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154,372 results on '"Shepherd BE"'

56. Adoptive transfer of personalized neoantigen-reactive TCR-transduced T cells in metastatic colorectal cancer: phase 2 trial interim results

Author

Parkhurst, Maria, Goff, Stephanie L., Lowery, Frank J., Beyer, Rachel K., Halas, Hyunmi, Robbins, Paul F., Prickett, Todd D., Gartner, Jared J., Sindiri, Sivasish, Krishna, Sri, Zacharakis, Nikolaos, Ngo, Lien, Ray, Satyajit, Bera, Alakesh, Shepherd, Ryan, Levin, Noam, Kim, Sanghyun P., Copeland, Amy, Nah, Shirley, Levi, Shoshana, Parikh, Neilesh, Kwong, Mei Li M., Klemen, Nicholas D., Yang, James C., and Rosenberg, Steven A.

Published
2024
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59. Maine Early Childhood Consultation Partnership® (ECCP®) Pilot Final Evaluation Report

Author

SRI Education, Betsy Davies-Mercier, Jennifer Nakamura, Sally Shepherd, Kirby Chow, and Hannah Kelly

Abstract

In 2022-23, SRI Education conducted an evaluation of a pilot implementation of the Maine Early Childhood Consultation Partnership® (ECCP®) for Maine's Department of Health and Human Services, Office of Child and Family Services. Created and developed by Advanced Behavioral Health, Inc., ECCP® is an evidence-based, manualized model of infant and early childhood mental health consultation (IECMHC) that builds capacity of the early care and education workforce to address young children's social-emotional and behavioral needs through intensive, time-limited consultation with a trained mental health consultant. SRI Education collected and analyzed data from state leaders, consultants, trainers, supervisors, teachers and parents/guardians in five counties to assess the pilot implementation and provide recommendations for statewide scale up and sustainability of the model. [This report was prepared for Office of Child & Family Services, Maine Department of Health and Human Services.]

Published
2023

60. DeepEMC-T2 Mapping: Deep Learning-Enabled T2 Mapping Based on Echo Modulation Curve Modeling

Author

Pei, Haoyang, Shepherd, Timothy M., Wang, Yao, Liu, Fang, Sodickson, Daniel K, Ben-Eliezer, Noam, and Feng, Li

Subjects
Electrical Engineering and Systems Science - Image and Video Processing
Abstract

Purpose: Echo modulation curve (EMC) modeling can provide accurate and reproducible quantification of T2 relaxation times. The standard EMC-T2 mapping framework, however, requires sufficient echoes and cumbersome pixel-wise dictionary-matching steps. This work proposes a deep learning version of EMC-T2 mapping, called DeepEMC-T2 mapping, to efficiently estimate accurate T2 maps from fewer echoes without a dictionary. Methods: DeepEMC-T2 mapping was developed using a modified U-Net to estimate both T2 and Proton Density (PD) maps directly from multi-echo spin-echo (MESE) images. The modified U-Net employs several new features to improve the accuracy of T2/PD estimation. MESE datasets from 68 subjects were used for training and evaluation of the DeepEMC-T2 mapping technique. Multiple experiments were conducted to evaluate the impact of the proposed new features on DeepEMC-T2 mapping. Results: DeepEMC-T2 mapping achieved T2 estimation errors ranging from 3%-12% in different T2 ranges and 0.8%-1.7% for PD estimation with 10/7/5/3 echoes, which yielded more accurate parameter estimation than standard EMC-T2 mapping. The new features proposed in DeepEMC-T2 mapping enabled improved parameter estimation. The use of a larger echo spacing with fewer echoes can maintain the accuracy of T2 and PD estimations while reducing the number of 180-degree refocusing pulses. Conclusions: DeepEMC-T2 mapping enables simplified, efficient, and accurate T2 quantification directly from MESE images without a time-consuming dictionary-matching step and requires fewer echoes. This allows for increased volumetric coverage and/or decreased SAR by reducing the number of 180-degree refocusing pulses.

Published
2024

61. Identifying probabilistic weather regimes targeted to a local-scale impact variable

Author

Spuler, Fiona Raphaela, Kretschmer, Marlene, Kovalchuk, Yevgeniya, Balmaseda, Magdalena Alonso, and Shepherd, Theodore G.

Subjects
Physics - Geophysics
Abstract

Weather regimes are recurrent and persistent large-scale atmospheric circulation patterns that modulate the occurrence of local impact variables such as extreme precipitation. In their capacity as mediators between long-range teleconnections and these local extremes, they have shown potential for improving sub-seasonal forecasting as well as long-term climate projections. However, existing methods for identifying weather regimes are not designed to capture the physical processes relevant to the impact variable in question while still representing the full atmospheric phase space. This paper introduces a novel probabilistic machine learning method, RMM-VAE, for identifying weather regimes targeted to a local-scale impact variable. Based on a variational autoencoder architecture, the method combines non-linear dimensionality reduction with a prediction task and probabilistic clustering in a coherent architecture. The new method is applied to identify circulation patterns over the Mediterranean region targeted to precipitation over Morocco and compared to three existing approaches, two established linear methods and another machine learning approach. The RMM-VAE method identifies regimes that are more predictive of the target variable compared to the two linear methods, and more robust and persistent compared to the alternative machine learning method, while also improving the reconstruction of the input space. The results demonstrate the potential benefit of the new method for use in various climate applications such as sub-seasonal forecasting, while also highlighting the trade-offs involved in targeted clustering.

Published
2024

62. Understanding Difference-in-differences methods to evaluate policy effects with staggered adoption: an application to Medicaid and HIV

Author

Thome, Julia C., Rebeiro, Peter F., Spieker, Andrew J., and Shepherd, Bryan E.

