Timing Information Research Articles

From megabytes to molecules: The usage of DNA computing for storage and its implications on the future

It is more important now than ever to develop more effective data storage techniques in the constantly advancing field of computers. Due to their limits in terms of durability, information density, and physical space requirements, current storage technologies, such as magnetic and optical media, are finding it difficult to keep up with the global demand for data storage, which is expected to exceed 175 trillion gigabytes by 2025. Nature’s own method of storing genetic information for a long time, deoxyribonucleic acid (DNA), provides great data density, stability, and endurance, making it a viable solution to address this issue. Through a comprehensive analysis of existing literature, this paper aims to provide a nuanced understanding of DNA computing’s current state - mainly its trajectory towards becoming a viable alternative to traditional storage methods - highlighting the history, current developments/challenges, and future prospects.

Signal modulation waveform recognition method based on STF-Net

Signal modulation waveform recognition is one of the key technologies in the field of spatial spectrum cognition and an important means to realize the monitoring and control of spectrum resources of low-orbit satellites. In view of the problems of large number of parameters and high computational complexity in the current modulation waveform recognition methods based on deep learning, a lightweight signal modulation waveform recognition method based on space-time fusion network (STF-Net) is proposed. The signal is preprocessed into dual-channel data in the form of time domain and frequency domain, and the signal spatial features are extracted and feature redundancy is reduced by convolutional neural network (CNN). Then, the long short-term memory network (LSTM) is used to extract the timing information and output the recognition result. The experimental results show that when the signal-to-noise ratio is greater than 0 dB, the average recognition accuracy of the modulation waveform of the proposed method reaches 91.79%; compared with the same method, the number of parameters of the proposed method is reduced 96%and the efficiency is increased by 2.7 times.

Inventory Management System Using Economic Order Quantity And Reorder Point

The inventory management system for car workshops is still using Excel, which makes it inefficient and inaccurate for complex stock calculations. The solution is to design an inventory application that uses the Economic Order Quantity and Reorder Point methods. The application will provide timely stock replenishment information and optimize order quantities, increasing inventory management efficiency and accuracy. The Software Development Life Cycle used in this study is Rapid Application Development, a process emphasizing short development cycles. User Acceptance Test results show that users received the inventory management system very well, with an average satisfaction level of 98.44% for Admins and 97% for general users, indicating high satisfaction with the system's features and functionality.

Neuropeptide-dependent spike time precision and plasticity in circadian output neurons.

Circadian rhythms influence various physiological and behavioral processes such as sleep-wake cycles, hormone secretion, and metabolism. Circadian output neurons are a group of neurons that receive input from the central circadian clock located in the suprachiasmatic nucleus of the mammalian brain and transmit timing information to different regions of the brain and body, coordinating the circadian rhythms of various physiological processes. In Drosophila , an important set of circadian output neurons are called pars intercerebralis (PI) neurons, which receive input from specific clock neurons called DN1. These neurons can further be subdivided into functionally and anatomically distinctive anterior (DN1a) and posterior (DN1p) clusters. The neuropeptide diuretic hormones 31 (Dh31) and 44 (Dh44) are the insect neuropeptides known to activate PI neurons to control activity rhythms. However, the neurophysiological basis of how Dh31 and Dh44 affect circadian clock neural coding mechanisms underlying sleep in Drosophila is not well understood. Here, we identify Dh31/Dh44-dependent spike time precision and plasticity in PI neurons. We find that the application of synthesized Dh31 and Dh44 affects membrane potential dynamics of PI neurons in the precise timing of the neuronal firing through their synergistic interaction, possibly mediated by calcium-activated potassium channel conductance. Further, we characterize that Dh31/Dh44 enhances postsynaptic potentials in PI neurons. Together, these results suggest multiplexed neuropeptide-dependent spike time precision and plasticity as circadian clock neural coding mechanisms underlying sleep in Drosophila .

