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arXiv 2024年

作者： Khwaja, Emaad Rashwan, Abdullah Chen, Ting Wang, Oliver Kothawade, Suraj Li, Yeqing UC Berkeley UCSF Joint Bioengineering Graduate Program United States Computer Science Division UC Berkeley United States Google United States Google Deepmind United Kingdom

We present a one-shot text-to-image diffusion model that can generate high-resolution images from natural language descriptions. Our model employs a layered U-Net architecture that simultaneously synthesizes images at multiple resolution scales. We show that this method outperforms the baseline of synthesizing images only at the target resolution, while reducing the computational cost per step. We demonstrate that higher resolution synthesis can be achieved by layering convolutions at additional resolution scales, in contrast to other methods which require additional models for super-resolution synthesis. © 2024, CC BY.

关键词： Diffusion

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Superhydrophobic fluoride conversion coating on bioresorbable magnesium alloy——fabrication,characterization,degradation and cytocompatibility with BMSCs

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Journal of Magnesium and Alloys 2021年第4期9卷 1252-1266页

作者： Chunyan Zhanga Shiyu Zhang Dongwei Sun Jiajia Lin Fancheng Meng Huinan Liu School of Materials Science&Engineering Chongqing University of TechnologyNo.69 Hongguang AvenueChongqing 400054China Department of Bioengineering and the Materials Science and Engineering ProgramUniversity of CaliforniaRiverside900 University AvenueMSE 205RiversideCA 92521USA

A micro-nano structure CaF_(2)chemical conversion layer was prepared on fluoride-treated AZ31 alloy,then the composite fluoride conversion film(CaF_(2)/MgF_(2))was modified by stearic acid(SA)and fabricated a superhydrophobic *** fluoride-treated magnesium,fluoride conversion film and superhydrophobic coating were characterized by SEM,EDS,XRD and *** properties of coatings1 adhesion and corrosion resistance were evaluated via tape test and electrochemical *** cytocompatibility of the MgF_(2),CaF_(2)and superhydrophobic CaF_(2)/SA surface was investigated with bone marrow-derived mesenchymal stem cells(BMSCs)by direct culture for 24 *** results showed that the superhydrophobic fluoride conversion coating composed of inner MgF_(2)layer and the outer CaF_(2)/SA composite layer had an average water contact angle of 152°.SA infiltrated into the micro-nano structure CaF_(2)layer and formed a strong adhesion with CaF_(2)***,the super-hydrophobic coating showed higher barrier properties and corrosion resistance compared with the fluoride conversion film and fluoride-treated AZ31 *** BMSC adhesion test results demonstrated MgF_(2)CaF_(2)and CaF_(2)/SA coatings were all nontoxic to *** the condition of in direct contact with cells,MgF_(2)showed higher cell density and enhanced the BMSCs proliferation,while CaF_(2)and CaF_(2)/SA coating showed no statistically difference in cell density compared with glass reference but the CaF_(2)and CaF_(2)/SA coating were not conducive to BMSCs adhesion.

关键词： Biodegradable Magnesium alloy Superhydrophobic Fluoride conversion film Cytocompatibility

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Spectral DiffuserScope - Computational Snapshot Hyperspectral Imager for Microscopy

Spectral DiffuserScope - Computational Snapshot Hyperspectra...

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2023 Computational Optical Sensing and Imaging, COSI 2023 in Optica Imaging Congress - Part of Imaging and Applied Optics Congress 2023

作者： Aggarwal, Neerja Markley, Eric Raniwala, Yashovardhan Houck, William D. Lee, Kyung Chul Bae, Junghyun Baek, Nakkyu Park, Wook Lee, Seung Ah Waller, Laura Department of Electrical Engineering and Computer Sciences University of California Berkeley United States UCB/UCSF Joint Graduate Program in Bioengineering University of California Berkeley United States VIAVI Solutions Inc Santa Rosa United States School of Electrical and Electronic Engineering Yonsei University Seoul Korea Republic of

We introduce a computational snapshot hyperspectral imager for benchtop microscopy. The compact device uses a diffuser and spectral filter array to multiplex spatio-spectral information into a 2D measurement, then rec... 详细信息

ISBN: (纸本)9781957171289

关键词： Blue light emitting diodes Diffusers Fluorescence microscopy Image sensors Spatial resolution Ultraviolet light emitting diodes

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DEVELOPING A DIGITAL TWIN FOR SINGLE-CELL MECHANICAL PHENOTYPING MICROFLUIDIC DEVICES 26

DEVELOPING A DIGITAL TWIN FOR SINGLE-CELL MECHANICAL PHENOTY...

