College of Sciences Faculty Research
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12588/257
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Item Development of Aptamers for RNase Inactivation in Xtract-Free™ Sample Collection and Transport Medium(MDPI, 2024-06-07) Daum, Luke T.; Rodriguez, John D.; Chambers, James P.There is a significant need to develop new environmentally friendly, extraction-free sample collection mediums that can effectively preserve and protect genetic material for point-of-care and/or self-collection, home-collection, and mail-back testing. Systematic evolution of ligands by exponential enrichment (SELEX) was used to create anti-ribonuclease (RNase) deoxyribonucleic acid (DNA) aptamers against purified RNase A conjugated to paramagnetic carboxylated beads. Following eight rounds of SELEX carried out under various stringency conditions, e.g., selection using Xtract-Free™ (XF) specimen collection medium and elevated ambient temperature of 28 °C, a panel of five aptamers was chosen following bioinformatic analysis using next-generation sequencing. The efficacy of aptamer inactivation of RNase was assessed by monitoring ribonucleic acid (RNA) integrity via fluorometric and real-time RT-PCR analysis. Inclusion of aptamers in reaction incubations resulted in an 8800- to 11,200-fold reduction in RNase activity, i.e., digestion of viral RNA compared to control. Thus, anti-RNase aptamers integrated into XF collection medium as well as other commercial reagents and kits have great potential for ensuring quality intact RNA for subsequent genomic analyses.Item Current Progress in the Science of Novel Adjuvant Nano-Vaccine-Induced Protective Immune Responses(MDPI, 2024-05-23) Saleemi, Mansab Ali; Zhang, Yan; Zhang, GuoquanVaccinations are vital as they protect us from various illness-causing agents. Despite all the advancements in vaccine-related research, developing improved and safer vaccines against devastating infectious diseases including Ebola, tuberculosis and acquired immune deficiency syndrome (AIDS) remains a significant challenge. In addition, some of the current human vaccines can cause adverse reactions in some individuals, which limits their use for massive vaccination program. Therefore, it is necessary to design optimal vaccine candidates that can elicit appropriate immune responses but do not induce side effects. Subunit vaccines are relatively safe for the vaccination of humans, but they are unable to trigger an optimal protective immune response without an adjuvant. Although different types of adjuvants have been used for the formulation of vaccines to fight pathogens that have high antigenic diversity, due to the toxicity and safety issues associated with human-specific adjuvants, there are only a few adjuvants that have been approved for the formulation of human vaccines. Recently, nanoparticles (NPs) have gain specific attention and are commonly used as adjuvants for vaccine development as well as for drug delivery due to their excellent immune modulation properties. This review will focus on the current state of adjuvants in vaccine development, the mechanisms of human-compatible adjuvants and future research directions. We hope this review will provide valuable information to discovery novel adjuvants and drug delivery systems for developing novel vaccines and treatments.Item Characterization of Excited-State Electronic Structure in Diblock π-Conjugated Oligomers with Adjustable Linker Electronic Coupling(MDPI, 2024-06-05) Gobeze, Habtom B.; Younus, Muhammed; Turlington, Michael D.; Ahmed, Sohel; Schanze, Kirk S.Diblock conjugated oligomers are π-conjugated molecules that contain two segments having distinct frontier orbital energies and HOMO-LUMO gap offsets. These oligomers are of fundamental interest to understand how the distinct π-conjugated segments interact and modify their excited state properties. The current paper reports a study of two series of diblock oligomers that contain oligothiophene (Tn) and 4,7-bis(2-thienyl)-2,1,3-benzothiadiazole (TBT) segments that are coupled by either ethynyl (-C≡C-) or trans-(-C≡C-)2Pt(II)(PBu3)2 acetylide linkers. In these structures, the Tn segment is electron rich (donor), and the TBT is electron poor (acceptor). The diblock oligomers are characterized by steady-state and time-resolved spectroscopy, including UV-visible absorption, fluorescence, fluorescence lifetimes, and ultrafast transient absorption spectroscopy. Studies are compared in several solvents of different polarity and with different excitation wavelengths. The results reveal that the (-C≡C-) linked oligomers feature a delocalized excited state that takes on a charge transfer (CT) character in more polar media. In the (-C≡C-)2Pt(II)(PBu3)2-linked oligomers, there is weak coupling between the Tn and TBT segments. Consequently, short wavelength excitation selectively excites the Tn segment, which then undergoes ultrafast energy transfer (~1 ps) to afford a TBT-localized excited state.Item A Standardized Nomenclature