Georgia Institute Of Technology Research Articles

Aviation-BERT-NER: Named Entity Recognition for Aviation Safety Reports

This work introduces Aviation-BERT-NER, a Named Entity Recognition (NER) system tailored for aviation safety reports, building on the Aviation-BERT base model developed at the Georgia Institute of Technology’s Aerospace Systems Design Laboratory. This system integrates aviation domain-specific data, including aircraft types, manufacturers, quantities, and aviation terminology, to identify named entities critical for aviation safety analysis. A key innovation of Aviation-BERT-NER is its template-based approach to fine-tuning, which utilizes structured datasets to generate synthetic training data that mirror the complexity of real-world aviation safety reports. This method significantly improves the model’s generalizability and adaptability, enabling rapid updates and customization to meet evolving domain-specific requirements. The development process involved careful data preparation, including the synthesis of entity types and the generation of labeled datasets through template filling. Testing on real-world narratives from the National Transportation Safety Board (NTSB) database highlighted Aviation-BERT-NER’s robustness, with a precision of 95.34%, recall of 94.62%, and F1 score of 94.78% when evaluated over 50 manually annotated (BIO tagged) paragraphs. This work addresses a critical gap in English language NER models for aviation safety, promising substantial improvements in the analysis and understanding of aviation safety reports.

Science, Environmental, Technology, Society Approach (SETS) in Improving Science Literacy of Junior High School Students

Science, Environmental, Technology, Society Approach (SETS) in Improving Science Literacy of Junior High School Students. This study aims to describe the implementation of science learning with the Science, Environmental, Technology, Society (SETS) approach, improving students' scientific literacy skills. This study uses a descriptive-quantitative research type with a group Pretest Posttest Design and involves 35 students of class VII-K SMP Negeri 1 Wonoayu as subjects. The research instrument is a science literacy test measured using the TOSLS Scientific Literacy indicators developed by Gormally from the Georgia Institute of Technology. The results showed a significant increase in students' scientific literacy with an N-Gain value of 0.74 which is included in the high category. In conclusion, the implementation of the SETS-Based Guided Inquiry Learning Model has proven effective in improving the scientific literacy of junior high school students.

Solidarity as subversion: Attempting climate justice practice within the Neoliberal University

The neoliberal higher education model has often co-opted efforts from justice-based movements to disrupt academic complicity in a capitalist and colonial system of exploitation. Higher education institutions have already begun looking to, and appropriating, language and ideas from the climate justice movement to perform a response to the injustices that have led to and resulted from the climate crisis. As one way of subverting this appropriation, this article articulates, and reflects on, a specific approach to the Vertically Integrated Program (VIP) model, an educational idea originally developed at the Georgia Institute of Technology where undergraduate students work as researchers with faculty and graduate students. The approach put forth in this article is one based on the experience of the authors in developing a VIP that aims to foster and practice a culture of solidarity with an organisation that is addressing the causes and effects of historical injustices facing the community from which it grew. The practice of solidarity at a time of climate crisis offers a potential solution, showing students that it can be used to break down the walls of higher education, to practice solidarity with those excluded outside of it, and to remind us all of our humanity.

Hidden Convexity, Optimization, and Algorithms on Rotation Matrices

This paper studies hidden convexity properties associated with constrained optimization problems over the set of rotation matrices [Formula: see text]. Such problems are nonconvex because of the constraint [Formula: see text]. Nonetheless, we show that certain linear images of [Formula: see text] are convex, opening up the possibility for convex optimization algorithms with provable guarantees for these problems. Our main technical contributions show that any two-dimensional image of [Formula: see text] is convex and that the projection of [Formula: see text] onto its strict upper triangular entries is convex. These results allow us to construct exact convex reformulations for constrained optimization problems over [Formula: see text] with a single constraint or with constraints defined by low-rank matrices. Both of these results are maximal in a formal sense. Funding: A. Ramachandran was supported by the H2020 program of the European Research Council [Grant 805241-QIP]. A. L. Wang was supported by the Nederlandse Organisatie voor Wetenschappelijk Onderzoek [Grant OCENW.GROOT.2019.015 (OPTIMAL)]. K. Shu was supported by the Georgia Institute of Technology (ACO-ARC fellowship).