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26th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2022

作者： Roychowdhury, Sayan Mahmud, Samreen T. Puleri, Daniel F. Lai, Andre Rex, Rachel Li, Brian Sohn, Lydia L. Randles, Amanda Department of Biomedical Engineering Duke University United States UC Berkeley-UC San Francisco Graduate Program in Bioengineering University of California Berkeley United States Department of Mechanical Engineering University of California Berkeley United States

ISBN: (纸本)9781733419048

Microfluidics can be used to characterize individual cells in a population based on their mechanical traits. In this work, we digitally replicate the microfluidic device developed by Li et al. [1] and perform simulations of a representative AP-1060 cell. We show that the numerical model is able to recover whole-cell deformability index, a metric used to quantify the resistance of cells to compressive deformation, within 3% of the experimental average. These results pave the way for future studies which utilize experimental and computational approaches to optimize geometric design parameters, complement signal analysis, and enhance the acquisition of mechanical information. © 2022 MicroTAS 2022 - 26th International Conference on Miniaturized Systems for Chemistry and Life Sciences. All rights reserved.

关键词： Fluid structure interaction

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Polymeric nanomaterials in 3D bioprinting for tissue engineering and drug delivery applications

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Bioprinting 2024年 40卷

作者： Han, Sarang Fisher, John P. Mikos, Antonios G. Hogan, Katie J. Department of Bioengineering Rice University Houston 77030 TX United States Baylor College of Medicine Medical Scientist Training Program Houston 77030 TX United States Fischell Department of Bioengineering University of Maryland College Park 20742 MD United States

Nanoparticles have been broadly investigated in 3D bioprinting (3DBP) for various purposes, including drug delivery, enhanced mechanical performance, biocompatibility, and bioactivity. While polymeric nanoparticles have been widely studied for functionalization and drug delivery purposes, current reviews lack investigation of their application for 3DBP, where polymeric nanoparticles can also add unique properties in composition and application for 3DBP. Both natural and synthetic polymeric nanoparticles have been employed in 3DBP, with natural polymers providing a strong advantage for biocompatibility and bioactivity and synthetic polymers enabling more control over nanomaterial properties. In 3D printed structures, the colloidal network between polymeric nanoparticles can enhance rheological and mechanical properties and printability. Additionally, these nanomaterials may introduce stimuli responsive elements and deliver key biomolecules, including growth factors or medications. This paper discusses the current application of polymeric nanoparticles and highlights their potential in 3DBP for tissue engineering and drug delivery specifically. © 2024 Elsevier B.V.

关键词： 3D bioprinting Drug delivery Polymeric nanomaterials Tissue engineering

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The Impact of Cashless Payment in Application-Based Transportation on Gen Z User Behavior in Jakarta

The Impact of Cashless Payment in Application-Based Transpor...

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2023 International Conference on IT Innovation and Knowledge Discovery, ITIKD 2023

作者： Christian, Michael Yulita, Henilia Girsang, Lasmery Rm Wibowo, Suryo Indriyarti, Eko Retno Sunarno, Sunarno Management Universitas Bunda Mulia Jakarta Indonesia Universitas Bunda Mulia Communication Studies Jakarta Indonesia Biomedical and Bioengineering Indonesia International for Life Sciences Jakarta Indonesia Universitas Trisakti Faculty of Economics and Business Jakarta Indonesia Universitas Persada Indonesia Yai Psychological Science Doctoral Program Jakarta Indonesia