7513 Presence Of Hispanic/Latino Physicians In Academic Research. Are We There Yet?

Abstract Disclosure: C.E. Guillen Lopez: None. A. Patel: None. A. Rocha: None. C. Arima: None. A. Molkina: None. L. Robles: None. A. Arce Gastelum: None. Hispanic/Latino endocrinologists' presence and active involvement in diabetes research play a pivotal role in shaping the trajectory of healthcare initiatives in the United States. Diabetes, a prevalent and complex health condition, disproportionately affects diverse communities, with Hispanics/Latinos being among the groups facing higher incidence rates. In this context, the significance of Hispanic/Latino endocrinologists cannot be overstated, as their unique perspectives and cultural insights contribute to a more nuanced understanding of the multifaceted factors influencing diabetes prevalence, management, and outcomes in the U.S. By actively involving Hispanic/Latino endocrinologists in diabetes research, we not only enhance the representation of diverse patient populations but also foster a more comprehensive approach to addressing the intricate intersections of genetics, lifestyle, and socio-cultural factors contributing to diabetes disparities in the nation. In the 2021 Physician Specialty Data Report, the Association of American Medical Colleges (AAMC) incorporated physician race and ethnicity information for the first time. Within the 7,354 actively practicing endocrinologists surveyed, only 636 individuals identified as Hispanic/Latino. The majority of these endocrinologists were predominantly dedicated to clinical practice. A descriptive analysis of 1011 abstracts on diabetes and glucose metabolism presented at the Endo Society from 2021 to 2023 revealed that 549 were authored by women and 458 by men. The majority (705 posters, 69.7%) originated from the U.S., and 306 (30.26%) were classified as international posters. Among these, 152 posters (15%) were associated with the Hispanic or Latino authors, but only 91 (9%) were published in the U.S. In conclusion, the engagement of Hispanic/Latino physicians in endocrinology is indispensable for advancing healthcare. Their participation brings diverse perspectives, facilitates a better understanding of health disparities, and promotes innovative research and patient care strategies. By actively involving Hispanic/Latino physicians, we contribute to a more comprehensive understanding of endocrine disorders and work towards a healthcare system that prioritizes inclusivity, cultural sensitivity, and collaboration, ultimately benefiting the well-being of individuals across diverse communities. Presentation: 6/2/2024

4D Track Reconstruction on Free-Streaming Data with PANDA at FAIR

A new generation of accelerator-based experiments in subatomic physics is being developed, where the challenge of separating rare signal processes from background at high intensities requires a change of trigger paradigm. At the future PANDA experiment at FAIR, hardware triggers will be abandoned and instead a purely software-based system will be used. This requires novel reconstruction methods with the ability to process data from many beam–target interactions simultaneously. A 4D tracking algorithm, based on the cellular automaton, has been developed which will utilize the timing information from detector signals. Simulation studies have been performed to test its performance on the foreseen free-streaming, i.e., continuous readout from the PANDA detector, where all processing is on the software level. For this purpose, a novel quality assurance method, tailored for tracking on free-streaming data has been developed and implemented. Benchmark studies on PANDA software show that at higher interaction rates, 4D tracking performs better than the 3D algorithm in terms of efficiency, 84%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document} compared to 77%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document}. In addition, the fake track suppression is greatly improved, reducing the rate of fake tracks of “ghosts” by about 50%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document}.

Shower separation in five dimensions for highly granular calorimeters using machine learning

To achieve state-of-the-art jet energy resolution for Particle Flow, sophisticated energy clustering algorithms must be developed that can fully exploit available information to separate energy deposits from charged and neutral particles. Three published neural network-based shower separation models were applied to simulation and experimental data to measure the performance of the highly granular CALICE Analogue Hadronic Calorimeter (AHCAL) technological prototype in distinguishing the energy deposited by a single charged and single neutral hadron for Particle Flow. The performance of models trained using only standard spatial, energy and charged track position information from an event was compared to models trained using timing information available from AHCAL, which is expected to improve sensitivity to shower development and, therefore, aid in clustering. Both simulation and experimental data were used to train and test the models and their performances were compared. The best-performing neural network achieved significantly superior event reconstruction when timing information was utilised in training for the case where the charged hadron had more energy than the neutral one, motivating temporally sensitive calorimeters. All models under test were observed to tend to allocate energy deposited by the more energetic of the two showers to the less energetic one. Similar shower reconstruction performance was observed for a model trained on simulation and applied to data and a model trained and applied to data.