Revisiting the small-world property of co-enrollment networks: A network analysis of hybrid course delivery strategies

Infectious disease outbreaks bring new challenges to campus operations at institutions of higher education (IHEs). At the beginning of the COVID-19 pandemic, as a precaution against COVID-19 transmission on their campuses, many IHEs shifted to entirely remote courses in the Spring 2020 semester. As these institutions prepared for the Fall 2020 semester, their administrations evaluated the extent to which remote courses should continue. While remote courses may reduce the number of students who interact on campus and thus mitigate the risk of disease spread, there may be academic and financial downsides. MethodologyUsing de-identified enrollment, course schedule, and student profile data from the Fall 2019 semester at Georgia Institute of Technology (Georgia Tech), we construct a co-enrollment network, which is a representation of student connections through courses. In this co-enrollment network, we observe the small-world property in which the average path length among reachable student pairs is short and nearly all students are connected to each other in the main component of the network through multiple independent paths. We also observe high connectivity between different majors. Then, we apply various hybrid instructional mode strategies to this co-enrollment network and use network connectivity and in-person instruction metrics to compare these strategies from health and academic perspectives, by their impacts on various groups of students, and based on the trade-off between reducing network connectivity and delivering in-person instruction. ResultsAlthough these strategies result in reduced network connectivity, they do not remove the small-world property. When comparing the strategies in terms of reducing network connectivity, we find three different strategy types to be the most favorable. Even under these strategies, the percentage of students with in-person courses that could be exposed rises quickly with initial infection rates. When comparing the strategies in terms of delivering in-person instruction, the most favorable strategies select a fixed percentage of courses for each subject to be delivered remotely. We then consider the impacts of these strategies on various groups of students to evaluate if there may be disparate impacts across these groups. In general, we find that strategies with more remote courses result in less disparate impacts on network connectivity and in-person instruction across these groups. In addition, we generally see less in-person instruction for lower-level students (i.e., first-year students and sophomores) compared to upper-level students. Regarding the trade-off between reducing network connectivity and delivering in-person instruction, the only strategy that is dominated under all scenarios in this study is the 1000s and 4000s only strategy, which keeps only the 1000- and 4000-level (i.e., first-year and senior level, respectively) courses in-person. The reason for this is that even though the university offers less in-person instruction due to this strategy's large quantity of remote courses, this strategy results in more connected networks because the 1000- and 4000-level courses tend to be large in size, the 1000-level courses are highly central, and the first-year students and seniors have high connectivity. ImportanceBy quantitatively comparing network connectivity and in-person instruction for these various strategies, campus administrators can weigh the physical health, academic performance, and mental health of students, along with the financial well-being of their academic institutions when responding to infectious disease outbreaks.