Design for Systematic Referencing and Identification of Animal Cellular Material(MDPI, 2024-05-23) Schrade, Lisa; Mah, Nancy; Bandrowski, Anita; Chen, Ying; Dewender, Johannes; Diecke, Sebastian; Hiepen, Christian; Lancaster, Madeline A.; Marques-Bonet, Tomas; Martinez, Sira; Mueller, Sabine C.; Navara, Christopher; Prigione, Alessandro; Seltmann, Stefanie; Sochacki, Jaroslaw; Sutcliffe, Magdalena A.; Zywitza, Vera; Hildebrandt, Thomas B.; Kurtz, AndreasThe documentation, preservation and rescue of biological diversity increasingly uses living biological samples. Persistent associations between species, biosamples, such as tissues and cell lines, and the accompanying data are indispensable for using, exchanging and benefiting from these valuable materials. Explicit authentication of such biosamples by assigning unique and robust identifiers is therefore required to allow for unambiguous referencing, avoid identification conflicts and maintain reproducibility in research. A predefined nomenclature based on uniform rules would facilitate this process. However, such a nomenclature is currently lacking for animal biological material. We here present a first, standardized, human-readable nomenclature design, which is sufficient to generate unique and stable identifying names for animal cellular material with a focus on wildlife species. A species-specific human- and machine-readable syntax is included in the proposed standard naming scheme, allowing for the traceability of donated material and cultured cells, as well as data FAIRification. Only when it is consistently applied in the public domain, as publications and inter-institutional samples and data are exchanged, distributed and stored centrally, can the risks of misidentification and loss of traceability be mitigated. This innovative globally applicable identification system provides a standard for a sustainable structure for the long-term storage of animal bio-samples in cryobanks and hence facilitates current as well as future species conservation and biomedical research.Item Improving the Concrete Crack Detection Process via a Hybrid Visual Transformer Algorithm(MDPI, 2024-05-20) Shahin, Mohammad; Chen, F. Frank; Maghanaki, Mazdak; Hosseinzadeh, Ali; Zand, Neda; Khodadadi Koodiani, HamidInspections of concrete bridges across the United States represent a significant commitment of resources, given their biannual mandate for many structures. With a notable number of aging bridges, there is an imperative need to enhance the efficiency of these inspections. This study harnessed the power of computer vision to streamline the inspection process. Our experiment examined the efficacy of a state-of-the-art Visual Transformer (ViT) model combined with distinct image enhancement detector algorithms. We benchmarked against a deep learning Convolutional Neural Network (CNN) model. These models were applied to over 20,000 high-quality images from the Concrete Images for Classification dataset. Traditional crack detection methods often fall short due to their heavy reliance on time and resources. This research pioneers bridge inspection by integrating ViT with diverse image enhancement detectors, significantly improving concrete crack detection accuracy. Notably, a custom-built CNN achieves over 99% accuracy with substantially lower training time than ViT, making it an efficient solution for enhancing safety and resource conservation in infrastructure management. These advancements enhance safety by enabling reliable detection and timely maintenance, but they also align with Industry 4.0 objectives, automating manual inspections, reducing costs, and advancing technological integration in public infrastructure management.Item The Dolan Fire of Central Coastal California: Burn Severity Estimates from Remote Sensing and Associations with Environmental Factors(MDPI, 2024-05-10) Oseghae, Iyare; Bhaganagar, Kiran; Mestas-Nuñez, Alberto M.In 2020, wildfires scarred over 4,000,000 hectares in the western United States, devastating urban populations and ecosystems alike. The significant impact that wildfires have on plants, animals, and human environments makes wildfire adaptation, management, and mitigation strategies a critical task. This study uses satellite imagery from Landsat to calculate burn severity and map the fire progression for the Dolan Fire of central Coastal California which occurred in August 2020. Several environmental factors, such as temperature, humidity, fuel type, topography, surface conditions, and wind velocity, are known to affect wildfire spread and burn severity. The aim of this study is the investigation of the relationship between these environmental factors, estimates of burn severity, and fire spread patterns. Burn severity is calculated and classified using the Difference in Normalized Burn Ratio (dNBR) before being displayed as a time series of maps. The Dolan Fire had a moderate severity burn with an average dNBR of 0.292. The ignition site location, when paired with the patterns of fire spread, is consistent