Researching Informational Technologies of Trust: From Blockchain to Paradata and Digital Archives

ABSTRACTInformation science research has a long‐time interest in diverse informational means of codifying, communicating and maintaining trust as an antecedent and outcome of information, and a central constituent of information practices. While the landscape of the gatekeepers and guarantors of access to trustworthy information for a long time remained relatively stable, since the turn of the millennium, it has evolved rapidly with several new and repurposed social and digital technologies developed and repurposed for mediating and preserving trust. The purpose of this panel is to engage in exploring from theoretical, practical and empirical perspectives such technologies across the information field. The panelists present research conceptualizing, documenting, developing and describing informational technologies of mediating and preserving trust specifically addressing: 1) what different approaches to mediating and maintaining trust exist and can be identified in information science and technology research and practice; 2) how different information technologies of trust influence the understanding and conceptualisations of trust and trustworthy information; and 3) what novel insights from the current state‐of‐the‐art research can be drawn for helping practitioners to empower and put people first when interacting with informational technologies of trust in different areas of the information field, including knowledge organisation and information behaviour and practices, records management, digital preservation, and and development of information systems and services.

Improving flu vaccination rates among adult patients with cancer at Kaiser Permanente.

326 Background: Vaccines protect cancer patients from developing severe illness, hospitalization, and death. At Kaiser Permanente (KP) South Sacramento Medical Center (KPSSC), oncology patients on active chemotherapy had an overall flu vaccination rate of 13% between September 1, 2022, and December 1, 2022. Our aim was to increase this rate to 33% during the 2023 flu season. Methods: In conjunction with the ASCO Quality Training Program, we applied quality improvement initiatives to improve flu vaccination. Our population of interest included adult cancer patients on active chemotherapy at KPSCC. We evaluated the barriers to vaccination assessment by distributing surveys to infusion nurses. We performed three Plan-Do-Study-Act (PDSA) cycles for quality improvement and monitored flu vaccination rates. Cycle 1 (9/11/2023 to 11/5/2023): We distributed the ASCO flu vaccine handout at oncology clinic. We had medical assistants and infusion nurses administer flu vaccines during clinic visits and chemotherapy sessions. Cycle 2 (11/6/2023 to 11/21/2023): We added the vaccine handout in Chinese and Spanish and updated our receptionists’ script to strongly encourage patients to receive flu vaccine. Cycle 3 (11/22/2023 to 12/6/2023): KP flu clinic set up an onsite flu vaccine cart one half day per week in the oncology clinic. Results: Barriers to vaccination assessment in the clinic included lack of time (60%), difficulty remembering to ask (10%), and non-influenza season (10%). Our interventions resulted in an increased flu vaccination rate from 13% in 2022 to 36% in 2023. During cycle 1, 298 out of 615 patients received their vaccine (48.5%). During cycle 2, 16 out of 118 patients received their vaccine (13.6%). PDSA cycle 3 resulted in 14 out of 178 patients receiving their vaccine (7.9%). Conclusions: Promoting vaccine awareness via active engagement with nurses and medical assistants early on and having onsite vaccine availability in the oncology clinic were keys to improve the overall flu vaccination rate. While most vaccines were administered at the beginning of flu season, the addition of language-tailored vaccine handouts and having an onsite vaccine cart towards the end of the season did result in late season vaccinations. Our findings do support the importance of providing timely vaccine information in the oncology clinic. Our future goal is to expand these efforts to other KP Northern California oncology centers to establish stable onsite vaccine availability in clinics and include additional vaccine types.

Driving sustainable energy transitions with a multi-source RAG-LLM system

By 2035, the UK aims to upgrade all homes to achieve a net-zero economy by 2050, thereby reducing energy consumption, household costs, and improving living conditions. Small and Medium-sized Enterprises (SMEs) play a crucial role in this transition. However, many SME contractors lack essential information on Sustainable Energy Initiatives (SEIs) and the relevant Energy landscape necessary for driving Sustainable Energy Transitions (SETs). This knowledge gap poses risks to SME interventions, potentially leading to increased costs and inefficiencies. Accessing timely information on SEIs including government policies, funding, technologies, and environmental impacts from various media sources is essential for guiding effective SETs and understanding the relevant Energy landscape, thereby facilitating informed decision-making. Currently, SMEs lack an integrated system that consolidates data from diverse media sources into a centralized Information System (IS), limiting their ability to effectively navigate SEIs. To address this gap, this research introduces an Energy Chatbot, a sustainable IS that utilizes Large Language Models (LLMs) integrated with multi-source Retrieval Augmented Generation (RAG). This system encompasses diverse media sources, including news articles, government reports, industry publications, academic research, and social media. The Energy Chatbot is designed to enhance decision-making for SMEs by providing comprehensive Energy sector insights through a Question Answering (QA) system. Key findings emphasize that this approach reduces costs by utilizing open-source models. Moreover, the Energy Chatbot provides SMEs with access to up-to-date information, enabling them to identify long-term sustainability strategies and maintain a competitive edge in the evolving Energy landscape.