From approximate to exact integer programming

AbstractApproximate integer programming is the following: For a given convex body $$K \subseteq {\mathbb {R}}^n$$ K ⊆ R n , either determine whether $$K \cap {\mathbb {Z}}^n$$ K ∩ Z n is empty, or find an integer point in the convex body $$2\cdot (K - c) +c$$ 2 · ( K - c ) + c which is K, scaled by 2 from its center of gravity c. Approximate integer programming can be solved in time $$2^{O(n)}$$ 2 O ( n ) while the fastest known methods for exact integer programming run in time $$2^{O(n)} \cdot n^n$$ 2 O ( n ) · n n . So far, there are no efficient methods for integer programming known that are based on approximate integer programming. Our main contribution are two such methods, each yielding novel complexity results. First, we show that an integer point $$x^* \in (K \cap {\mathbb {Z}}^n)$$ x ∗ ∈ ( K ∩ Z n ) can be found in time $$2^{O(n)}$$ 2 O ( n ) , provided that the remainders of each component $$x_i^* \mod \ell $$ x i ∗ mod ℓ for some arbitrarily fixed $$\ell \ge 5(n+1)$$ ℓ ≥ 5 ( n + 1 ) of $$x^*$$ x ∗ are given. The algorithm is based on a cutting-plane technique, iteratively halving the volume of the feasible set. The cutting planes are determined via approximate integer programming. Enumeration of the possible remainders gives a $$2^{O(n)}n^n$$ 2 O ( n ) n n algorithm for general integer programming. This matches the current best bound of an algorithm by Dadush (Integer programming, lattice algorithms, and deterministic, vol. Estimation. Georgia Institute of Technology, Atlanta, 2012) that is considerably more involved. Our algorithm also relies on a new asymmetric approximate Carathéodory theorem that might be of interest on its own. Our second method concerns integer programming problems in equation-standard form $$Ax = b, 0 \le x \le u, \, x \in {\mathbb {Z}}^n$$ A x = b , 0 ≤ x ≤ u , x ∈ Z n . Such a problem can be reduced to the solution of $$\prod _i O(\log u_i +1)$$ ∏ i O ( log u i + 1 ) approximate integer programming problems. This implies, for example that knapsack or subset-sum problems with polynomial variable range$$0 \le x_i \le p(n)$$ 0 ≤ x i ≤ p ( n ) can be solved in time $$(\log n)^{O(n)}$$ ( log n ) O ( n ) . For these problems, the best running time so far was $$n^n \cdot 2^{O(n)}$$ n n · 2 O ( n ) .

Precursory elements of safety culture: Exploratory analyses of engineering students’ safety attitudes

Introduction: Safety culture as a concept has been well-researched in the literature. There is less work, however, on how individuals entering the workforce acquire and partake in safety culture over time and how they might be primed to partake in the positive elements of safety culture. Method: We begin this exploration by surveying engineering students’ attitudes toward safety and experiences with safety education at the Georgia Institute of Technology (n = 316). Results: We find disparities among engineering disciplines, where some majors have more negative views toward safety than others. This may point to the need for more [effective] safety education to prevent negative attitudes toward safety in the workplace. In addition to describing trends among engineering students’ attitudes, this study also uses factor analysis to characterize the latent constructs of precursory safety culture: the safety-related attitudes that may direct how people engage with safety culture as early-career engineers. Practical Applications: The analysis provides a conceptual construction of precursor safety culture attitudes, which can serve as a guide to future measurement efforts.

Editorial: Special Issue on Very High Cycle Fatigue

Abstract As the co-guest editors of the special issue of ASTM International’s journal Materials Performance and Characterization on very high cycle fatigue (VHCF), we are delighted to have this issue published by ASTM. Fatigue phenomena have long been a topic of significant interest and of research focusing on understanding the behavior of materials and structures under cyclic loading. However, the exploration of fatigue properties beyond traditional high cycle fatigue has gained substantial momentum in recent years. The VHCF regime, characterized by fatigue life exceeding 107 cycles, presents unique challenges and opportunities for advancing our understanding of fatigue mechanisms and developing robust design methodologies. This special issue brings together a collection of outstanding research articles that delve into various aspects of VHCF and contains 15 peer-reviewed articles (research and review) from researchers all around the globe (Asia, South and North America, and Europe). The published contributions encompass a broad range of materials, including metals and alloys, and employ diverse experimental, analytical, and computational techniques to investigate the behavior of structures subjected to VHCF loading. The research presented here not only enhances our fundamental knowledge of fatigue mechanisms but also provides practical insights for industrial applications such as aerospace, automotive, and additive manufacturing. We would like to sincerely thank all the authors who contributed to this special issue for their high-quality submissions, which greatly contribute to the advancement of this less-explored field. We also extend our acknowledgment to the Editor in Chief of the journal, Dr. Richard W. Neu (Georgia Institute of Technology), and the ASTM Publishing Manager, Ms. Alyssa Conaway. Without their invaluable help and support, it would have been impossible to publish this special issue. We hope this special issue enhances our knowledge and understanding in the field of fatigue, particularly VHCF, and serves as a reliable reference for students, researchers, and engineers working in this field. Co-guest editors Summer 2023