Subjects
Statistics - Methodology
Abstract

While a randomized control trial is considered the gold standard for estimating causal treatment effects, there are many research settings in which randomization is infeasible or unethical. In such cases, researchers rely on analytical methods for observational data to explore causal relationships. Difference-in-differences (DID) is one such method that, most commonly, estimates a difference in some mean outcome in a group before and after the implementation of an intervention or policy and compares this with a control group followed over the same time (i.e., a group that did not implement the intervention or policy). Although DID modeling approaches have been gaining popularity in public health research, the majority of these approaches and their extensions are developed and shared within the economics literature. While extensions of DID modeling approaches may be straightforward to apply to observational data in any field, the complexities and assumptions involved in newer approaches are often misunderstood. In this paper, we focus on recent extensions of the DID method and their relationships to linear models in the setting of staggered treatment adoption over multiple years. We detail the identification and estimation of the average treatment effect among the treated using potential outcomes notation, highlighting the assumptions necessary to produce valid estimates. These concepts are described within the context of Medicaid expansion and retention in care among people living with HIV (PWH) in the United States. While each DID approach is potentially valid, understanding their different assumptions and choosing an appropriate method can have important implications for policy-makers, funders, and public health as a whole.

Published
2024

63. Between- and Within-Cluster Spearman Rank Correlations

Author

Tu, Shengxin, Li, Chun, and Shepherd, Bryan E.

Subjects
Statistics - Methodology
Abstract

Clustered data are common in practice. Clustering arises when subjects are measured repeatedly, or subjects are nested in groups (e.g., households, schools). It is often of interest to evaluate the correlation between two variables with clustered data. There are three commonly used Pearson correlation coefficients (total, between-, and within-cluster), which together provide an enriched perspective of the correlation. However, these Pearson correlation coefficients are sensitive to extreme values and skewed distributions. They also depend on the scale of the data and are not applicable to ordered categorical data. Current non-parametric measures for clustered data are only for the total correlation. Here we define population parameters for the between- and within-cluster Spearman rank correlations. The definitions are natural extensions of the Pearson between- and within-cluster correlations to the rank scale. We show that the total Spearman rank correlation approximates a weighted sum of the between- and within-cluster Spearman rank correlations, where the weights are functions of rank intraclass correlations of the two random variables. We also discuss the equivalence between the within-cluster Spearman rank correlation and the covariate-adjusted partial Spearman rank correlation. Furthermore, we describe estimation and inference for the three Spearman rank correlations, conduct simulations to evaluate the performance of our estimators, and illustrate their use with data from a longitudinal biomarker study and a clustered randomized trial.