Considerations on time resolution of neutron irradited single pixel 3D structures at fuences up to1017 neq/cm2 using 120 GeV SPS pion beams

The proven radiation hardness of silicon 3D devices up to fluences of 1 × 1017 neq/cm2 makes them an excellent choice for next generation trackers, providing < 10 μm position resolution at a high multiplicity environment. The anticipated pile-up increase at HL-LHC conditions and beyond, requires the addition of < 50 ps per hit timing information to successfully resolve displaced and primary vertices. In this study, the timing performance, uniformity and efficiency of neutron and proton irradiated single pixel 3D devices is discussed. Fluences up to 1 × 1017 neq/cm2 in three different geometrical implementations are evaluated using 120 GeV SPS pion beams. A MIMOSA-26 type telescope is used to provide detailed tracking information with a ∼ 5 μm position resolution. Productions with single- and double-sided processes, yielding active thicknesses of 130 and 230 μm respectively, are examined with varied pixel sizes from 55 × 55 μm2 to 25 × 100 μm2 and a comparative study of field uniformity is presented with respect to electrode geometry. The question of electronics bandwidth is extensively addressed with respect to achievable time resolution, efficiency and collected charge, forming a 3D phase space to which an appropriate operating point can be selected depending on the application requirements.

Timing-aware analysis of shared cache interference for non-preemptive scheduling

AbstractIn multi-core architectures, the last-level cache (LLC) is often shared between cores. Sharing the LLC leads to inter-core interference, which impacts system performance and predictability. This means that tasks running in parallel on different cores may experience additional LLC misses as they compete for cache space. To compute a task’s worst-case execution time (WCET), a safe bound on the inter-core cache interference has to be determined. We propose an interference analysis for set-associative shared least-recently-used caches. The analysis leverages timing information to establish tight bounds on the worst-case interference and classifies individual accesses as either cache hits or potential cache misses. We evaluated the analysis performance for systems containing 2 and 4 cores using shared caches up to 64 KB. The evaluation shows an average WCET reduction of up to 23.3% for dual-core systems and 8.5% for quad-core systems.

Molecular identification of Hypomyces chrysospermus mycoparasitic fungus isolated from mushrooms in a local market of Iraq.

In this study, mycoparasitic fungus was identified by using the rDNA internal transcribed spacer barcode marker, i.e. ITS rDNA gene. Amplicons were sequenced and identified by NCBI - BLAST (Basic local alignment search tool). The BLAST results revealed that NOOR strain matched 100% with accession numbers [MH854754.1]. The phylogenetic tree shows close relationship between NOOR strain and H. chrysospermus [MH854754-1], H. chrysospermus [MZ389105-1], H. chrysospermus [MK605327- 1], H. chrysospermus [MT595227-1], H. [EU816370-1], H. chrysospermus [MG685885-1]. The Iraqi isolate was recorded as NOOR strain in the National Centre for Biotechnology Information for the first time in Iraq.