Dóri Pap and Susan Davis - Ideas to Serve: the Evolution of Social Innovation Education at GeorgiaTech

This letter delves into the transformation of social innovation education at the Georgia Institute of Technology (Georgia Tech) by exploring the evolution of its Ideas to Serve competition. Against the backdrop of Georgia Tech's vision for the next decade as an inclusive innovation hub, this narrative captures a conversation between Dori Pap, Managing Director, and Susan Davis, Practitioner in Residence at the Institute for Leadership and Social Impact. They discuss how the competition has evolved from fostering "heropreneurs" to empowering students to critically engage with systemic social issues. They present a compelling recap of how Georgia Tech has reimagined social innovation education by elevating community-based organizations as co-educators, inspiring students to become effective and empathetic social entrepreneurs.

Semi-supervised, Neural Network based approaches to face mask and anomaly detection in surveillance networks

In the post-pandemic world, surveillance cameras play a key aspect when it comes to detecting various kinds of security risks. These can range from burglars entering a premises to an individual wearing or not wearing a mask where convention dictates one way versus the other. We are proposing a system that would allow the autonomous detection of these security risks with minimal human intervention. We propose using Multi-task Cascaded Convolutional Neural Networks as the face detector, followed by a Gabor image feature extractor, and the Kernel-based Online Anomaly Detection algorithm for detecting and identifying potential risks in real-time. We have tested our proposed framework on five different datasets comprising two datasets from public online repositories, one publicly available dataset from the Georgia Institute of Technology, and two from real-life settings. We compared our results to the Viola Jones legacy face detector, and with two other anomaly detection algorithms based on Principal Component Analysis (PCA) and the Autoencoder scheme. Our proposed framework has yielded high detection rates with low false alarm rates, in addition to being adaptive, portable, and requiring minimal infrastructure.

Mastering Our Own Magic in the Evolution Toward Precision Practice.

Edelle (Edee) Field-Fote, PT, PhD, FASIA, FAPTA, the 54th Mary McMillan lecturer, is director of the Shepherd Center Spinal Cord Injury Research Program & Hulse Laboratory; professor in the division of physical therapy at Emory University School of Medicine; and professor of the practice in the school of biological sciences at the Georgia Institute of Technology. In her role as the director of spinal cord injury (SCI) research at Shepherd Center, Field-Fote leads a team dedicated to improving motor function in people with SCI through the development of neuromodulation and neurorehabilitation approaches informed by the latest neuroscience research and guided by outcomes that have meaning for people with SCI. With a clinical background as a physical therapist, PhD training in a preclinical model of SCI, and postdoctoral training in motor control physiology, her 25-plus years of SCI research have spanned the breadth of basic and clinical/translational research related to SCI. Dr Field-Fote has conducted randomized clinical trials with funding from the National Institutes of Health since 1997; other clinical trials in her lab have been funded by the Department of Defense, the National Institute on Disability Independent Living and Rehabilitation Research, and numerous foundations. Field-Fote is the recipient of multiple honors from the American Physical Therapy Association (APTA) and its components. She is a Fellow of APTA and a Fellow of the American Spinal Injury Association. She has also served in numerous APTA and APTA component appointed or elected positions and as a member and president of the Foundation for Physical Therapy Research Board of Trustees.

