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101. Examining the Concurrent and Predictive Validity of Single Items in Ecological Momentary Assessments

Author

Song, Jiyoung, Howe, Esther, Oltmanns, Joshua R, and Fisher, Aaron J

Subjects
Psychology, Applied and Developmental Psychology, Brain Disorders, Humans, Ecological Momentary Assessment, Reproducibility of Results, Psychometrics, Surveys and Questionnaires, single items, ecological momentary assessment, predictive validity, psychometrics, participant burden, Clinical Psychology, Applied and developmental psychology, Biological psychology
Abstract

Although single items can save time and burden in psychology research, concerns about their reliability have made the use of multiple-item measures the default standard practice. Although single items cannot demonstrate internal reliability, their criterion validity can be compared with multiple-item measures. Using ecological momentary assessment data, we evaluated repeated measures correlations and constructed multilevel cross-lagged models to assess concurrent and predictive validity of single- and multiple-item measures. Correlations between the single- and multiple-item measures ranged from .24 to .61. In 27 of 29 unique single-item predictor models, single items demonstrated significant predictive validity, and in one of eight sets of comparisons, a single-item predictor exhibited a larger effect size than its multiple-item counterpart. Although multiple-item measures generally performed better than single items, the added benefit of multiple items was modest in most cases. The present data provide support for the use of single-item measures in intensive longitudinal designs.

Published
2023

102. Combining Off‐flow, a Nextflow‐coded program, and whole genome sequencing reveals unintended genetic variation in CRISPR/Cas-edited iPSCs

Author

Carole Shum, Sang Yeon Han, Bhooma Thiruvahindrapuram, Zhuozhi Wang, Jill de Rijke, Benjamin Zhang, Maria Sundberg, Cidi Chen, Elizabeth D. Buttermore, Nina Makhortova, Jennifer Howe, Mustafa Sahin, and Stephen W. Scherer

Subjects
Induced pluripotent stem cells (iPSCs), Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR), Genome editing, Whole genome sequencing (WGS), Off-target detection, Biotechnology, TP248.13-248.65
Abstract

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Cas nucleases and human induced pluripotent stem cell (iPSC) technology can reveal deep insight into the genetic and molecular bases of human biology and disease. Undesired editing outcomes, both on-target (at the edited locus) and off-target (at other genomic loci) hinder the application of CRISPR-Cas nucleases. We developed Off-flow, a Nextflow-coded bioinformatic workflow that takes a specific guide sequence and Cas protein input to call four separate off-target prediction programs (CHOPCHOP, Cas-Offinder, CRISPRitz, CRISPR-Offinder) to output a comprehensive list of predicted off-target sites. We applied it to whole genome sequencing (WGS) data to investigate the occurrence of unintended effects in human iPSCs that underwent repair or insertion of disease-related variants by homology-directed repair. Off-flow identified a 3-base-pair-substitution and a mono-allelic genomic deletion at the target loci, KCNQ2, in 2 clones. Unbiased WGS analysis further identified off-target missense variants and a mono-allelic genomic deletion at the targeted locus, GNAQ, in 10 clones. On-target substitution and deletions had escaped standard PCR and Sanger sequencing analysis, while missense variants at other genomic loci were not detected by Off-flow. We used these results to filter out iPSC clones for subsequent functional experiments. Off-flow, which we make publicly available, works for human and mouse genomes currently and can be adapted for other genomes. Off-flow and WGS analysis can improve the integrity of studies using CRISPR/Cas-edited cells and animal models.

Published
2024
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114. Improving Unbalanced Security X-Ray Image Classification Using VGG16 and AlexNet with Z-Score Normalization and Augmentation

Author

Qi, Diao, Junaidi, Apri, Howe, Chan Weng, Zain, Azlan Mohd, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Triwiyanto, Triwiyanto, editor, Rizal, Achmad, editor, and Caesarendra, Wahyu, editor

Published
2024
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115. Enhancing Rice Leaf Disease Classification: A Combined Algorithm Approach for Improved Accuracy and Robustness

Author

Junaidi, Apri, Qi, Diao, Howe, Chan Weng, Hashim, Siti Zaiton Mohd, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Triwiyanto, Triwiyanto, editor, Rizal, Achmad, editor, and Caesarendra, Wahyu, editor