with wind speed and direction data, suggesting fire movement to the southeast of the fire ignition site. Patterns of increased burn severity are compared with both topography (slope and aspect) and fuel type. Locations that were found to be more susceptible to high burn severity featured Long Needle Timber Litter and Mature Timber fuels, intermediate slope angles between 15 and 35°, and north- and east-facing slopes. This study has implications for the future predictive modeling of wildfires that may serve to develop wildfire mitigation strategies, manage climate change impacts, and protect human lives.Item Role of Type 4B Secretion System Protein, IcmE, in the Pathogenesis of Coxiella burnetii(MDPI, 2024-05-14) Palanisamy, Rajesh; Zhang, Yan; Zhang, GuoquanCoxiella burnetii is an obligate intracellular Gram-negative bacterium that causes Q fever, a life-threatening zoonotic disease. C. burnetii replicates within an acidified parasitophorous vacuole derived from the host lysosome. The ability of C. burnetii to replicate and achieve successful intracellular life in the cell cytosol is vastly dependent on the Dot/Icm type 4B secretion system (T4SSB). Although several T4SSB effector proteins have been shown to be important for C. burnetii virulence and intracellular replication, the role of the icmE protein in the host–C. burnetii interaction has not been investigated. In this study, we generated a C. burnetii Nine Mile Phase II (NMII) mutant library and identified 146 transposon mutants with a single transposon insertion. Transposon mutagenesis screening revealed that disruption of icmE gene resulted in the attenuation of C. burnetii NMII virulence in SCID mice. ELISA analysis indicated that the levels of pro-inflammatory cytokines, including interleukin-1β, IFN-γ, TNF-α, and IL-12p70, in serum from Tn::icmE mutant-infected SCID mice were significantly lower than those in serum from wild-type (WT) NMII-infected mice. Additionally, Tn::icmE mutant bacteria were unable to replicate in mouse bone marrow-derived macrophages (MBMDM) and human macrophage-like cells (THP-1). Immunoblotting results showed that the Tn::icmE mutant failed to activate inflammasome components such as IL-1β, caspase 1, and gasdermin-D in THP-1 macrophages. Collectively, these results suggest that the icmE protein may play a vital role in C. burnetii virulence, intracellular replication, and activation of inflammasome mediators during NMII infection.Item On the Controllability of Coupled Nonlocal Partial Integrodifferential Equations Using Fractional Power Operators(MDPI, 2024-04-30) Litimein, Hamida; Huang, Zhen-You; Ouahab, Abdelghani; Stamova, Ivanka; Souid, Mohammed SaidIn this research paper, we investigate the controllability in the α-norm of a coupled system of integrodifferential equations with state-dependent nonlocal conditions in generalized Banach spaces. We establish sufficient conditions for the system’s controllability using resolvent operator theory introduced by Grimmer, fractional power operators, and fixed-point theorems associated with generalized measures of noncompactness for condensing operators in vector Banach spaces. Finally, we present an application example to validate the proposed methodology in this research.Item Improving Resource and Energy Efficiency for Cloud 3D through Excessive Rendering Reduction(Association for Computing Machinery, 2024-04-22) Liu, Tianyi; Lucas, Jerry; He, Sen; Liu, Tongping; Wang, Xiaoyin; Wang, WeiThe rise of cloud gaming makes interactive 3D applications an emerging type of data center workload. However, the excessive rendering in current cloud 3D systems leads to large gaps between the cloud and client frame rates (FPS, frames per second), thus wasting resources and power. Although FPS regulation can remove excessive rendering, due to the highly-varying frame processing time and the use of rendering delays, existing cloud FPS regulation solutions have low FPS and slow motion-to-photon (MtP) latency, causing violations of Quality-of-Service (QoS) requirements. In this paper, we present a novel cloud FPS regulation solution, called OnDemand Rendering (ODR). ODR employs multi-buffering, dynamic rendering delay/acceleration, and input processing prioritization to reduce excessive rendering and ensure QoS satisfaction. ODR was evaluated in our private cloud and Google cloud. Evaluation results showed that ODR effectively removed excessive rendering, thus improving DRAM performance by 19% and reducing power usage by 16% over no FPS regulation. Better memory efficiency also allowed ODR to increase client FPS by 5.5%. Moreover, ODR reduced average MtP latency by more than 92% and outperformed existing FPS regulations. More importantly, ODR's high FPS and low latency make it feasible to deploy 3D applications to conventional public clouds.Item Experiences in Delivering Online CS Teacher Professional Development(Association for Computing Machinery, 2024-03-07) Wilde, Jina; Beltran, Emiliano; Zawatski, Michael J.; Fernandez, Amanda S.; Prasad, Priya