ISBN: (纸本)9781665463720

Many industrial sectors, including transportation, have seen a series of adjustments or changes because of technological advancements. The traditional mode of transportation, particularly on land, is now application-based. This provides several advantages, including flexibility, convenience, speed, and security. This is also influencing payment methods for these app-based transportation services. Transportation service providers, including one of them, continue to promote the use of this cashless method through promotion or a loyalty point program for service users. This is undeniably appealing to its users, particularly those born after the year 2000. The purpose of this study is to examine the behavior of users who switch to cashless payment methods and the impact on their behavior. Using SmartPLS 3.0 structural modeling and 120 participants in Jakarta, we used application-based transportation services from generation Z. According to the findings of this study, four hypotheses are accepted and three are rejected. This study specifically explains that switching costs have a significant impact on switching decisions. Furthermore, this study demonstrates that the decision to switch has a significant impact on user satisfaction. User satisfaction is significantly influenced by attitude promotion. According to the study's other findings, attitude toward promotion does not moderate the effect of switching costs on switching decisions. The limitations of this study stem from the use of variables that only use transitional forming factors, and satisfaction is based solely on attitude variables and transitional drivers from the promotion aspect. Meanwhile, other variables such as price competition from application-based transportation service providers or the number of competitors may have a different impact, enriching the study's findings. Another suggestion for future research is to cover research areas with sample sizes from different generations. © 2023 IEEE.

关键词： Competition

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Understanding Incoming bioengineering Student Perceptions About Mental Health and Wellness

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Biomedical Engineering Education 2023年第1期4卷 57-72页

作者： Miller, Isabel Golecki, Holly Jensen, Karin Department of Bioengineering University of Illinois Urbana-Champaign Urbana USA Department of Biomedical Engineering University of Michigan Ann Arbor USA Engineering Education Research Program University of Michigan Ann Arbor USA

Mental health is a rising concern in higher education, with increasing numbers of students experiencing mental health challenges. Stress is a common experience for undergraduate students and the first semester of college can be especially stressful for students as they navigate new coursework and surroundings and being without familiar supports. Simultaneously, engineering students report high workloads and competition that may exacerbate stress. Narratives of extreme resilience required for success in engineering may negatively impact student perceptions about norms of stress and how students care for their mental health and wellness. In order to best support students, we need to understand how students approach taking care of their mental health and wellness to inform curriculum and resources provided to students. In this study, we sought to understand how first-semester bioengineering students approached caring for their mental health and wellness and how these perceptions may be influenced by perceptions of engineering culture. Towards accomplishing these goals we measured (1) how students cope with stress, (2) whether they planned to use campus wellness resources, and (3) perceived barriers to mental health care. Students in a first-semester bioengineering course were surveyed during the second week of their first semester. Most students reported at least one coping mechanism for high stress and the most commonly reported mechanism was talking with peers. Only about 35% of students indicated that they would be likely to use campus wellness resources, often citing that limited time prevented them from doing so. While perceived barriers to mental health care were low on average, some students (between 5 and 10.5%) rated these barriers as severe. Students who rated barriers as severe most commonly held beliefs that mental health supports on campus, such as counseling centers, would not be effective. Engineering identity scores for students surveyed in this study w

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Intelligent reflux and suction detection system for ventricular assist devices: in silico study

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Research on Biomedical Engineering 2025年第1期41卷 1-23页

作者： Santos, Bruno J. Cestari, Idágene A. Biomedical Engineering Graduate Program Polythecnic School of Engineering University of Sao Paulo Av. Prof. Luciano Gualberto Travessa 3 nº380 Sao Paulo05508-010 Brazil Department of Information Technology of Universidade São Judas Tadeu Rua Taquari nº546 Sao Paulo03166-000 Brazil Faculdade de Medicina Bioengineering Division - Heart Institute Hospital das Clinicas HCFMUSP Universidade de Sao Paulo LIM Bioengenharia Sao Paulo Sao Paulo Brazil

Introduction: Left ventricular assist devices (LVADs) serve both as a bridge to transplantation and as destination therapy for the treatment of congestive heart failure (CHF). However, the inability of the existing control strategies to automatically adapt LVAD flow according to hemodynamic changes can significantly impact patient survival and quality of life. Physiological control strategies for LVAD show promising results, with reflux and suction detection (RSD) increasing device safety. Methods: This study presents in silico results of an RSD system based on measurements of inlet and outlet pressures in continuous-flow LVAD. Two strategies were used to investigate control feasibility, safety, and adjustments to nonlinear variations and comprehensively assess the system’s state considering a structured algorithm (SA) and ensembles of AI models (eAIm): K-nearest neighbors (KNN), support vector machine (SVM), and artificial neural network (ANN). Results: The SA submodule achieved an accuracy of 99.66% in suction detection but showed limitations in reflux events, with 80.04% accuracy and an F1-Score of 70.4%. The KNN and SVM models demonstrated performance exceeding 96% for both events, exhibiting more excellent stability than the SA submodule. The ANN excelled with low variability and an RMSE of 0.07 in R1, though its suction accuracy (96.7%) was slightly lower than for reflux (99.48%). The KNN was the most effective model, achieving 99.66% accuracy in suction and 98.44% in reflux. The SVM also produced competitive results but with variability across evaluations. The eAIm model showed satisfactory precision (97.78% for suction and 97.14% for reflux), with variations depending on the scenario. The eAIm is recommended for optimization in precision-critical situations. Discussion: These strategies are designed to fulfill the proposal’s feasibility, flexibility, and safety requirements. They address the challenges of achieving consistent reproduction using an SA and the