Published
2024
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116. The European Reference Genome Atlas: piloting a decentralised approach to equitable biodiversity genomics

Author

Mc Cartney, Ann M., Formenti, Giulio, Mouton, Alice, De Panis, Diego, Marins, Luísa S., Leitão, Henrique G., Diedericks, Genevieve, Kirangwa, Joseph, Morselli, Marco, Salces-Ortiz, Judit, Escudero, Nuria, Iannucci, Alessio, Natali, Chiara, Svardal, Hannes, Fernández, Rosa, De Pooter, Tim, Joris, Geert, Strazisar, Mojca, Wood, Jonathan M. D., Herron, Katie E., Seehausen, Ole, Watts, Phillip C., Shaw, Felix, Davey, Robert P., Minotto, Alice, Fernández, José M., Böhne, Astrid, Alegria, Carla, Alioto, Tyler, Alves, Paulo C., Amorim, Isabel R., Aury, Jean-Marc, Backstrom, Niclas, Baldrian, Petr, Baltrunaite, Laima, Barta, Endre, BedHom, Bertrand, Belser, Caroline, Bergsten, Johannes, Bertrand, Laurie, Bilandija, Helena, Binzer-Panchal, Mahesh, Bista, Iliana, Blaxter, Mark, Borges, Paulo A. V., Dias, Guilherme Borges, Bosse, Mirte, Brown, Tom, Bruggmann, Rémy, Buena-Atienza, Elena, Burgin, Josephine, Buzan, Elena, Cariani, Alessia, Casadei, Nicolas, Chiara, Matteo, Chozas, Sergio, Čiampor, Jr., Fedor, Crottini, Angelica, Cruaud, Corinne, Cruz, Fernando, Dalen, Love, De Biase, Alessio, del Campo, Javier, Delic, Teo, Dennis, Alice B., Derks, Martijn F. L., Diroma, Maria Angela, Djan, Mihajla, Duprat, Simone, Eleftheriadi, Klara, Feulner, Philine G. D., Flot, Jean-François, Forni, Giobbe, Fosso, Bruno, Fournier, Pascal, Fournier-Chambrillon, Christine, Gabaldon, Toni, Garg, Shilpa, Gissi, Carmela, Giupponi, Luca, Gomez-Garrido, Jessica, González, Josefa, Grilo, Miguel L., Grüning, Björn, Guerin, Thomas, Guiglielmoni, Nadege, Gut, Marta, Haesler, Marcel P., Hahn, Christoph, Halpern, Balint, Harrison, Peter W., Heintz, Julia, Hindrikson, Maris, Höglund, Jacob, Howe, Kerstin, Hughes, Graham M., Istace, Benjamin, Cock, Mark J., Janžekovič, Franc, Jonsson, Zophonias O., Joye-Dind, Sagane, Koskimäki, Janne J., Krystufek, Boris, Kubacka, Justyna, Kuhl, Heiner, Kusza, Szilvia, Labadie, Karine, Lähteenaro, Meri, Lantz, Henrik, Lavrinienko, Anton, Leclère, Lucas, Lopes, Ricardo Jorge, Madsen, Ole, Magdelenat, Ghislaine, Magoga, Giulia, Manousaki, Tereza, Mappes, Tapio, Marques, Joao Pedro, Redondo, Gemma I. Martinez, Maumus, Florian, McCarthy, Shane A., Megens, Hendrik-Jan, Melo-Ferreira, Jose, Mendes, Sofia L., Montagna, Matteo, Moreno, Joao, Mosbech, Mai-Britt, Moura, Mónica, Musilova, Zuzana, Myers, Eugene, Nash, Will J., Nater, Alexander, Nicholson, Pamela, Niell, Manuel, Nijland, Reindert, Noel, Benjamin, Noren, Karin, Oliveira, Pedro H., Olsen, Remi-Andre, Ometto, Lino, Oomen, Rebekah A., Ossowski, Stephan, Palinauskas, Vaidas, Palsson, Snaebjorn, Panibe, Jerome P., Pauperio, Joana, Pavlek, Martina, Payen, Emilie, Pawlowska, Julia, Pellicer, Jaume, Pesole, Graziano, Pimenta, Joao, Pippel, Martin, Pirttilä, Anna Maria, Poulakakis, Nikos, Rajan, Jeena, M.C. Rego, Rúben, Resendes, Roberto, Resl, Philipp, Riesgo, Ana, Rodin-Morch, Patrik, Soares, Andre E. R., Fernandes, Carlos Rodriguez, Romeiras, Maria M., Roxo, Guilherme, Rüber, Lukas, Ruiz-Lopez, Maria Jose, Saarma, Urmas, da Silva, Luis P., Sim-Sim, Manuela, Soler, Lucile, Sousa, Vitor C., Santos, Carla Sousa, Spada, Alberto, Stefanovic, Milomir, Steger, Viktor, Stiller, Josefin, Stöck, Matthias, Struck, Torsten H., Sudasinghe, Hiranya, Tapanainen, Riikka, Tellgren-Roth, Christian, Trindade, Helena, Tukalenko, Yevhen, Urso, Ilenia, Vacherie, Benoit, Van Belleghem, Steven M., Van Oers, Kees, Vargas-Chavez, Carlos, Velickovic, Nevena, Vella, Noel, Vella, Adriana, Vernesi, Cristiano, Vicente, Sara, Villa, Sara, Pettersson, Olga Vinnere, Volckaert, Filip A. M., Voros, Judit, Wincker, Patrick, Winkler, Sylke, Ciofi, Claudio, Waterhouse, Robert M., and Mazzoni, Camila J.