ECR Spotlight – Kristen Jakubowski

ECR Spotlight is a series of interviews with early-career authors from a selection of papers published in Journal of Experimental Biology and aims to promote not only the diversity of early-career researchers (ECRs) working in experimental biology during our centenary year but also the huge variety of animals and physiological systems that are essential for the ‘comparative’ approach. Kristen Jakubowski is an author on ‘ Non-linear properties of the Achilles tendon determine ankle impedance over a broad range of activations in humans’, published in JEB. Kristen conducted the research described in this article while a PhD candidate in Eric J. Perreault and Sabrina S. M. Lee's lab at Northwestern University, USA. She is now a Postdoctoral Fellow in the lab of Lena H. Ting and Gregory S. Sawicki at Emory University and Georgia Institute of Technology, USA, investigating an individual's neuromuscular control and their interactions with robotic devices and evaluating how devices can be designed and controlled to restore and augment human mobility.

Registration open and poster abstracts invited for Herty Medalist Undergraduate Research Symposium

The American Chemical Society Georgia Section will hold the 18th Herty Medalist Undergraduate Research Symposium (HMURS) Friday, Sept. 22, from 1:30 to 5:00 p.m. (EDT) at Georgia Gwinnett College in Lawrenceville, Georgia. HMURS was established in 2006 to showcase undergraduate research in chemistry. The 2023 Charles H. Herty Medalist, C. David Sherrill from the Georgia Institute of Technology, will be talking at this year’s symposium alongside other eminent scientists. A poster session for undergraduate students will follow the presentations. Registration and poster abstract submission are free and can be completed at commons.ggc.edu/hmurs/registration. The deadline for submitting poster abstracts is Sept. 1. The two best poster presenters will receive a $600 travel award to attend an ACS spring or fall meeting and 1 year of ACS membership. If you have any questions, please contact Ajay Mallia at amallia@ggc.edu.

ACS Catalysis Science and Technology Division awards to Fabio Ribeiro and Andrew J. Medford

Two awards from the American Chemical Society Division of Catalysis Science and Technology are being announced. Fabio Ribeiro , the R. Norris and Eleanor Shreve Professor of Chemical Engineering at Purdue University, is the 2023 recipient of the Exceptional Achievements in Catalysis award, in recognition of his exceptionally meritorious, impactful, and enduring scientific and leadership contributions to the broad field of catalysis science. Andrew J. “AJ” Medford , an assistant professor of chemical and biomolecular engineering at the Georgia Institute of Technology, is the 2023 recipient of the Early Career in Catalysis award. This award recognizes independent contributions to the broad field of catalysis science that are of unusual merit and creativity in the early stages of a career.

Performance Comparison of Helium and sCO2 as Coolants for Modular Finger-Type Divertors

Several studies at the Georgia Institute of Technology have evaluated the thermal and fluids performance of the helium-cooled modular divertor with multiple jets (HEMJ) over the past decade. This finger-type divertor was studied both experimentally at nearly prototypical conditions and numerically at fully prototypical operating conditions using experimentally validated simulations. Recently, supercritical carbon dioxide (sCO2) has been studied as the primary coolant in power cycles and other applications in various systems, in part because CO2 achieves the high densities typical of supercritical fluids at relatively low temperatures and pressures, with a critical point of (7.38 MPa, 31°C). This density makes it possible to realize very compact and efficient sCO2 power cycles. The feasibility of sCO2 as a coolant for plasma-facing components, specifically the divertor, was therefore evaluated as part of the Fusion Energy System Studies design study activities. This work compares the thermal-fluid performance of helium and sCO2 in the HEMJ divertor geometry using numerical simulations at prototypical conditions: inlet temperatures Ti = 600°C to 700°C, pressures p ≈ 10 MPa, and steady-state incident heat fluxes on the tile q″ < 17 MW/m2. The performance is quantified here as the maximum heat flux that can be accommodated by the plasma-facing tile, the pumping power fraction, defined as the ratio of the coolant pumping power to the incident thermal power, and the operating stress limits based on ASME pressure vessel criteria. As expected, helium requires lower mass flow rates and pumping power fractions within imposed maximum temperature limits for the HEMJ pressure boundary. However, it also appears that neither helium nor sCO2 can remove 10 MW/m2 of incident heat flux while meeting ASME pressure vessel criteria. Finally, the numerical modeling reveals that sCO2 may remove slightly higher incident heat fluxes than helium due to the imposed stress limits due to the sCO2 coolant resulting in smaller local temperature gradients, albeit at a considerably higher pumping power fraction.