关键词： Left ventricular assist devices

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Longmambattn: A Novel Architecture for Enhanced Breast Cancer Risk Prediction Using Variable-Length Longitudinal Mammograms

Longmambattn: A Novel Architecture for Enhanced Breast Cance...

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IEEE International Symposium on Biomedical Imaging

作者： Zhengbo Zhou Dooman Arefan Margarita Zuley Jules Sumkin Shandong Wu Intelligent Systems Program University of Pittsburgh Pittsburgh PA USA Department of Radiology University of Pittsburgh Pittsburgh PA USA Department of Biomedical Informatics and Department of Bioengineering University of Pittsburgh Pittsburgh PA USA

ISBN: (数字)9798331520526

ISBN: (纸本)9798331520533

Recent advancements in deep learning have shown significant potential in predicting breast cancer risk from mammograms. While leveraging longitudinal changes in mammograms is crucial for accurate risk prediction, existing models often face limitations in capturing these temporal relationships effectively, and they tend to be computationally intensive. To address these challenges, we introduce LongMambAttn, a novel architecture designed to handle variable-length, multitemporal mammograms, thereby enhancing breast cancer risk prediction accuracy. LongMambAttn models the temporal changes of mammograms taken over periods ranging from 1 to 8 years. In an internal case-control dataset of 590 patients, our model demonstrates superior performance in predicting future cancer incidence, surpassing methods that rely only on the most recent prior mammogram as well as other models that incorporate mammograms taken at varying time intervals. Our results show that incorporating longitudinal mammograms via LongMambAttn leads to improved predictive accuracy for breast cancer risk.

关键词： Deep learning Accuracy Computational modeling Biological system modeling Computer architecture Predictive models Mammography Breast cancer Distance measurement Faces

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Resistant to Technology and Digital Banking Behavior Among Jakarta's Generation Z

Resistant to Technology and Digital Banking Behavior Among J...

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2023 International Conference on IT Innovation and Knowledge Discovery, ITIKD 2023

作者： Christian, Michael Yulita, Henilia Yuniarto, Yustinus Wibowo, Suryo Indriyarti, Eko Retno Sunarno, Sunarno Management Universitas Bunda Mulia Jakarta Indonesia Universitas Bunda Mulia Communication Studies Jakarta Indonesia Biomedical and Bioengineering Indonesia International for Life Sciences Jakarta Indonesia Universitas Trisakti Faculty of Economics and Business Jakarta Indonesia Universitas Persada Indonesia Yai Psychological Science Doctoral Program Jakarta Indonesia

ISBN: (纸本)9781665463720

When sophisticated technology is integrated into digital banking services with the goal of providing customers with an easy, fast, safe, and enjoyable experience, then details about customer behavior when receiving services are based on this sophisticated technology. Therefore, the goal of this study is to investigate how ease of use, usefulness, security, and self-efficacy affect resistance to technology or behavior when using digital banks among Jakarta's generation Z. In this quantitative study, partial least-square structural equation modeling (PLS-SEM) is used. Specifically, SmartPLS 3.0 is used to analyze the data collected from 157 participants. According to the findings of this study, participants consider the factor of resistance to digital banking technology to be more important than the impact on usage behavior. Issues related to security are also an important factor for customers when using technology such as digital banking services. Notably, the limitation of this research is that it does not use aspects of the technology used in each digital banking service. Furthermore, comparing users from different generations can help to improve the findings of this study. © 2023 IEEE.

关键词： Sales

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