Published
2024
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128. Frequency and predictors of headache in the first 12 months after traumatic brain injury: results from CENTER-TBI

Author

Howe, Emilie Isager, Andelic, Nada, Brunborg, Cathrine, Zeldovich, Marina, Helseth, Eirik, Skandsen, Toril, Olsen, Alexander, Fure, Silje C. R., Theadom, Alice, Rauen, Katrin, Madsen, Benedikte Å., Jacobs, Bram, van der Naalt, Joukje, Tartaglia, Maria Carmela, Einarsen, Cathrine Elisabeth, Storvig, Gøril, Tronvik, Erling, Tverdal, Cathrine, von Steinbüchel, Nicole, Røe, Cecilie, and Hellstrøm, Torgeir

Published
2024
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131. The ENGAGE study: a 3-arm randomized hybrid type 1 effectiveness and implementation study of an in-home, collaborative PCP model of remote telegenetic services to increase uptake of cancer genetic services in childhood cancer survivors

Author

Henderson, Tara O., Allen, Mary Ashley, Mim, Rajia, Egleston, Brian, Fleisher, Linda, Elkin, Elena, Oeffinger, Kevin, Krull, Kevin, Ofidis, Demetrios, Mcleod, Briana, Griffin, Hannah, Wood, Elizabeth, Cacioppo, Cara, Weinberg, Michelle, Brown, Sarah, Howe, Sarah, McDonald, Aaron, Vukadinovich, Chris, Alston, Shani, Rinehart, Dayton, Armstrong, Gregory T., and Bradbury, Angela R.

Published
2024
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134. Chromosome level genome assembly of the Etruscan shrew Suncus etruscus

Author

Bukhman, Yury V., Meyer, Susanne, Chu, Li-Fang, Abueg, Linelle, Antosiewicz-Bourget, Jessica, Balacco, Jennifer, Brecht, Michael, Dinatale, Erica, Fedrigo, Olivier, Formenti, Giulio, Fungtammasan, Arkarachai, Giri, Swagarika Jaharlal, Hiller, Michael, Howe, Kerstin, Kihara, Daisuke, Mamott, Daniel, Mountcastle, Jacquelyn, Pelan, Sarah, Rabbani, Keon, Sims, Ying, Tracey, Alan, Wood, Jonathan M. D., Jarvis, Erich D., Thomson, James A., Chaisson, Mark J. P., and Stewart, Ron

Published
2024
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137. Transcriptomic profiling of early synucleinopathy in rats induced with preformed fibrils

Author

Patterson, Joseph R., Kochmanski, Joseph, Stoll, Anna C., Kubik, Michael, Kemp, Christopher J., Duffy, Megan F., Thompson, Kajene, Howe, Jacob W., Cole-Strauss, Allyson, Kuhn, Nathan C., Miller, Kathryn M., Nelson, Seth, Onyekpe, Christopher U., Beck, John S., Counts, Scott E., Bernstein, Alison I., Steece-Collier, Kathy, Luk, Kelvin C., and Sortwell, Caryl E.