Published
2024

64. Doping Liquid Argon with Xenon in ProtoDUNE Single-Phase: Effects on Scintillation Light

Author

DUNE Collaboration, Abud, A. Abed, Abi, B., Acciarri, R., Acero, M. A., Adames, M. R., Adamov, G., Adamowski, M., Adams, D., Adinolfi, M., Adriano, C., Aduszkiewicz, A., Aguilar, J., Aimard, B., Akbar, F., Allison, K., Monsalve, S. Alonso, Alrashed, M., Alton, A., Alvarez, R., Es-sghir, H. Amar, Amedo, P., Anderson, J., Andrade, D. A., Andreopoulos, C., Andreotti, M., Andrews, M. P., Andrianala, F., Andringa, S., Anfimov, N., Ankowski, A., Antoniassi, M., Antonova, M., Antoshkin, A., Aranda-Fernandez, A., Arellano, L., Diaz, E. Arrieta, Arroyave, M. A., Asaadi, J., Ashkenazi, A., Asquith, L., Atkin, E., Auguste, D., Aurisano, A., Aushev, V., Autiero, D., Azfar, F., Back, A., Back, H., Back, J. J., Bagaturia, I., Bagby, L., Balashov, N., Balasubramanian, S., Baldi, P., Baldini, W., Baller, B., Bambah, B., Banerjee, R., Barao, F., Barenboim, G., BarhamAlzás, P., Barker, G. J., Barkhouse, W., Barr, G., Monarca, J. Barranco, Barros, A., Barros, N., Barrow, D., Barrow, J. L., Basharina-Freshville, A., Bashyal, A., Basque, V., Batchelor, C., Bathe-Peters, L., Battat, J. B. R., Battisti, F., Bay, F., Bazetto, M. C. Q., Alba, J. L. L. Bazo, Beacom, J. F., Bechetoille, E., Behera, B., Belchior, E., Bell, G., Bellantoni, L., Bellettini, G., Bellini, V., Beltramello, O., Benekos, N., Montiel, C. Benitez, Benjamin, D., Neves, F. Bento, Berger, J., Berkman, S., Bernardini, P., Bersani, A., Bertolucci, S., Betancourt, M., Rodríguez, A. Betancur, Bevan, A., Bezawada, Y., Bezerra, A. T., Bezerra, T. J., Bhat, A., Bhatnagar, V., Bhatt, J., Bhattacharjee, M., Bhattacharya, M., Bhuller, S., Bhuyan, B., Biagi, S., Bian, J., Biery, K., Bilki, B., Bishai, M., Bitadze, A., Blake, A., Blaszczyk, F. D., Blazey, G. C., Blucher, E., Boissevain, J., Bolognesi, S., Bolton, T., Bomben, L., Bonesini, M., Bonilla-Diaz, C., Bonini, F., Booth, A., Boran, F., Bordoni, S., Merlo, R. Borges, Borkum, A., Bostan, N., Bracinik, J., Braga, D., Brahma, B., Brailsford, D., Bramati, F., Branca, A., Brandt, A., Bremer, J., Brew, C., Brice, S. J., Brio, V., Brizzolari, C., Bromberg, C., Brooke, J., Bross, A., Brunetti, G., Brunetti, M., Buchanan, N., Budd, H., Buergi, J., Burgardt, D., Butchart, S., V., G. Caceres, Cagnoli, I., Cai, T., Calabrese, R., Calcutt, J., Calin, M., Calivers, L., Calvo, E., Caminata, A., Campanelli, W., Benitez, A. Campos, Canci, N., Capó, J., Caracas, I., Caratelli, D., Carber, D., Carceller, J. M., Carini, G., Carlus, B., Carneiro, M. F., Carniti, P., Terrazas, I. Caro, Carranza, H., Carrara, N., Carroll, L., Carroll, T., Carter, A., Casazza, D., Forero, J. F. Castaño, Castaño, F. A., Castillo, A., Castromonte, C., Catano-Mur, E., Cattadori, C., Cavalier, F., Cavanna, F., Centro, S., Cerati, G., Cervelli, A., Villanueva, A. Cervera, Chakraborty, K., Chalifour, M., Chappell, A., Charitonidis, N., Chatterjee, A., Chen, H., Chen, M., Chen, W. C., Chen, Y., Chen-Wishart, Z., Cherdack, D., Chi, C., Chirco, R., Chitirasreemadam, N., Cho, K., Choate, S., Chokheli, D., Chong, P. S., Chowdhury, B., Christian, D., Chukanov, A., Chung, M., Church, E., Cicala, M. F., Cicerchia, M., Cicero, V., Ciolini, R., Clair, J., Clarke, P., Cline, G., Coan, T. E., Cocco, A. G., Coelho, J. A. B., Cohen, A., Collot, J., Conley, E., Conrad, J. M., Convery, M., Cooke, P., Copello, S., Cova, P., Cox, C., Cremaldi, L., Cremonesi, L., Crespo-Anadón, J. I., Crisler, M., Cristaldo, E., Crnkovic, J., Crone, G., Cross, R., Cudd, A., Cuesta, C., Cui, Y., Cussans, D., Dai, J., Dalager, O., Dallavalle, R., da Motta, H., Dar, Z. A., Darby, R., Peres, L. Da Silva, David, Q., Davies, G. S., Davini, S., Dawson, J., De Aguiar, R., De Almeida, P., Debbins, P., De Bonis, I., Decowski, M. P., de Gouvêa, A., De Holanda, P. C., Astiz, I. L. De Icaza, De Jong, P., De la Torre, A., Delbart, A., Delepine, D., Delgado, M., Dell'Acqua, A., Monache, G. Delle, Delmonte, N., De Lurgio, P., Demario, R., Neto, J. R. T. de Mello, DeMuth, D. M., Dennis, S., Densham, C., Denton, P., Deptuch, G. W., De Roeck, A., De Romeri, V., Detje, J. P., Devine, J., Dharmapalan, R., Dias, M., Díaz, J. S., Díaz, F., Di Capua, F., Di Domenico, A., Di Domizio, S., Di Falco, S., Di Giulio, L., Ding, P., Di Noto, L., Diociaiuti, E., Distefano, C., Diurba, R., Diwan, M., Djurcic, Z., Doering, D., Dolan, S., Dolek, F., Dolinski, M. J., Domenici, D., Domine, L., Donati, S., Donon, Y., Doran, S., Douglas, D., Doyle, T. A., Dragone, A., Drielsma, F., Duarte, L., Duchesneau, D., Duffy, K., Dugas, K., Dunne, P., Dutta, B., Duyang, H., Dvornikov, O., Dwyer, D. A., Dyshkant, A. S., Dytman, S., Eads, M., Earle, A., Edayath, S., Edmunds, D., Eisch, J., Englezos, P., Ereditato, A., Erjavec, T., Escobar, C. O., Evans, J. J., Ewart, E., Ezeribe, A. C., Fahey, K., Fajt, L., Falcone, A., Fani', M., Farnese, C., Farzan, Y., Fedoseev, D., Felix, J., Feng, Y., Fernandez-Martinez, E., Ferraro, F., Ferry, G., Fields, L., Filip, P., Filkins, A., Filthaut, F., Fine, R., Fiorillo, G., Fiorini, M., Fogarty, S., Foreman, W., Fowler, J., Franc, J., Francis, K., Franco, D., Franklin, J., Freeman, J., Fried, J., Friedland, A., Fuess, S., Furic, I. K., Furman, K., Furmanski, A. P., Gabrielli, A., Gago, A. M., Galizzi, F., Gallagher, H., Gallas, A., Gallice, N., Galymov, V., Gamberini, E., Gamble, T., Ganacim, F., Gandhi, R., Ganguly, S., Gao, F., Gao, S., Garcia-Gamez, D., García-Peris, M. Á., Gardim, F., Gardiner, S., Gastler, D., Gauch, A., Gauvreau, J., Gauzzi, P., Ge, G., Geffroy, N., Gelli, B., Gent, S., Gerlach, L., Ghorbani-Moghaddam, Z., Giammaria, P., Giammaria, T., Gibin, D., Gil-Botella, I., Gilligan, S., Gioiosa, A., Giovannella, S., Girerd, C., Giri, A. K., Giugliano, C., Giusti, V., Gnani, D., Gogota, O., Gollapinni, S., Gollwitzer, K., Gomes, R. A., Bermeo, L. V. Gomez, Fajardo, L. S. Gomez, Gonnella, F., Gonzalez-Diaz, D., Gonzalez-Lopez, M., Goodman, M. C., Goswami, S., Gotti, C., Goudeau, J., Goudzovski, E., Grace, C., Gramellini, E., Gran, R., Granados, E., Granger, P., Grant, C., Gratieri, D. R., Grauso, G., Green, P., Greenberg, S., Greer, J., Griffith, W. C., Groetschla, F. T., Grzelak, K., Gu, W., Guarino, V., Guarise, M., Guenette, R., Guerard, E., Guerzoni, M., Guffanti, D., Guglielmi, A., Guo, B., Guo, Y., Gupta, A., Gupta, V., Gurung, G., Gutierrez, D., Guzowski, P., Guzzo, M. M., Gwon, S., Haaf, K., Habig, A., Hadavand, H., Haenni, R., Hagaman, L., Hahn, A., Haiston, J., Hakenmueller, J., Hamernik, T., Hamilton, P., Hancock, J., Happacher, F., Harris, D. A., Hartnell, J., Hartnett, T., Harton, J., Hasegawa, T., Hasnip, C., Hatcher, R., Hayrapetyan, K., Hays, J., Hazen, E., He, M., Heavey, A., Heeger, K. M., Heise, J., Henry, S., Morquecho, M. A. Hernandez, Herner, K., Hewes, V., Higuera, A., Hilgenberg, C., Hillier, S. J., Himmel, A., Hinkle, E., Hirsch, L. R., Ho, J., Hoff, J., Holin, A., Holvey, T., Hoppe, E., Horton-Smith, G. A., Hostert, M., Houdy, T., Howard, B., Howell, R., Hristova, I., Hronek, M. S., Huang, J., Huang, R. G., Hulcher, Z., Ibrahim, M., Iles, G., Ilic, N., Iliescu, A. M., Illingworth, R., Ingratta, G., Ioannisian, A., Irwin, B., Isenhower, L., Oliveira, M. Ismerio, Itay, R., Jackson, C. M., Jain, V., James, E., Jang, W., Jargowsky, B., Jena, D., Ji, X., Jiang, C., Jiang, J., Jiang, L., Jipa, A., Joaquim, F. R., Johnson, W., Jones, B., Jones, R., Fernández, D. José, Jovancevic, N., Judah, M., Jung, C. K., Junk, T., Jwa, Y., Kabirnezhad, M., Kaboth, A. C., Kadenko, I., Kakorin, I., Kalitkina, A., Kalra, D., Kamiya, F., Kandemir, M., Kaplan, D. M., Karagiorgi, G., Karaman, G., Karcher, A., Karyotakis, Y., Kasai, S., Kasetti, S. P., Kashur, L., Katsioulas, I., Kauther, A., Kazaryan, N., Ke, L., Kearns, E., Keener, P. T., Kelly, K. J., Kemp, E., Kemularia, O., Kermaidic, Y., Ketchum, W., Kettell, S. H., Khabibullin, M., Khan, N., Khvedelidze, A., Kim, D., Kim, J., King, B., Kirby, B., Kirby, M., Klein, J., Kleykamp, J., Klustova, A., Kobilarcik, T., Koch, L., Koehler, K., Koerner, L. W., Koh, D. H., Kolupaeva, L., Korablev, D., Kordosky, M., Kosc, T., Kose, U., Kostelecký, V. A., Kothekar, K., Kotler, I., Kovalcuk, M., Kozhukalov, V., Krah, W., Kralik, R., Kramer, M., Kreczko, L., Krennrich, F., Kreslo, I., Kroupova, T., Kubota, S., Kubu, M., Kudenko, Y., Kudryavtsev, V. A., Kuhlmann, S., Kumar, J., Kumar, P., Kumaran, S., Kunze, P., Kunzmann, J., Kuravi, R., Kurita, N., Kuruppu, C., Kus, V., Kutter, T., Kvasnicka, J., Labree, T., Lackey, T., Lambert, A., Land, B. J., Lane, C. E., Lane, N., Lang, K., Langford, T., Langstaff, M., Lanni, F., Lantwin, O., Larkin, J., Lasorak, P., Last, D., Laudrain, A., Laundrie, A., Laurenti, G., Lavaut, E., Lawrence, A., Laycock, P., Lazanu, I., Lazzaroni, M., Le, T., Leardini, S., Learned, J., LeCompte, T., Lee, C., Legin, V., Miotto, G. Lehmann, Lehnert, R., de Oliveira, M. A. Leigui, Leitner, M., Silverio, D. Leon, Lepin, L. M., Li, J. -Y., Li, S. W., Li, Y., Liao, H., Lin, C. S., Lindebaum, D., Lineros, R. A., Ling, J., Lister, A., Littlejohn, B. R., Liu, H., Liu, J., Liu, Y., Lockwitz, S., Lokajicek, M., Lomidze, I., Long, K., Lopes, T. V., Lopez, J., de Rego, I. López, March, N. López, Lord, T., LoSecco, J. M., Louis, W. C., Sanchez, A. Lozano, Lu, X. -G., Luk, K. B., Lunday, B., Luo, X., Luppi, E., Maalmi, J., MacFarlane, D., Machado, A. A., Machado, P., Macias, C. T., Macier, J. R., MacMahon, M., Maddalena, A., Madera, A., Madigan, P., Magill, S., Magueur, C., Mahn, K., Maio, A., Major, A., Majumdar, K., Man, M., Mandujano, R. C., Maneira, J., Manly, S., Mann, A., Manolopoulos, K., Plata, M. Manrique, Corchado, S. Manthey, Manyam, V. N., Marchan, M., Marchionni, A., Marciano, W., Marfatia, D., Mariani, C., Maricic, J., Marinho, F., Marino, A. D., Markiewicz, T., Marques, F. Das