning Techniques, Nathan A. Johnston

Theses and Dissertations

Studies have shown a connection between early catastrophic engine failures with microtexture regions (MTRs) of a specific size and orientation on the titanium metal engine components. The MTRs can be identified through the use of Electron Backscatter Diffraction (EBSD) however doing so is costly and requires destruction of the metal component being tested. A new methodology of characterizing MTRs is needed to properly evaluate the reliability of engine components on live aircraft. The Air Force Research Lab Materials Directorate (AFRL/RX) proposed a solution of supplementing EBSD with two non-destructive modalities, Eddy Current Testing (ECT) and Scanning Acoustic Microscopy (SAM). Doing …

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Uncertainty Quantification In Federated Learning For Persistent Post-Traumatic Headache, Byungmoo Brian Kim Mar 2023

Uncertainty Quantification In Federated Learning For Persistent Post-Traumatic Headache, Byungmoo Brian Kim

Theses and Dissertations

A post-traumatic headache (PTH), resulting from a mild traumatic brain injury (mTBI), potentially develops into persistent post-traumatic headache (PPTH). Although no known cure for PPTH exists, research has shown that receiving treatment at earlier stages of PTH lowers the risk of patients developing PPTH. Previous studies have shown machine learning (ML) models capable of predicting a patient’s PTH progression, but none have considered the issue of protecting patient privacy. Due to patient privacy, ML models only have access to data within the institution. Federated learning (FL) harnesses data from separate institutions without sacrificing patient privacy as institutions can run ML …

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Bayesian Recurrent Neural Networks For Real Time Object Detection, Stephen Z. Kimatian Mar 2023

Bayesian Recurrent Neural Networks For Real Time Object Detection, Stephen Z. Kimatian

Theses and Dissertations

Neural networks have become increasingly popular in real time object detection algorithms. A major concern with these algorithms is their ability to quantify their own uncertainty, leading to many high profile failures. This research proposes three novel real time detection algorithms. The first of leveraging Bayesian convolutional neural layers producing a predictive distribution, the second leveraging predictions from previous frames, and the third model combining these two techniques together. These augmentations seek to mitigate the calibration problem of modern detection algorithms. These three models are compared to the state of the art YOLO architecture; with the strongest contending model achieving …

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Predicting Success Of Pilot Training Candidates Using Interpretable Machine Learning, Alexandra S. King Mar 2023

Predicting Success Of Pilot Training Candidates Using Interpretable Machine Learning, Alexandra S. King

Theses and Dissertations

The United States Air Force (USAF) has struggled with a sustained pilot shortage over the past several years; senior military and government leaders have been working towards a solution to the problem, with no noticeable improvements. Both attrition of more experienced pilots as well as wash out rates within pilot training contribute to this issue. This research focuses on pilot training attrition. Improving the process for selecting pilot candidates can reduce the number of candidates who fail. This research uses historical specialized undergraduate pilot training (SUPT) data and leverages select machine learning techniques to determine which factors are associated with …

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Fragility Of The Florida Panhandle's Electrical Transmission Grid To Hurricanes, Zachary D. Schumann Mar 2023

Fragility Of The Florida Panhandle's Electrical Transmission Grid To Hurricanes, Zachary D. Schumann

Theses and Dissertations

The increased frequency and intensity of extreme weather events from climate change necessitates understanding impacts on critical infrastructure, particularly electrical transmission grids. One of the foundational concepts of a grid’s resilience is its robustness to extreme weather events, such as hurricanes. Resilience of the electric grid to high wind speeds is predicated upon the location and physical characteristics of the system components. Previous modeling assessments of electric grid failure were done at the systems level with assumptions on location and type of specific components. To facilitate more explicit adaptation metrics, accurate component-level information is needed. In this study, we build …

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Air Force Cadet To Career Field Matching Problem, Ian P. Macdonald Mar 2023