V.; Yuen, Timothy T.This paper describes our team's experience in designing and delivering the online teacher professional development (PD) program, Computer Science for San Antonio (CS4SA), aimed at empowering educators with computer science (CS) knowledge to increase Latinx participation in CS and STEM education within a large, urban predominantly Latinx school district in South Texas. This paper highlights the successes, challenges, and lessons learned while facilitating two cohorts of the CS PD through online platforms during the COVID-19 pandemic. As a result of this program, participants recognized the importance of integrating CS into their classroom and becoming advocates for the discipline at the high school level. Additionally, teachers, investigators, and other personnel learned important lessons for enhancing the program's impact through collaboration with district administrators and refinement of the online learning experience.Item CS1 with a Side of AI: Teaching Software Verification for Secure Code in the Era of Generative AI(Association for Computing Machinery, 2024-03-07) Fernandez, Amanda S.; Cornell, Kimberly A.As AI-generated code promises to become an increasingly relied upon tool for software developers, there is a temptation to call for significant changes to early computer science curricula. A move from syntax-focused topics in CS1 toward abstraction and high-level application design seems motivated by the new large language models (LLMs) recently made available. In this position paper however, we advocate for an approach more informed by the AI itself - teaching early CS learners not only how to use the tools but also how to better understand them. Novice programmers leveraging AI-code-generation without proper understanding of syntax or logic can create "black box" code with significant security vulnerabilities. We outline methods for integrating basic AI knowledge and traditional software verification steps into CS1 along with LLMs, which will better prepare students for software development in professional settings.Item ChemAIstry: A Novel Software Tool for Teaching Model Training in K-8 Education(Association for Computing Machinery, 2024-03-07) Martin, Fred; Mahipal, Vaishali; Jain, Garima; Ghosh, Srija; Sanusi, Ismaila TemitayoMachine learning (ML) systems are increasingly in use in society. For young learners to be informed citizens and have full career potential it is important for them to understand these concepts. To support this learning, we created "ChemAIstry,'' an interactive software tool for children which demonstrates training and classification in machine learning. Students select which everyday items are safe to bring into a chemistry lab (e.g., a lab coat is safe; pizza is not). These selections serve as training input for a decision tree classifier. After training, students see how the trained model performs in classifying new objects. ChemAIstry was tested with 40 students aged 7 to 14 years at a public K?8 school. The software captured student selections during training. We analyzed these interactions to yield a "Correspondence Score,'' a measure of student understanding of the classification task. We screen-recorded student use of the software and audio-recorded our conversations with them during this use. Our analysis of these data indicates that students were able to understand the concept of model training, including that items were subsequently classified based on their training input. More than half of the student trials indicated that students correctly understood the task. This suggests ChemAIstry was effective in introducing students to these ideas in machine learning. We recommend continued development of related tools for curriculum integration of AI in K-8 education.Item Efficient and Direct Inference of Heart Rate Variability using Both Signal Processing and Machine Learning(Association for Computing Machinery, 2024-01-22) Zhang, Yuntong; Xu, Jingye; Xie, Mimi; Zhu, Dakai; Song, Houbing; Wang, WeiHeart Rate Variability (HRV) measures the variation of the time between consecutive heartbeats and is a major indicator of physical and mental health. Recent research has demonstrated that photoplethysmography (PPG) sensors can be used to infer HRV. However, many prior studies had high errors because they only employed signal processing or machine learning (ML), or because they indirectly inferred HRV, or because there lacks large training datasets. Many prior studies may also require large ML models. The low accuracy and large model sizes limit their applications to small embedded devices and potential future use in healthcare. To address the above issues, we first collected a large dataset of PPG signals and HRV ground truth. With this dataset, we developed HRV models that combine signal processing and ML to directly infer HRV. Evaluation results show that our method had errors between 3.5% to 25.7% and outperformed signal-processing-only and ML-only methods. We also explored different ML models, which showed that Decision