Chagas, Marsden, D., Marshak, M., Marshall, C. M., Marshall, J., Martín-Albo, J., Martinez, N., Caicedo, D. A. Martinez, López, F. Martínez, Miravé, P. Martínez, Martynenko, S., Mascagna, V., Massari, C., Mastbaum, A., Matichard, F., Matsuno, S., Matteucci, G., Matthews, J., Mauger, C., Mauri, N., Mavrokoridis, K., Mawby, I., Mazza, R., Mazzacane, A., McAskill, T., McConkey, N., McFarland, K. S., McGrew, C., McNab, A., Meazza, L., Meddage, V. C. N., Mehta, B., Mehta, P., Melas, P., Mena, O., Mendez, H., Mendez, P., Méndez, D. P., Menegolli, A., Meng, G., Messier, M. D., Metallo, S., Metcalf, J., Metcalf, W., Mewes, M., Meyer, H., Miao, T., Miccoli, A., Michna, G., Mikola, V., Milincic, R., Miller, G., Miller, W., Mineev, O., Minotti, A., Miralles, L., Miranda, O. G., Mironov, C., Miryala, S., Miscetti, S., Mishra, C. S., Mishra, S. R., Mislivec, A., Mitchell, M., Mladenov, D., Mocioiu, I., Mogan, A., Moggi, N., Mohanta, R., Mohayai, T. A., Mokhov, N., Molina, J., Bueno, L. Molina, Montagna, E., Montanari, A., Montanari, C., Montanari, D., Montanino, D., Zetina, L. M. Montaño, Mooney, M., Moor, A. F., Moore, Z., Moreno, D., Moreno-Palacios, O., Morescalchi, L., Moretti, D., Moretti, R., Morris, C., Mossey, C., Mote, M., Moura, C. A., Mouster, G., Mu, W., Mualem, L., Mueller, J., Muether, M., Muheim, F., Muir, A., Mulhearn, M., Munford, D., Munteanu, L. J., Muramatsu, H., Muraz, J., Murphy, M., Murphy, T., Muse, J., Mytilinaki, A., Nachtman, J., Nagai, Y., Nagu, S., Nalbandyan, M., Nandakumar, R., Naples, D., Narita, S., Nath, A., Navrer-Agasson, A., Nayak, N., Nebot-Guinot, M., Nehm, A., Nelson, J. K., Neogi, O., Nesbit, J., Nessi, M., Newbold, D., Newcomer, M., Nichol, R., Nicolas-Arnaldos, F., Nikolica, A., Nikolov, J., Niner, E., Nishimura, K., Norman, A., Norrick, A., Novella, P., Nowak, J. A., Oberling, M., Ochoa-Ricoux, J. P., Oh, S., Oh, S. B., Olivier, A., Olshevskiy, A., Olson, T., Onel, Y., Onishchuk, Y., Oranday, A., Osbiston, M., Vélez, J. A. Osorio, Ormachea, L. Otiniano, Ott, J., Pagani, L., Palacio, G., Palamara, O., Palestini, S., Paley, J. M., Pallavicini, M., Palomares, C., Pan, S., Panda, P., Vazquez, W. Panduro, Pantic, E., Paolone, V., Papadimitriou, V., Papaleo, R., Papanestis, A., Papoulias, D., Paramesvaran, S., Paris, A., Parke, S., Parozzi, E., Parsa, S., Parsa, Z., Parveen, S., Parvu, M., Pasciuto, D., Pascoli, S., Pasqualini, L., Pasternak, J., Patrick, C., Patrizii, L., Patterson, R. B., Patzak, T., Paudel, A., Paulucci, L., Pavlovic, Z., Pawloski, G., Payne, D., Pec, V., Pedreschi, E., Peeters, S. J. M., Perez, A. Pena, Pennacchio, E., Penzo, A., Peres, O. L. G., Gonzalez, Y. F. Perez, Pérez-Molina, L., Pernas, C., Perry, J., Pershey, D., Pessina, G., Petrillo, G., Petta, C., Petti, R., Pia, V., Pickering, L., Pietropaolo, F., Pimentel, V. L., Pinaroli, G., Pinchault, J., Plows, K., Plunkett, R., Pollack, C., Pollman, T., Pompa, F., Pons, X., Poonthottathil, N., Poppi, F., Pordes, S., Porter, J., Potekhin, M., Potenza, R., Pozimski, J., Pozzato, M., Prakash, S., Prakash, T., Pratt, C., Prest, M., Psihas, F., Pugnere, D., Qian, X., Raaf, J. L., Radeka, V., Rademacker, J., Radics, B., Rafique, A., Raguzin, E., Rai, M., Rajaoalisoa, M., Rakhno, I., Rakotondravohitra, L., Ralte, L., Delgado, M. A. Ramirez, Ramson, B., Rappoldi, A., Raselli, G., Ratoff, P., Ray, R., Razafinime, H., Rea, E. M., Real, J. S., Rebel, B., Rechenmacher, R., Reggiani-Guzzo, M., Reichenbacher, J., Reitzner, S. D., Sfar, H. Rejeb, Renner, E., Renshaw, A., Rescia, S., Resnati, F., Restrepo, D., Reynolds, C., Ribas, M., Riboldi, S., Riccio, C., Riccobene, G., Ricol, J. S., Rigan, M., Rincón, E. V., Ritchie-Yates, A., Ritter, S., Rivera, D., Rivera, R., Robert, A., Rocha, J. L. Rocabado, Rochester, L., Roda, M., Rodrigues, P., Alonso, M. J. Rodriguez, Rondon, J. Rodriguez, Rosauro-Alcaraz, S., Rosier, P., Ross, D., Rossella, M., Rossi, M., Ross-Lonergan, M., Roy, N., Roy, P., Rubbia, C., Ruggeri, A., Ferreira, G. Ruiz, Russell, B., Ruterbories, D., Rybnikov, A., Saa-Hernandez, A., Saakyan, R., Sacerdoti, S., Sahoo, S. K., Sahu, N., Sala, P., Samios, N., Samoylov, O., Sanchez, M. C., Bravo, A. Sánchez, Sanchez-Lucas, P., Sandberg, V., Sanders, D. A., Sankey, D., Santoro, D., Saoulidou, N., Sapienza, P., Sarasty, C., Sarcevic, I., Sarra, I., Savage, G., Savinov, V., Scanavini, G., Scaramelli, A., Scarff, A., Schefke, T., Schellman, H., Schifano, S., Schlabach, P., Schmitz, D., Schneider, A. W., Scholberg, K., Schukraft, A., Schuld, B., Segreto, E., Selyunin, A., Senise, C. R., Sensenig, J., Shaevitz, M. H., Shanahan, P., Sharma, P., Kumar, R., Shaw, K., Shaw, T., Shchablo, K., Shepherd-Themistocleous, C., Sheshukov, A., Shi, W., Shin, S., Shivakoti, S., Shoemaker, I., Shooltz, D., Shrock, R., Siddi, B., Silber, J., Simard, L., Sinclair, J., Sinev, G., Singh, Jaydip, Singh, J., Singh, L., Singh, P., Singh, V., Chauhan, S. Singh, Sipos, R., Sironneau, C., Sirri, G., Siyeon, K., Skarpaas, K., Smedley, J., Smith, E., Smith, J., Smith, P., Smolik, J., Smy, M., Snape, M., Snider, E. L., Snopok, P., Snowden-Ifft, D., Nunes, M. Soares, Sobel, H., Soderberg, M., Sokolov, S., Salinas, C. J. Solano, Söldner-Rembold, S., Soleti, S. R., Solomey, N., Solovov, V., Sondheim, W. E., Sorel, M., Sotnikov, A., Soto-Oton, J., Sousa, A., Soustruznik, K., Spinella, F., Spitz, J., Spooner, N. J. C., Spurgeon, K., Stalder, D., Stancari, M., Stanco, L., Steenis, J., Stein, R., Steiner, H. M., Lisbôa, A. F. Steklain, Stepanova, A., Stewart, J., Stillwell, B., Stock, J., Stocker, F., Stokes, T., Strait, M., Strauss, T., Strigari, L., Stuart, A., Suarez, J. G., Subash, J., Surdo, A., Suter, L., Sutera, C. M., Sutton, K., Suvorov, Y., Svoboda, R., Swain, S. K., Szczerbinska, B., Szelc, A. M., Sztuc, A., Taffara, A., Talukdar, N., Tamara, J., Tanaka, H. A., Tang, S., Taniuchi, N., Casanova, A. M. Tapia, Oregui, B. Tapia, Tapper, A., Tariq, S., Tarpara, E., Tatar, E., Tayloe, R., Tedeschi, D., Teklu, A. M., Vidal, J. 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Subjects
Physics - Instrumentation and Detectors
Abstract