Air Force Cadet To Career Field Matching Problem, Ian P. Macdonald

Theses and Dissertations

This research examines the Cadet to Air Force Specialty Code (AFSC) Matching Problem (CAMP). Currently, the matching problem occurs annually at the Air Force Personnel Center (AFPC) using an integer program and value focused thinking approach. This paper presents a novel method to match cadets with AFSCs using a generalized structure of the Hospitals Residents problem with special emphasis on lower quotas. This paper also examines the United States Army Matching problem and compares it to the techniques and constraints applied to solve the CAMP. The research culminates in the presentation of three algorithms created to solve the CAMP and …

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Examining Fuel Service System Failures Of The Usaf R11 Using Survival Analysis, Roed M.S. Mejia Mar 2023

Examining Fuel Service System Failures Of The Usaf R11 Using Survival Analysis, Roed M.S. Mejia

Theses and Dissertations

Recent events show that fuel supply is a large contributor to the success or failure of a military operation in response to a contingency. Any future near-peer conflict will stress the supply chain and require fully operational vehicles to be ready for the primary mission sets they support. In the United States Air Force (USAF), the readiness of fuel distribution trucks is crucial to meeting those mission sets in global operations. Utilizing non-parametric and semi-parametric survival models, which do not assume specific probability distributions, this study analyzes maintenance data for R-11 trucks that refuel aircraft.

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Examining Failures Of Kc-135 Boom Assemblies Using Survival Analysis, Benjamin D. Miller Mar 2023

Examining Failures Of Kc-135 Boom Assemblies Using Survival Analysis, Benjamin D. Miller

Theses and Dissertations

The purposes of this study are to confirm the applicability of survival analysis for predicting recurrent failures of a component of a military aircraft and to provide practical insights to maintenance managers and mission planners. The results of this study also can help the United States Department of Defense improve the CBM+ program. This study was able to predict recurrent failures of the component using Nelson-Aalen cumulative estimates. In addition, this study used a Cox proportional hazards regression model with shared frailty for measuring the effect of covariates on recurrent failures and unidentified heterogeneity in the model, which warranted future …

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Simulation And Analysis Of Dynamic Threat Avoidance Routing In An Anti-Access Area Denial (A2ad) Environment, Dante C. Reid Mar 2023

Simulation And Analysis Of Dynamic Threat Avoidance Routing In An Anti-Access Area Denial (A2ad) Environment, Dante C. Reid

Theses and Dissertations

This research modeled and analyzed the effectiveness of different routing algorithms for penetration assets in an A2AD environment. AFSIM was used with different configurations of SAMs locations and numbers to compare the performance of AFSIM’s internal zone and shrink algorithm routers with a Dijkstra algorithm router. Route performance was analyzed through computational and operational metrics, including computational complexity, run-time, mission survivability, and simulation duration. This research also analyzed the impact of the penetration asset’s ingress altitude on those factors. Additionally, an excursion was conducted to analyze the Dijkstra algorithm router’s grid density holding altitude constant to understand its impact on …

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Analysis And Optimization Of Contract Data Schema, Franklin Sun Mar 2023

Analysis And Optimization Of Contract Data Schema, Franklin Sun

Theses and Dissertations

agement, development, and growth of U.S Air Force assets demand extensive organizational communication and structuring. These interactions yield substantial amounts of contracting and administrative information. Over 4 million such contracts as a means towards obtaining valuable insights on Department of Defense resource usage. This set of contracting data is largely not optimized for backend service in an analytics environment. To this end, the following research evaluates the efficiency and performance of various data structuring methods. Evaluated designs include a baseline unstructured schema, a Data Mart schema, and a snowflake schema. Overall design success metrics include ease of use by end …

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Probability Of Agreement As A Simulation Validation Methodology, Matthew C. Ledwith Mar 2023

Probability Of Agreement As A Simulation Validation Methodology, Matthew C. Ledwith