Electric-thermal energy storage using solid particles as storage media

Jeffrey Gifford is a PhD Candidate in the Advanced Energy Systems program sponsored by National Renewable Energy Laboratory (NREL) and the Colorado School of Mines. He previously earned his M. and BS in Mechanical Engineering from the University of Colorado – Boulder and Purdue University, respectively, and has worked at NREL as a graduate researcher. His research interests include energy storage systems for economy-wide decarbonization and long-duration, particle-based thermal energy storage systems using a multi-method approach, including computational fluid dynamics, dynamic integrated system modeling, and mixed-integer linear programming for design and dispatch optimization. Janna Martinek is a researcher in the Thermal Energy Systems group at the National Renewable Energy Laboratory (NREL). She received her PhD in Chemical Engineering from the University of Colorado – Boulder prior to joining NREL. Her work includes predictive performance modeling and analysis of concentrating solar power (CSP), solar thermochemical and thermal energy storage (TES) systems, computational fluid dynamics modeling, and analysis of dispatch optimization and grid integration of CSP and TES technologies. Xingchao Wang is a joint appointment researcher to the National Renewable Energy Laboratory (NREL). He is a research faculty of the Mechanical Engineering Department at Colorado School of Mines. Dr. Wang received his PhD in Mechanical Engineering from Lehigh University and BE in Thermal Engineering from Tsinghua University. His expertise lies in heat transfer, thermodynamics, and conventional and renewable energy systems designing and modeling. He is working on energy conversion, storage research, and technology development using renewable energy sources. Zhiwen Ma is a senior engineer in the Thermal Systems R&D Group at National Renewable Energy Laboratory (NREL). He received his PhD in Mechanical Engineering from the Georgia Institute of Technology. Zhiwen is leading the research projects on long-duration energy storage using particle-based thermal energy storage, thermal and electrochemical modeling for hydrogen production, and solar fuel processes. He has expertise in computational modeling and experimental testing, renewable solution and system development, component performance, and cost analysis. He has published over 70 peer-reviewed papers and was awarded 12 patents. Jeffrey Gifford is a PhD Candidate in the Advanced Energy Systems program sponsored by National Renewable Energy Laboratory (NREL) and the Colorado School of Mines. He previously earned his M. and BS in Mechanical Engineering from the University of Colorado – Boulder and Purdue University, respectively, and has worked at NREL as a graduate researcher. His research interests include energy storage systems for economy-wide decarbonization and long-duration, particle-based thermal energy storage systems using a multi-method approach, including computational fluid dynamics, dynamic integrated system modeling, and mixed-integer linear programming for design and dispatch optimization. Janna Martinek is a researcher in the Thermal Energy Systems group at the National Renewable Energy Laboratory (NREL). She received her PhD in Chemical Engineering from the University of Colorado – Boulder prior to joining NREL. Her work includes predictive performance modeling and analysis of concentrating solar power (CSP), solar thermochemical and thermal energy storage (TES) systems, computational fluid dynamics modeling, and analysis of dispatch optimization and grid integration of CSP and TES technologies. Xingchao Wang is a joint appointment researcher to the National Renewable Energy Laboratory (NREL). He is a research faculty of the Mechanical Engineering Department at Colorado School of Mines. Dr. Wang received his PhD in Mechanical Engineering from Lehigh University and BE in Thermal Engineering from Tsinghua University. His expertise lies in heat transfer, thermodynamics, and conventional and renewable energy systems designing and modeling. He is working on energy conversion, storage research, and technology development using renewable energy sources. Zhiwen Ma is a senior engineer in the Thermal Systems R&D Group at National Renewable Energy Laboratory (NREL). He received his PhD in Mechanical Engineering from the Georgia Institute of Technology. Zhiwen is leading the research projects on long-duration energy storage using particle-based thermal energy storage, thermal and electrochemical modeling for hydrogen production, and solar fuel processes. He has expertise in computational modeling and experimental testing, renewable solution and system development, component performance, and cost analysis. He has published over 70 peer-reviewed papers and was awarded 12 patents.