Published
2024
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140. Latitudinal patterns in stabilizing density dependence of forest communities

Author

Hülsmann, Lisa, Chisholm, Ryan A., Comita, Liza, Visser, Marco D., de Souza Leite, Melina, Aguilar, Salomon, Anderson-Teixeira, Kristina J., Bourg, Norman A., Brockelman, Warren Y., Bunyavejchewin, Sarayudh, Castaño, Nicolas, Chang-Yang, Chia-Hao, Chuyong, George B., Clay, Keith, Davies, Stuart J., Duque, Alvaro, Ediriweera, Sisira, Ewango, Corneille, Gilbert, Gregory S., Holík, Jan, Howe, Robert W., Hubbell, Stephen P., Itoh, Akira, Johnson, Daniel J., Kenfack, David, Král, Kamil, Larson, Andrew J., Lutz, James A., Makana, Jean-Remy, Malhi, Yadvinder, McMahon, Sean M., McShea, William J., Mohamad, Mohizah, Nasardin, Musalmah, Nathalang, Anuttara, Norden, Natalia, Oliveira, Alexandre A., Parmigiani, Renan, Perez, Rolando, Phillips, Richard P., Pongpattananurak, Nantachai, Sun, I-Fang, Swanson, Mark E., Tan, Sylvester, Thomas, Duncan, Thompson, Jill, Uriarte, Maria, Wolf, Amy T., Yao, Tze Leong, Zimmerman, Jess K., Zuleta, Daniel, and Hartig, Florian

Published
2024
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146. Refinements of Katz-Sarnak theory for the number of points on curves over finite fields

Author

Bergström, Jonas, Howe, Everett W., García, Elisa Lorenzo, and Ritzenthaler, Christophe

Subjects
Mathematics - Number Theory, Mathematics - Algebraic Geometry
Abstract

This paper goes beyond Katz-Sarnak theory on the distribution of curves over finite fields according to their number of rational points, theoretically, experimentally and conjecturally. In particular, we give a formula for the limits of the moments measuring the asymmetry of this distribution for (non-hyperelliptic) curves of genus $g \geq 3$. The experiments point to a stronger notion of convergence than the one provided by the Katz-Sarnak framework for all curves of genus $\geq 3$. However, for elliptic curves and for hyperelliptic curves of every genus we prove that this stronger convergence cannot occur., Comment: 24 pages, 5 figures. We reformulated one of our main results (Theorem 3.1) and added remark 2.6 after one of the referees' questions

Published
2023

147. Detector bandwidth and polarisation switching rates: spectrophotometric observations of the Sun by the Birmingham Solar Oscillations Network (BiSON)

Author

Hale, S. J., Chaplin, W. J., Davies, G. R., Elsworth, Y. P., and Howe, R.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Solar and Stellar Astrophysics
Abstract

The Birmingham Solar Oscillations Network (BiSON) observes acoustic oscillations of the Sun. The dominant noise source is caused by fluctuations of Earth's atmosphere, and BiSON seeks to mitigate this effect by combining multiple rapid observations in alternating polarisation states. Current instrumentation uses bespoke Pockels-effect cells to select the polarisation state. Here, we investigate an alternative off-the-shelf solution, a liquid crystal retarder, and discuss the potential impact of differences in performance. We show through electrical simulation of the photodiode-based detectors, and assessment of both types of polarisation device, that although the switching rate is slower the off-the-shelf LCD retarder is a viable replacement for a bespoke Pockels-effect cell. The simplifications arising from the use of off-the-shelf components allows easier and quicker instrumentation deployment., Comment: 6 pages, 9 figures, 1 table. Accepted by RAS Techniques and Instruments: 2023 March 1