Theses and Dissertations

Determining whether a simulation model is operationally valid requires the rigorous assessment of agreement between observed functional responses of the simulation model and the corresponding real world system or process of interest. This research seeks to extend and formulate the probability of agreement approach to the operational validation of simulation models. The first paper provides a methodological approach and an initial demonstration which leverages bootstrapping to overcome situations where one’s ability to collect real-world data is limited. The second paper extends the probability of agreement approach to account for second-order heteroscedastic variability structures and establishes a weighted probability of agreement …

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Improving Accessibility And Efficiency Of Analytic Provenance Tools For Reverse Engineering, Caleb W. Richardson Mar 2023

Improving Accessibility And Efficiency Of Analytic Provenance Tools For Reverse Engineering, Caleb W. Richardson

Theses and Dissertations

Reverse engineering is a vital technique for identifying and mitigating cyber threats. Yet, despite its importance, reverse engineering is a time-consuming process. Provenance tools help to improve the workflow of reverse engineers by providing an accessible method of viewing their flow through a binary. The current state-of-theart provenance tool for reverse engineering software called SensorRE, leverages an external server, web browser, and a large array of javascript libraries. This thesis presents Provenance Ninja, a software reverse engineering tool developed in Python that runs directly within Binary Ninja. Provenance Ninja captures reverse engineers’ provenance data and provides an interactive graph within …

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Developing And Assessing A Generalized Serious Game That Supports Customized Joint All-Domain Operations Related Learning Objectives, Jonathan D. Moore Mar 2023

Developing And Assessing A Generalized Serious Game That Supports Customized Joint All-Domain Operations Related Learning Objectives, Jonathan D. Moore

Theses and Dissertations

As the threat of near-peer adversaries has increased, the DoD has increased its emphasis on Joint All-Domain Operations (JADO). This emphasis on JADO highlights the need for hands-on training that can engage military members at all levels. The serious game Battlespace Next (BSN) was designed to teach high-level JADO concepts by modeling real-world military assets in the context of a strategic card game. To keep pace with the evolving landscape of warfare as well as fit the needs of a variety of Department of Defense (DoD) communities, this research introduces the Battlespace Next Education Framework (BSNEF). The BSNEF allows JADO …

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Debris Survivability Study For Mega-Constellation Architectures, Joseph C. Canoy Mar 2023

Debris Survivability Study For Mega-Constellation Architectures, Joseph C. Canoy

Theses and Dissertations

The analysis for the overall theoretical debris survivabilty of mega-constellation architectures, with an emphasis on space-based ballistic missile defense constellation (SB-BMD), is explored via three extensive different Monte Carlo simulations: preliminary analysis of low Earth Orbit (LEO) mega-constellation survivabilty following a fragmentation event within the constellation, analysis of LEO mega-constellation survivability with a fragmentation event occurring on a satellite performing a maneuver to insert itself within the constellation, and the analysis of LEO mega-constellation survivabilty after a fragmentation event resulting from the destruction of a missile. The LEO mega-constellations represent the SB-BMD constellation. The first two analysis sections will include …

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Coupling To Quantum Topological Order In Superconducting Qubit Systems, Seth T. Hyra Mar 2023

Coupling To Quantum Topological Order In Superconducting Qubit Systems, Seth T. Hyra

Theses and Dissertations

The coupling of superconducting qubits to non-trivial topological phases offers a means of improving existing quantum computational capabilities in lieu of a fully realized topological quantum computer. I will show that although such systems do not completely avoid the necessary errors associated with an energetic qubit basis, they do provide a potential avenue for decoherence free quantum memory. Further, the physics behind such systems enables exploration of the nature of non-Abelian anyons, as well as the remaining challenges in realization of true topological quantum computation.