Trees and Multi-level Perceptrons have 13.0% and 9.1% errors on average with models at most hundreds of KB and inference time less than 1ms. Hence, they are more suitable for small embedded devices and potentially enable the future use of PPG-based HRV monitoring in healthcare.Item Impact of endosymbionts on tick physiology and fitness(Cambridge University Press, 2023-08-24) Kolo, Agatha O.; Raghavan, RahulTicks transmit pathogens and harbour non-pathogenic, vertically transmitted intracellular bacteria termed endosymbionts. Almost all ticks studied to date contain 1 or more of Coxiella, Francisella, Rickettsia or Candidatus Midichloria mitochondrii endosymbionts, indicative of their importance to tick physiology. Genomic and experimental data suggest that endosymbionts promote tick development and reproductive success. Here, we review the limited information currently available on the potential roles endosymbionts play in enhancing tick metabolism and fitness. Future studies that expand on these findings are needed to better understand endosymbionts’ contributions to tick biology. This knowledge could potentially be applied to design novel strategies that target endosymbiont function to control the spread of ticks and pathogens they vector.Item Thorium: A Language for Bounded Verification of Dynamic Reactive Objects(Association for Computing Machinery, 2023-10-19) Baldor, Kevin; Wang, Xiaoyin; Niu, JianweiDeveloping reliable reactive software is notoriously difficult – particularly when that software reacts by changing its behavior. Some of this difficulty is inherent; software that must respond to external events as they arrive tends to end up in states that are dependent on the value of that input and its order of arrival. This results in complicated corner cases that can be challenging to recognize. However, we find that some of the complexity is an accident of the features of the programming languages widely used in industry. The loops and subroutines of structured programming are well-suited to data transformation, but poorly capture – and sometimes obscure – the flow of data through reactive programs developed using the inversion-of-control paradigm; an event handler that modifies the data flow tends to be declared closer to the definition of the event that activates it than to the initial definition of the data flow that it modifies. This paper approaches both challenges with a language inspired by the declarative modules of languages SIGNAL and Lustre and the semantics of the SodiumFRP Functional Reactive Programming library with a declarative mechanism for self modification through module substitution. These language features lead to software with a code structure that closely matches the flow of data through the running program and thus makes software easier to understand. Further, we demonstrate how those language features enable a bounded model checking approach that can verify that a reactor meets its requirements or present a counterexample trace, a series of states and inputs that lead to a violation. We analyze the runtime performance of the verifier as a function of model size and trace length.Item MemPerf: Profiling Allocator-Induced Performance Slowdowns(Association for Computing Machinery, 2023-10-16) Zhou, Jin; Silvestro, Sam; Tang, Steven (Jiaxun); Yang, Hanmei; Liu, Hongyu; Zeng, Guangming; Wu, Bo; Liu, Cong; Liu, TongpingThe memory allocator plays a key role in the performance of applications, but none of the existing profilers can pinpoint performance slowdowns caused by a memory allocator. Consequently, programmers may spend time improving application code incorrectly or unnecessarily, achieving low or no performance improvement. This paper designs the first profiler—MemPerf—to identify allocator-induced performance slowdowns without comparing against another allocator. Based on the key observation that an allocator may impact the whole life-cycle of heap objects, including the accesses (or uses) of these objects, MemPerf proposes a life-cycle based detection to identify slowdowns caused by slow memory management operations and slow accesses separately. For the prior one, MemPerf proposes a thread-aware and type-aware performance modeling to identify slow management operations. For slow memory accesses, MemPerf utilizes a top-down approach to identify all possible reasons for slow memory accesses introduced by the allocator, mainly due to cache and TLB misses, and further proposes a unified method to identify them correctly and efficiently. Based on our extensive evaluation, MemPerf reports 98% medium and large allocator-reduced slowdowns (larger than 5%) correctly without reporting any false positives. MemPerf also pinpoints multiple known and unknown design issues in widely-used allocators.Item PExReport-Maven: Creating Pruned Executable Cross-Project Failure Reports in Maven Build System(Association for Computing Machinery, 2023-07-13) Huang, Sunzhou; Wang, XiaoyinModern Java software development extensively depends on existing libraries