Doping of liquid argon TPCs (LArTPCs) with a small concentration of xenon is a technique for light-shifting and facilitates the detection of the liquid argon scintillation light. In this paper, we present the results of the first doping test ever performed in a kiloton-scale LArTPC. From February to May 2020, we carried out this special run in the single-phase DUNE Far Detector prototype (ProtoDUNE-SP) at CERN, featuring 720 t of total liquid argon mass with 410 t of fiducial mass. A 5.4 ppm nitrogen contamination was present during the xenon doping campaign. The goal of the run was to measure the light and charge response of the detector to the addition of xenon, up to a concentration of 18.8 ppm. The main purpose was to test the possibility for reduction of non-uniformities in light collection, caused by deployment of photon detectors only within the anode planes. Light collection was analysed as a function of the xenon concentration, by using the pre-existing photon detection system (PDS) of ProtoDUNE-SP and an additional smaller set-up installed specifically for this run. In this paper we first summarize our current understanding of the argon-xenon energy transfer process and the impact of the presence of nitrogen in argon with and without xenon dopant. We then describe the key elements of ProtoDUNE-SP and the injection method deployed. Two dedicated photon detectors were able to collect the light produced by xenon and the total light. The ratio of these components was measured to be about 0.65 as 18.8 ppm of xenon were injected. We performed studies of the collection efficiency as a function of the distance between tracks and light detectors, demonstrating enhanced uniformity of response for the anode-mounted PDS. We also show that xenon doping can substantially recover light losses due to contamination of the liquid argon by nitrogen., Comment: 36 pages, 20 figures. Corrected author list; corrected typos across paper and polished text