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Towards An Understanding Of The Thermodynamic Properties Of Crtao4: A Computational Perspective, Tanner B. Gordon Mar 2023

Towards An Understanding Of The Thermodynamic Properties Of Crtao4: A Computational Perspective, Tanner B. Gordon

Theses and Dissertations

Materials that can withstand higher temperatures are paramount for next-generation aircraft design. Hypersonic capabilities and jet-turbine engines operate in extreme environments. Choosing materials that have high thermal stability and oxidation resistance for these applications can increase engine efficiency, reduce size, weight and power (SWaP), and increase the maneuverability of the aircraft. The mixed oxide CrTaO4 has been experimentally observed to significantly contribute to oxidation resistance at high temperatures. However, and despite its significance, its properties remain largely unknown. This work explores the thermal properties of this material from a multi-scale approach, by obtaining an accurate description of the thermodynamics …

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Reference Frames In Human Sensory, Motor, And Cognitive Processing, Dongcheng He Mar 2023

Reference Frames In Human Sensory, Motor, And Cognitive Processing, Dongcheng He

Electronic Theses and Dissertations

Reference-frames, or coordinate systems, are used to express properties and relationships of objects in the environment. While the use of reference-frames is well understood in physical sciences, how the brain uses reference-frames remains a fundamental question. The goal of this dissertation is to reach a better understanding of reference-frames in human perceptual, motor, and cognitive processing. In the first project, we study reference-frames in perception and develop a model to explain the transition from egocentric (based on the observer) to exocentric (based outside the observer) reference-frames to account for the perception of relative motion. In a second project, we focus …

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Design, Determination, And Evaluation Of Gender-Based Bias Mitigation Techniques For Music Recommender Systems, Sunny Shrestha Mar 2023

Design, Determination, And Evaluation Of Gender-Based Bias Mitigation Techniques For Music Recommender Systems, Sunny Shrestha

Electronic Theses and Dissertations

The majority of smartphone users engage with a recommender system on a daily basis. Many rely on these recommendations to make their next purchase, download the next game, listen to the new music or find the next healthcare provider. Although there are plenty of evidence backed research that demonstrates presence of gender bias in Machine Learning (ML) models like recommender systems, the issue is viewed as a frivolous cause that doesn’t merit much action. However, gender bias poses to effect more than half of the population as by default ML systems are designed to cater to a cisgender man. This …

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Hearing Healthcare Professionals’ Views About Over-The-Counter (Otc) Hearing Aids: Analysis Of Retrospective Survey Data, Vinaya Manchaiah, Anu Sharma, Hansapani Rodrigo, Abram Bailey, Karina C. De Sousa, De Wet Swanepoel Mar 2023

Hearing Healthcare Professionals’ Views About Over-The-Counter (Otc) Hearing Aids: Analysis Of Retrospective Survey Data, Vinaya Manchaiah, Anu Sharma, Hansapani Rodrigo, Abram Bailey, Karina C. De Sousa, De Wet Swanepoel

School of Mathematical & Statistical Sciences Faculty Publications

Over-the-counter hearing aids have been available to consumers in the US since 17 October 2022 following a ruling by the Food and Drug Administration. However, their reception by hearing healthcare professionals (HHP) has been mixed, and concerns have been expressed by many HHPs. The aim of this study was to examine the concerns that HHPs have towards over-the-counter (OTC) hearing aids. The study used a retrospective survey design. The survey data of HHPs (n = 730) was obtained from Hearing Tracker. A 22-item structured questionnaire was administered using a Question Scout platform. Descriptive analyses examined reported areas of concern and …

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Speed Of Sound For Hadronic And Quark Phases In A Magnetic Field, Efrain J. Ferrer, Aric Hackebill Mar 2023

Speed Of Sound For Hadronic And Quark Phases In A Magnetic Field, Efrain J. Ferrer, Aric Hackebill

Physics & Astronomy Faculty Publications

In this paper we calculate the speed of sound for three phases that may exist inside a magnetized hybrid neutron star at different density regions: A hadronic phase at low densities, quark-matter in the magnetic dual chiral density wave (MDCDW) phase at intermediate densities and a free-quark phase modeled by the MIT bag model at higher densities. It is found that the speed of sound exhibits a non-monotonic behavior, that goes from values smaller than the conformal limit ( c 2 s < 1 / 3 ) in the hadronic phase, to peak ( c 2 s > 1 / 3 ) in the MDCDW phase, to finally reach the conformal limit ( c 2 s …