Published
2023

148. AI Chat Assistants can Improve Conversations about Divisive Topics

Author

Argyle, Lisa P., Busby, Ethan, Gubler, Joshua, Bail, Chris, Howe, Thomas, Rytting, Christopher, and Wingate, David

Subjects
Computer Science - Human-Computer Interaction, Computer Science - Artificial Intelligence, Computer Science - Computation and Language
Abstract

A rapidly increasing amount of human conversation occurs online. But divisiveness and conflict can fester in text-based interactions on social media platforms, in messaging apps, and on other digital forums. Such toxicity increases polarization and, importantly, corrodes the capacity of diverse societies to develop efficient solutions to complex social problems that impact everyone. Scholars and civil society groups promote interventions that can make interpersonal conversations less divisive or more productive in offline settings, but scaling these efforts to the amount of discourse that occurs online is extremely challenging. We present results of a large-scale experiment that demonstrates how online conversations about divisive topics can be improved with artificial intelligence tools. Specifically, we employ a large language model to make real-time, evidence-based recommendations intended to improve participants' perception of feeling understood in conversations. We find that these interventions improve the reported quality of the conversation, reduce political divisiveness, and improve the tone, without systematically changing the content of the conversation or moving people's policy attitudes. These findings have important implications for future research on social media, political deliberation, and the growing community of scholars interested in the place of artificial intelligence within computational social science.

Published
2023

149. Observation of Coherently Coupled Cation Spin Dynamics in an Insulating Ferrimagnetic Oxide

Author

Klewe, C., Shafer, P., Shoup, J. E., Kons, C., Pogoryelov, Y., Knut, R., Gray, B. A., Jeon, H. -M., Howe, B. M., Karis, O., Suzuki, Y., Arenholz, E., Arena, D. A., and Emori, S.

Subjects
Condensed Matter - Materials Science, Condensed Matter - Mesoscale and Nanoscale Physics
Abstract

Many technologically useful magnetic oxides are ferrimagnetic insulators, which consist of chemically distinct cations. Here, we examine the spin dynamics of different magnetic cations in ferrimagnetic NiZnAl-ferrite (Ni$_{0.65}$Zn$_{0.35}$Al$_{0.8}$Fe$_{1.2}$O$_4$) under continuous microwave excitation. Specifically, we employ time-resolved x-ray ferromagnetic resonance to separately probe Fe$^{2+/3+}$ and Ni$^{2+}$ cations on different sublattice sites. Our results show that the precessing cation moments retain a rigid, collinear configuration to within $\approx$2$^\circ$. Moreover, the effective spin relaxation is identical to within $<$10% for all magnetic cations in the ferrite. We thus validate the oft-assumed ``ferromagnetic-like'' dynamics in resonantly driven ferrimagnetic oxides, where the magnetic moments from different cations precess as a coherent, collective magnetization.

Published
2023
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150. Adapting to Skew: Imputing Spatiotemporal Urban Data with 3D Partial Convolutions and Biased Masking

Author

Han, Bin and Howe, Bill

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Computers and Society
Abstract

We adapt image inpainting techniques to impute large, irregular missing regions in urban settings characterized by sparsity, variance in both space and time, and anomalous events. Missing regions in urban data can be caused by sensor or software failures, data quality issues, interference from weather events, incomplete data collection, or varying data use regulations; any missing data can render the entire dataset unusable for downstream applications. To ensure coverage and utility, we adapt computer vision techniques for image inpainting to operate on 3D histograms (2D space + 1D time) commonly used for data exchange in urban settings. Adapting these techniques to the spatiotemporal setting requires handling skew: urban data tend to follow population density patterns (small dense regions surrounded by large sparse areas); these patterns can dominate the learning process and fool the model into ignoring local or transient effects. To combat skew, we 1) train simultaneously in space and time, and 2) focus attention on dense regions by biasing the masks used for training to the skew in the data. We evaluate the core model and these two extensions using the NYC taxi data and the NYC bikeshare data, simulating different conditions for missing data. We show that the core model is effective qualitatively and quantitatively, and that biased masking during training reduces error in a variety of scenarios. We also articulate a tradeoff in varying the number of timesteps per training sample: too few timesteps and the model ignores transient events; too many timesteps and the model is slow to train with limited performance gain.

Published
2023

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