Published
2024

66. Correlating fluorescence microscopy, optical and magnetic tweezers to study single chiral biopolymers such as DNA

Author

Shepherd, Jack W, Guilbaud, Sebastien, Zhou, Zhaokun, Howard, Jamieson, Burman, Matthew, Schaefer, Charley, Kerrigan, Adam, Steele-King, Clare, Noy, Agnes, and Leake, Mark C

Subjects
Physics - Biological Physics, Quantitative Biology - Biomolecules
Abstract

Biopolymer topology is critical for determining interactions inside cell environments, exemplified by DNA where its response to mechanical perturbation is as important as biochemical properties to its cellular roles. The dynamic structures of chiral biopolymers exhibit complex dependence with extension and torsion, however the physical mechanisms underpinning the emergence of structural motifs upon physiological twisting and stretching are poorly understood due to technological limitations in correlating force, torque and spatial localization information. We present COMBI-Tweez (Combined Optical and Magnetic BIomolecule TWEEZers), a transformative tool that overcomes these challenges by integrating optical trapping, time-resolved electromagnetic tweezers, and fluorescence microscopy, demonstrated on single DNA molecules, that can controllably form and visualise higher order structural motifs including plectonemes. This technology combined with cutting-edge MD simulations provides quantitative insight into complex dynamic structures relevant to DNA cellular processes and can be adapted to study a range of filamentous biopolymers.

Published
2024

67. The Impact of the Third Dredge-up and Mass Loss in Shaping the Initial-Final Mass Relation of White Dwarfs

Author

Addari, Francesco, Marigo, Paola, Bressan, Alessandro, Costa, Guglielmo, Shepherd, Kendall, and Volpato, Guglielmo

Subjects
Astrophysics - Solar and Stellar Astrophysics
Abstract

The initial-final mass relation (IFMR) plays a crucial role in understanding stellar structure and evolution by linking a star's initial mass to the mass of the resulting white dwarf. This study explores the IFMR in the initial mass range $0.8 \leq M_\mathrm{ini} / M_\odot \leq 4$ using full PARSEC evolutionary calculations supplemented with COLIBRI computations to complete the ejection of the envelope and obtain the final core mass. Recent works have shown that the supposed monotonicity of the IFMR is interrupted by a kink in the initial mass range $M_\mathrm{ini} \approx 1.65-2.10 M_\odot$, due to the interaction between recurrent dredge-up episodes and stellar winds in carbon stars evolving on the thermally-pulsing asymptotic giant branch phase. To reproduce the IFMR non-monotonic behavior we investigate the role of convective overshooting efficiency applied to the base of the convective envelope ($f_\mathrm{env}$) and to the borders of the pulse-driven convective zone ($f_\mathrm{pdcz}$), as well as its interplay with mass loss. We compare our models to observational data and find that $f_\mathrm{env}$ must vary with initial mass in order to accurately reproduce the IFMR's observed kink and slopes. We find some degeneracy between the overshooting parameters when only the IFMR information is used. Nonetheless, this analysis provides valuable insights into the internal mixing processes during the TP-AGB phase., Comment: Accepted for publication in ApJ. 17 pages, 12 figures

Published
2024
Full Text
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68. An essential and highly selective protein import pathway encoded by nucleus-forming phage

Author

Morgan, Chase J, Enustun, Eray, Armbruster, Emily G, Birkholz, Erica A, Prichard, Amy, Forman, Taylor, Aindow, Ann, Wannasrichan, Wichanan, Peters, Sela, Inlow, Koe, Shepherd, Isabelle L, Razavilar, Alma, Chaikeeratisak, Vorrapon, Adler, Benjamin A, Cress, Brady F, Doudna, Jennifer A, Pogliano, Kit, Villa, Elizabeth, Corbett, Kevin D, and Pogliano, Joe

Subjects
Biochemistry and Cell Biology, Biological Sciences, Genetics, 1.1 Normal biological development and functioning, Generic health relevance, Viral Proteins, Bacteriophages, Protein Transport, Cell Nucleus, Virus Replication, phage, protein trafficking, phage nucleus
Abstract

Targeting proteins to specific subcellular destinations is essential in prokaryotes, eukaryotes, and the viruses that infect them. Chimalliviridae phages encapsulate their genomes in a nucleus-like replication compartment composed of the protein chimallin (ChmA) that excludes ribosomes and decouples transcription from translation. These phages selectively partition proteins between the phage nucleus and the bacterial cytoplasm. Currently, the genes and signals that govern selective protein import into the phage nucleus are unknown. Here, we identify two components of this protein import pathway: a species-specific surface-exposed region of a phage intranuclear protein required for nuclear entry and a conserved protein, PicA (Protein importer of chimalliviruses A), that facilitates cargo protein trafficking across the phage nuclear shell. We also identify a defective cargo protein that is targeted to PicA on the nuclear periphery but fails to enter the nucleus, providing insight into the mechanism of nuclear protein trafficking. Using CRISPRi-ART protein expression knockdown of PicA, we show that PicA is essential early in the chimallivirus replication cycle. Together, our results allow us to propose a multistep model for the Protein Import Chimallivirus pathway, where proteins are targeted to PicA by amino acids on their surface and then licensed by PicA for nuclear entry. The divergence in the selectivity of this pathway between closely related chimalliviruses implicates its role as a key player in the evolutionary arms race between competing phages and their hosts.