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A Simple In Situ Method For Optimizing Settings For The Einzel Lens Elements In A Focused Ion Beam, Rich Swinford, Erik Sanchez Mar 2023

A Simple In Situ Method For Optimizing Settings For The Einzel Lens Elements In A Focused Ion Beam, Rich Swinford, Erik Sanchez

Physics Faculty Publications and Presentations

Ion beams have had an incredible impact on research in the past couple of decades. One major reason for this is the continued development of systems having optimal beam currents that allows one to image more clearly at different spot sizes to include higher currents that allow for faster milling. The advancements for Focused ion beam (FIB) columns have developed rapidly due to the computational optimization of lens designs. However, once a system has been produced, the optimal column settings for these lenses may change or simply become obscure. Our work involves regaining this optimization with the newly applied values …

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Separation Axioms In Neutrosophic Topological Spaces, Sudeep Dey, Gautam Chandra Ray Feb 2023

Separation Axioms In Neutrosophic Topological Spaces, Sudeep Dey, Gautam Chandra Ray

Neutrosophic Systems with Applications

In this article, we first establish some results based on single-valued neutrosophic sets. Next, we define a subspace topology in a neutrosophic topological space and investigate some properties. We then define the neutrosophic T0, T1, T2-spaces and study their various properties, offering adequate examples.

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Letter From The Vice President For Research, The Mcnair Team Feb 2023

Letter From The Vice President For Research, The Mcnair Team

McNair Scholars Research Journal

No abstract provided.

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Notes From The Director, The Mcnair Team Feb 2023

Notes From The Director, The Mcnair Team

McNair Scholars Research Journal

No abstract provided.

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Spectral Sensitivity Near Exceptional Points As A Resource For Hardware Encryption, Minye Yang, Liang Zhu, Qi Zhong, Ramy El-Ganainy, Pai Yen Chen Feb 2023

Spectral Sensitivity Near Exceptional Points As A Resource For Hardware Encryption, Minye Yang, Liang Zhu, Qi Zhong, Ramy El-Ganainy, Pai Yen Chen

Michigan Tech Publications, Part 1

The spectral sensitivity near exceptional points (EPs) has been recently explored as an avenue for building sensors with enhanced sensitivity. However, to date, it is not clear whether this class of sensors does indeed outperform traditional sensors in terms of signal-to-noise ratio. In this work, we investigate the spectral sensitivity associated with EPs under a different lens and propose to utilize it as a resource for hardware security. In particular, we introduce a physically unclonable function (PUF) based on analogue electronic circuits that benefit from the drastic eigenvalues bifurcation near a divergent exceptional point to enhance the stochastic entropy caused …

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A Clustering Linear Combination Method For Multiple Phenotype Association Studies Based On Gwas Summary Statistics, Meida Wang, Xuewei Cao, Shuanglin Zhang, Qiuying Sha Feb 2023

A Clustering Linear Combination Method For Multiple Phenotype Association Studies Based On Gwas Summary Statistics, Meida Wang, Xuewei Cao, Shuanglin Zhang, Qiuying Sha

Michigan Tech Publications, Part 1

There is strong evidence showing that joint analysis of multiple phenotypes in genome-wide association studies (GWAS) can increase statistical power when detecting the association between genetic variants and human complex diseases. We previously developed the Clustering Linear Combination (CLC) method and a computationally efficient CLC (ceCLC) method to test the association between multiple phenotypes and a genetic variant, which perform very well. However, both of these methods require individual-level genotypes and phenotypes that are often not easily accessible. In this research, we develop a novel method called sCLC for association studies of multiple phenotypes and a genetic variant based on …

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Scholarships, The Mcnair Team Feb 2023

Scholarships, The Mcnair Team

McNair Scholars Research Journal

No abstract provided.

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