Herty Medal goes to David Sherrill

The 2023 Charles H. Herty Medal goes to C. David Sherrill , Regents’ Professor in the Schools of Chemistry and Biochemistry and Computational Science and Engineering at Georgia Institute of Technology. This medal is awarded annually by the American Chemical Society Georgia Section to recognize the work and service of an outstanding chemist from the southeastern region of the US. The focus of Sherrill’s research is the development and application of theoretical methods and algorithms in computational quantum chemistry. He is a fellow of ACS, the American Association for the Advancement of Science, and the American Physical Society. Sherrill is an associate editor of the Journal of Chemical Physics and was recently elected to the board of the World Association of Theoretical and Computational Chemists. He is very active in ACS both nationally and in the Georgia Section. The gold Herty Medal will be presented to Sherrill at the 89th

ECR Spotlight – Jennifer Leestma

ECR Spotlight is a series of interviews with early-career authors from a selection of papers published in Journal of Experimental Biology and aims to promote not only the diversity of early-career researchers (ECRs) working in experimental biology during our centenary year but also the huge variety of animals and physiological systems that are essential for the ‘comparative’ approach. Jennifer Leestma is an author on ‘ Linking whole-body angular momentum and step placement during perturbed walking’, published in JEB. Jennifer is a PhD candidate in the lab of Gregory Sawicki and Aaron Young at Georgia Institute of Technology, USA, investigating how humans navigate complex and dynamic environments and how wearable robots can augment locomotion in these contexts.

Autobiography of Paul L. Houston.

ADVERTISEMENT RETURN TO ISSUEPREVSpecial Issue Prefac...Special Issue PrefaceNEXTAutobiography of Paul L. HoustonPaul L. Houston*Paul L. HoustonDepartment of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14850, United StatesDepartment of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30332, United States*[email protected]More by Paul L. Houstonhttps://orcid.org/0000-0003-2566-9539Cite this: J. Phys. Chem. A 2023, 127, 9, 2065–2067Publication Date (Web):March 9, 2023Publication History Received26 January 2023Published online9 March 2023Published inissue 9 March 2023https://doi.org/10.1021/acs.jpca.3c00580Copyright © Published 2023 by American Chemical SocietyRIGHTS & PERMISSIONSArticle Views139Altmetric-Citations-LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (1 MB) Get e-AlertsSupporting Info (3)»Supporting Information Supporting Information SUBJECTS:Aldehydes,Imaging,Lasers,Photodissociation,Students Get e-Alerts

NIH/NIBIB Introduces New Center for Biomedical Engineering Technology Acceleration.

In Late January 2023, the National Institute of Biomedical Imaging and Bioengineering (NIBIB) launched a new center designed to accelerate biomedical discovery and therapeutics, in part by pulling together expert, multidisciplinary teams from throughout the National Institutes of Health (NIH) to quickly respond when national or global health crises strike. The inaugural director of this Center for BME Technology Acceleration, or BETA Center, is biomedical engineer Manu Platt, Ph.D., (Figure 1) who is also taking on the role of NIBIB associate director for scientific diversity, equity, and inclusion. Platt previously held appointments as professor, Wallace H. Coulter distinguished faculty fellow, and diversity director of the Center on Emergent Behaviors of Integrated Cellular Systems and Cellular Manufacturing and Technologies at the Georgia Institute of Technology and Emory University.