ATLAS upgrade for the HL-LHC

While the on-going Run-3 data-taking campaign will provide twice the integrated proton–proton luminosity currently available at the LHC, most of the data expected for the full LHC physics program will only be delivered during the HL-LHC phase. For this, the LHC will undergo an ambitious upgrade program to be able to deliver an instantaneous luminosity of 7.5⋅1034cm−2s−1, allowing the collection of more than 3 ab−1 of data at s=13.6(14)TeV. This unprecedented data sample will allow the ATLAS experiment to perform several precision measurements to constrain the Standard Model (SM) in yet unexplored regions of phase space, in particular in the Higgs sector, only accessible at the LHC. To benefit from such a rich data sample, it is fundamental to upgrade the detector to cope with the challenging experimental conditions that include radiation doses 10 times higher than what ATLAS experienced since its construction and increase in the number of interactions per bunch crossing from the current 50-60 to 200. The upgrade of the ATLAS detector comprises a completely new all-silicon tracker with extended rapidity coverage that will replace the current inner tracker detector; a redesigned trigger and data acquisition system for the calorimeters and muon systems, allowing the implementation of a readout system that can operate complex trigger algorithms at 40 MHz. Finally, a new subsystem called High Granularity Timing Detector will aid the track-vertex association in the forward region by providing timing information to the reconstructed tracks. An important ingredient, relevant to almost all measurements, is the precise determination of the delivered luminosity with systematic uncertainties below the percent level. This challenging task will be achieved by collecting the information from several detector systems using different and complementary techniques. This document will describe the ongoing ATLAS detector upgrade status and the main results obtained with the prototypes, giving a synthetic view of the whole upgrade project.

Tracking performances of the ePIC detector at the Electron-Ion Collider

The ePIC (electron–Proton/Ion Collider) experiment is a future facility at the Electron-Ion Collider (EIC) complex, located at the Brookhaven National Laboratory, USA. It will use ∼70% longitudinally polarized beam of electrons, protons, and light ions to study their collisions to understand the properties of the quarks, gluons, and the strong force responsible for the formation of the nucleus. The layout of the central detector of the ePIC experiment is not symmetric along the beams axis consisting of barrel, forward, and backward detectors to achieve a wide pseudorapidity (|η|< 3.5) coverage. There are further far-forward and far-backward tracking detectors to measure the luminosity and reconstruct the particles and fragments for the study of the exclusive deep-inelastic scattering (DIS) processes. The experiment has a challenging environment due to the presence of the background radiations (synchrotron radiation, beam-gas interactions, minimum-bias events, etc.) which will produce additional background hits on the tracker. The synchrotron radiation is suppressed to some extent by coating the beampipe with a 5μm gold layer. The experiment uses state-of-the-art bent wafer-scale silicon monolithic active pixel sensors (MAPS) with a ∼5μs acquisition window, micro-pattern gas detector (MPGD) with a good time resolution (∼20–30ns), and time-of-flight detectors based on AC-LGAD sensors (time resolution ∼30ps). The timing information of each detector will play a crucial role in track finding and rejecting the background hits utilizing the 4-dimensional tracking (space, time) to ensure the excellent performance of the experiment. The article presents the expected tracking performance of the ePIC detector using the modular ePIC software stack for simulation, reconstruction, and analysis. The Geant4 toolkit is employed for full detector simulations, alongside DD4hep (Detector Description for High Energy Physics) for geometry definition and exchange. The reconstruction incorporates the JANA2 framework, in addition to the tracking and vertexing algorithms inherited from A Common Tracking Software (ACTS).

Timed Genetic Process Mining for Robust Tracking of Processes under Incomplete Event Log Conditions

In process mining, an event log is a structured collection of recorded events that describes the execution of processes within an organization. The completeness of event logs is crucial for ensuring accurate and reliable process models. Incomplete event logs, which can result from system errors, manual data entry mistakes, or irregular operational patterns, undermine the integrity of these models. Addressing this issue is essential for constructing accurate models. This research aims to enhance process model performance and robustness by transforming incomplete event logs into complete ones using a process discovery algorithm. Genetic process mining, a type of process discovery algorithm, is chosen for its ability to evaluate multiple candidate solutions concurrently, effectively recovering missing events and improving log completeness. However, the original form of the genetic process mining algorithm is not optimized for handling incomplete logs, which can result in incorrect models being discovered. To address this limitation, this research proposes a modified approach that incorporates timing information to better manage incomplete logs. By leveraging timing data, the algorithm can infer missing events, leading to process tracking and reconstruction which is more accurate. Experimental results validate the effectiveness of the modified algorithm, showing higher fitness and precision scores, improved process model comparisons, and a good level of coverage without errors. Additionally, several advanced metrics for conformance checking are presented to further validate the process models and event logs discovered by both algorithms.