written by other developer teams from the same or a different organization. When a developer executes the test, the execution trace may go across the boundaries of multiple dependencies and create cross-project failures (CPFs). A readable, executable, and concise CPF report may enable the most effective communication, but creating such a report is often challenging in Java ecosystems. We developed PExReport-Maven to automatically create the ideal CPF reports in the Maven build system. PExReport-Maven leverages the Maven build system to prune source code, dependencies, and the build environment to create a concise stand-alone executable CPF reproduction package from the original CPF project. The reproduction package includes the source code, dependencies, and build environment necessary to reproduce the CPF, making it an ideal CPF report. We performed an evaluation on 74 software project issues with 198 cross-project failures, and the evaluation results show that PExReport can create pruned reproduction packages for 184 out of the 198 test failures in our dataset, with an average reduction of 72.97% in Java classes. A future study will be conducted based on user feedback from using this tool to report real-world CPFs. PExReport-Maven is publicly available at https://github.com/wereHuang/PExReport-Maven. The tool demo is available on the PExReport website: https://sites.google.com/view/pexreport/home.Item The Eyes Have It: Visual Feedback Methods to Make Walking in Immersive Virtual Reality More Accessible for People With Mobility Impairments While Utilizing Head-Mounted Displays(Association for Computing Machinery, 2023-10-22) Mahmud, M. Rasel; Cordova, Alberto; Quarles, JohnThe use of Head-Mounted Displays (HMDs) in Virtual Reality (VR) can cause gait disturbance problems for users because they are unable to see the real world while in VR. This is particularly challenging for individuals with mobility impairments who rely heavily on visual cues to maintain balance. The limited research that has been conducted on this issue has not focused on ways to solve it. IN this study, we investigated how different visual feedback methods affect walking patterns (i.e., gait) in VR. The study involved 50 participants, including 25 individuals with mobility impairments due to multiple sclerosis and 25 without mobility impairments. The participants completed timed walking tasks in both the real world and in VR environments that included various types of visual feedback, such as spatial, static, and rhythmic. The results showed that static and rhythmic visual feedback significantly improved gait performance in VR for people with mobility impairments compared to no visual feedback in VR. The results will help to make more accessible virtual environments for people with mobility impairments.Item Context Modulation Enables Multi-tasking and Resource Efficiency in Liquid State Machines(Association for Computing Machinery, 2023-08-28) Helfer, Peter; Teeter, Corinne; Hill, Aaron; Vineyard, Craig M.; Aimone, James B.; Kudithipudi, DhireeshaMemory storage and retrieval are context-sensitive in both humans and animals; memories are more accurately retrieved in the context where they were acquired, and similar stimuli can elicit different responses in different contexts. Researchers have suggested that such effects may be underpinned by mechanisms that modulate the dynamics of neural circuits in a context-dependent fashion. Based on this idea, we design a mechanism for context-dependent modulation of a liquid state machine, a recurrent spiking artificial neural network. We find that context modulation enables a single network to multitask and requires fewer neurons than when several smaller networks are used to perform the tasks individually.Item What’s (Not) Working in Programmer User Studies?(Association for Computing Machinery, 2023-07-24) Davis, Matthew C.; Aghayi, Emad; Latoza, Thomas D.; Wang, Xiaoyin; Myers, Brad A.; Sunshine, JoshuaA key goal of software engineering research is to improve the environments, tools, languages, and techniques programmers use to efficiently create quality software. Successfully designing these tools and demonstrating their effectiveness involves engaging with tool users—software engineers. Researchers often want to conduct user studies of software engineers to collect direct evidence. However, running user studies can be difficult, and researchers may lack solution strategies to overcome the barriers, so they may avoid user studies. To understand the challenges researchers face when conducting programmer user studies, we interviewed 26 researchers. Based on the analysis of interview data, we contribute (i) a taxonomy of 18 barriers researchers encounter; (ii) 23 solution strategies some researchers use to address 8 of the 18 barriers in their own studies; and (iii) 4 design ideas, which we adapted from the behavioral science community, that may lower 8 additional barriers. To validate the design ideas, we held an in-person all-day focus group with 16 researchers.