Development and validation of the infodemic scale

ABSTRACT Infodemic is closely related to all healthcare professionals. Nurses take the lead in health professions that spend a long time with the society and try to present accurate information due to their roles. Infodemic is the massive spread of false or unreliable information in times of crisis. This study aims to develop a valid and reliable tool that identifies individuals’ approaches to infodemic. This study was methodological. The sample consisted of 504 people (N = 504). Data were collected using the Information Form and the Infodemic Scale. The sample was divided into two for the explanatory factor analysis (EFA) and the confirmatory factor analysis (CFA). The scale was developed using the scale development process in health and social research, which consists of three steps. The EFA revealed 14 items under two factors, which are awareness and literacy. Item factor loadings were found to range between 0.334 and 0.907. The CFA confirmed the two-factor scale structure. The total Cronbach’s alpha of the scale was 0.87, and the composite reliability value was 0.89. The intra-class correlation coefficient (ICC) value was found to be 0.857. According to psychometric evaluations, the Infodemic Scale is a valid and reliable instrument that can make consistent measurements.

Realistic mossy fiber input patterns to unipolar brush cells evoke a continuum of temporal responses comprised of components mediated by different glutamate receptors.

Unipolar brush cells (UBCs) are excitatory interneurons in the cerebellar cortex that receive mossy fiber (MF) inputs and excite granule cells. The UBC population responds to brief burst activation of MFs with a continuum of temporal transformations, but it is not known how UBCs transform the diverse range of MF input patterns that occur in vivo. Here we use cell-attached recordings from UBCs in acute cerebellar slices to examine responses to MF firing patterns that are based on in vivo recordings. We find that MFs evoke a continuum of responses in the UBC population, mediated by three different types of glutamate receptors that each convey a specialized component. AMPARs transmit timing information for single stimuli at up to 5 spikes/s, and for very brief bursts. A combination of mGluR2/3s (inhibitory) and mGluR1s (excitatory) mediates a continuum of delayed, and broadened responses to longer bursts, and to sustained high frequency activation. Variability in the mGluR2/3 component controls the time course of the onset of firing, and variability in the mGluR1 component controls the duration of prolonged firing. We conclude that the combination of glutamate receptor types allows each UBC to simultaneously convey different aspects of MF firing. These findings establish that UBCs are highly flexible circuit elements that provide diverse temporal transformations that are well suited to contribute to specialized processing in different regions of the cerebellar cortex.

Power over fiber development for HEP detectors

Power-over-Fiber (PoF) technology has been used extensively in settings where high voltages require isolation from ground and electromagnetic isolation is critical. In cryogenic environments, PoF offers a reliable power transmission technology, leveraging optical fibers to transfer power with minimal system degradation. PoF technology excels in maintaining low noise levels and isolation when delivering power to sensitive electronic systems operating in extreme temperature ranges and high voltage environments. In a novel application of PoF for a HEP detector, power is provided to photon detector modules located on a surface at ∼300 kV with respect to ground in the planned DUNE experiment. This summary paper of the PoF talk at the 16th PISA Meeting on Advanced Detectors highlights the R&D effort of PoF in extreme conditions and underscores its capacity to revolutionize power delivery and management in critical applications offering a dependable solution with low noise, optimal efficiency, and superior isolation. The DUNE (Abi et al., 2020) experiment will soon deploy large liquid argon (LAr) time projection chambers (TPC) to detect neutrino interactions and other particle physics phenomena. In addition to the particle tracking provided by the TPC, photon detectors, powered by a first ever PoF system, in the cryostat will leverage the high scintillation light yield of LAr to provide crucial timing and additional calorimetric information.

Community, Context, and Communication: Responses of Canadian Libraries to Difficult Situations Involving Medical Mis- or Disinformation

Canadian libraries have traditionally supported and defended intellectual freedom while also being expected to provide communities with trustworthy information in times of personal and collective crisis. Issues of medical misinformation reveal the tension between these two ideals. Library workers face challenges in preparing for and responding to issues with controversial materials, with little guidance on how to navigate this tension and balance the two ideals. In an interview study with 22 Canadian library worker participants, we asked about experiences with navigating these situations. Our preliminary results reveal a range of strategies and considerations at play, ranging from individual incidents to broader policies and power dynamics.