Published
2024

69. The DUNE Far Detector Vertical Drift Technology, Technical Design Report

Author

DUNE Collaboration, Abud, A. Abed, Abi, B., Acciarri, R., Acero, M. A., Adames, M. R., Adamov, G., Adamowski, M., Adams, D., Adinolfi, M., Adriano, C., Aduszkiewicz, A., Aguilar, J., Aimard, B., Akbar, F., Allison, K., Monsalve, S. Alonso, Alrashed, M., Alton, A., Alvarez, R., Amar, H., Amedo, P., Anderson, J., Andrade, D. A., Andreopoulos, C., Andreotti, M., Andrews, M. P., Andrianala, F., Andringa, S., Anfimov, N., Ankowski, A., Antoniassi, M., Antonova, M., Antoshkin, A., Aranda-Fernandez, A., Arellano, L., Diaz, E. Arrieta, Arroyave, M. A., Asaadi, J., Ashkenazi, A., Asquith, L., Atkin, E., Auguste, D., Aurisano, A., Aushev, V., Autiero, D., Azfar, F., Back, A., Back, H., Back, J. J., Bagaturia, I., Bagby, L., Balashov, N., Balasubramanian, S., Baldi, P., Baldini, W., Baller, B., Bambah, B., Banerjee, R., Barao, F., Barenboim, G., Alzás, P. Barham, Barker, G. J., Barkhouse, W., Barr, G., Monarca, J. Barranco, Barros, A., Barros, N., Barrow, D., Barrow, J. L., Basharina-Freshville, A., Bashyal, A., Basque, V., Batchelor, C., Bathe-Peters, L., Battat, J. B. R., Battisti, F., Bay, F., Bazetto, M. C. Q., Alba, J. L. L. Bazo, Beacom, J. F., Bechetoille, E., Behera, B., Belchior, E., Bell, G., Bellantoni, L., Bellettini, G., Bellini, V., Beltramello, O., Benekos, N., Montiel, C. Benitez, Benjamin, D., Neves, F. Bento, Berger, J., Berkman, S., Bernardini, P., Bersani, A., Bertolucci, S., Betancourt, M., Rodríguez, A. Betancur, Bevan, A., Bezawada, Y., Bezerra, A. T., Bezerra, T. J., Bhat, A., Bhatnagar, V., Bhatt, J., Bhattacharjee, M., Bhattacharya, M., Bhuller, S., Bhuyan, B., Biagi, S., Bian, J., Biery, K., Bilki, B., Bishai, M., Bitadze, A., Blake, A., Blaszczyk, F. D., Blazey, G. C., Blucher, E., Boissevain, J., Bolognesi, S., Bolton, T., Bomben, L., Bonesini, M., Bonilla-Diaz, C., Bonini, F., Booth, A., Boran, F., Bordoni, S., Merlo, R. Borges, Borkum, A., Bostan, N., Bracinik, J., Braga, D., Brahma, B., Brailsford, D., Bramati, F., Branca, A., Brandt, A., Bremer, J., Brew, C., Brice, S. J., Brio, V., Brizzolari, C., Bromberg, C., Brooke, J., Bross, A., Brunetti, G., Brunetti, M., Buchanan, N., Budd, H., Buergi, J., Burgardt, D., Butchart, S., V., G. Caceres, Cagnoli, I., Cai, T., Calabrese, R., Calcutt, J., Calin, M., Calivers, L., Calvo, E., Caminata, A., Campanelli, W., Benitez, A. Campos, Canci, N., Capó, J., Caracas, I., Caratelli, D., Carber, D., Carceller, J. M., Carini, G., Carlus, B., Carneiro, M. F., Carniti, P., Terrazas, I. Caro, Carranza, H., Carrara, N., Carroll, L., Carroll, T., Carter, A., Casazza, D., Forero, J. F. Castaño, Castaño, F. A., Castillo, A., Castromonte, C., Catano-Mur, E., Cattadori, C., Cavalier, F., Cavanna, F., Centro, S., Cerati, G., Cervelli, A., Villanueva, A. Cervera, Chakraborty, K., Chalifour, M., Chappell, A., Charitonidis, N., Chatterjee, A., Chen, H., Chen, M., Chen, W. C., Chen, Y., Chen-Wishart, Z., Cherdack, D., Chi, C., Chirco, R., Chitirasreemadam, N., Cho, K., Choate, S., Chokheli, D., Chong, P. S., Chowdhury, B., Christian, D., Chukanov, A., Chung, M., Church, E., Cicala, M. F., Cicerchia, M., Cicero, V., Ciolini, R., Clair, J., Clarke, P., Cline, G., Coan, T. E., Cocco, A. G., Coelho, J. A. B., Cohen, A., Collot, J., Conley, E., Conrad, J. M., Convery, M., Cooke, P., Copello, S., Cova, P., Cox, C., Cremaldi, L., Cremonesi, L., Crespo-Anadón, J. I., Crisler, M., Cristaldo, E., Crnkovic, J., Crone, G., Cross, R., Cudd, A., Cuesta, C., Cui, Y., Cussans, D., Dai, J., Dalager, O., Dallavalle, R., da Motta, H., Dar, Z. A., Darby, R., Peres, L. Da Silva, David, Q., Davies, G. S., Davini, S., Dawson, J., De Aguiar, R., De Almeida, P., Debbins, P., De Bonis, I., Decowski, M. P., de Gouvêa, A., De Holanda, P. C., Astiz, I. L. De Icaza, De Jong, P., De la Torre, A., Delbart, A., Delepine, D., Delgado, M., Dell'Acqua, A., Monache, G. Delle, Delmonte, N., De Lurgio, P., Demario, R., Neto, J. R. T. de Mello, DeMuth, D. M., Dennis, S., Densham, C., Denton, P., Deptuch, G. W., De Roeck, A., De Romeri, V., Detje, J. P., Devine, J., Dharmapalan, R., Dias, M., Díaz, J. S., Díaz, F., Di Capua, F., Di Domenico, A., Di Domizio, S., Di Falco, S., Di Giulio, L., Ding, P., Di Noto, L., Diociaiuti, E., Distefano, C., Diurba, R., Diwan, M., Djurcic, Z., Doering, D., Dolan, S., Dolek, F., Dolinski, M. J., Domenici, D., Domine, L., Donati, S., Donon, Y., Doran, S., Douglas, D., Doyle, T. A., Dragone, A., Drielsma, F., Duarte, L., Duchesneau, D., Duffy, K., Dugas, K., Dunne, P., Dutta, B., Duyang, H., Dvornikov, O., Dwyer, D. A., Dyshkant, A. S., Dytman, S., Eads, M., Earle, A., Edayath, S., Edmunds, D., Eisch, J., Englezos, P., Ereditato, A., Erjavec, T., Escobar, C. O., Evans, J. J., Ewart, E., Ezeribe, A. C., Fahey, K., Fajt, L., Falcone, A., Fani', M., Farnese, C., Farzan, Y., Fedoseev, D., Felix, J., Feng, Y., Fernandez-Martinez, E., Ferraro, F., Ferry, G., Fields, L., Filip, P., Filkins, A., Filthaut, F., Fine, R., Fiorillo, G., Fiorini, M., Fogarty, S., Foreman, W., Fowler, J., Franc, J., Francis, K., Franco, D., Franklin, J., Freeman, J., Fried, J., Friedland, A., Fuess, S., Furic, I. K., Furman, K., Furmanski, A. P., Gabrielli, A., Gago, A. M., Galizzi, F., Gallagher, H., Gallas, A., Gallice, N., Galymov, V., Gamberini, E., Gamble, T., Ganacim, F., Gandhi, R., Ganguly, S., Gao, F., Gao, S., Garcia-Gamez, D., García-Peris, M. Á., Gardim, F., Gardiner, S., Gastler, D., Gauch, A., Gauvreau, J., Gauzzi, P., Ge, G., Geffroy, N., Gelli, B., Gent, S., Gerlach, L., Ghorbani-Moghaddam, Z., Giammaria, P., Giammaria, T., Gibin, D., Gil-Botella, I., Gilligan, S., Gioiosa, A., Giovannella, S., Girerd, C., Giri, A. K., Giugliano, C., Giusti, V., Gnani, D., Gogota, O., Gollapinni, S., Gollwitzer, K., Gomes, R. A., Bermeo, L. V. Gomez, Fajardo, L. S. Gomez, Gonnella, F., Gonzalez-Diaz, D., Gonzalez-Lopez, M., Goodman, M. C., Goswami, S., Gotti, C., Goudeau, J., Goudzovski, E., Grace, C., Gramellini, E., Gran, R., Granados, E., Granger, P., Grant, C., Gratieri, D. R., Grauso, G., Green, P., Greenberg, S., Greer, J., Griffith, W. C., Groetschla, F. T., Grzelak, K., Gu, W., Guarino, V., Guarise, M., Guenette, R., Guerard, E., Guerzoni, M., Guffanti, D., Guglielmi, A., Guo, B., Guo, Y., Gupta, A., Gupta, V., Gurung, G., Gutierrez, D., Guzowski, P., Guzzo, M. M., Gwon, S., Haaf, K., Habig, A., Hadavand, H., Haenni, R., Hagaman, L., Hahn, A., Haiston, J., Hakenmueller, J., Hamernik, T., Hamilton, P., Hancock, J., Happacher, F., Harris, D. A., Hartnell, J., Hartnett, T., Harton, J., Hasegawa, T., Hasnip, C., Hatcher, R., Hayrapetyan, K., Hays, J., Hazen, E., He, M., Heavey, A., Heeger, K. M., Heise, J., Henry, S., Morquecho, M. A. Hernandez, Herner, K., Hewes, V., Higuera, A., Hilgenberg, C., Hillier, S. J., Himmel, A., Hinkle, E., Hirsch, L. R., Ho, J., Hoff, J., Holin, A., Holvey, T., Hoppe, E., Horton-Smith, G. A., Hostert, M., Houdy, T., Howard, B., Howell, R., Hristova, I., Hronek, M. S., Huang, J., Huang, R. G., Hulcher, Z., Ibrahim, M., Iles, G., Ilic, N., Iliescu, A. M., Illingworth, R., Ingratta, G., Ioannisian, A., Irwin, B., Isenhower, L., Oliveira, M. Ismerio, Itay, R., Jackson, C. M., Jain, V., James, E., Jang, W., Jargowsky, B., Jena, D., Ji, X., Jiang, C., Jiang, J., Jiang, L., Jipa, A., Joaquim, F. R., Johnson, W., Jones, B., Jones, R., Fernández, D. José, Jovancevic, N., Judah, M., Jung, C. K., Junk, T., Jwa, Y., Kabirnezhad, M., Kaboth, A. C., Kadenko, I., Kakorin, I., Kalitkina, A., Kalra, D., Kamiya, F., Kandemir, M., Kaplan, D. M., Karagiorgi, G., Karaman, G., Karcher, A., Karyotakis, Y., Kasai, S., Kasetti, S. P., Kashur, L., Katsioulas, I., Kauther, A., Kazaryan, N., Ke, L., Kearns, E., Keener, P. T., Kelly, K. J., Kemp, E., Kemularia, O., Kermaidic, Y., Ketchum, W., Kettell, S. H., Khabibullin, M., Khan, N., Khotjantsev, A., Khvedelidze, A., Kim, D., Kim, J., King, B., Kirby, B., Kirby, M., Kish, A., Klein, J., Kleykamp, J., Klustova, A., Kobilarcik, T., Koch, L., Koehler, K., Koerner, L. W., Koh, D. H., Kolupaeva, L., Korablev, D., Kordosky, M., Kosc, T., Kose, U., Kostelecký, V. A., Kothekar, K., Kotler, I., Kovalcuk, M., Kozhukalov, V., Krah, W., Kralik, R., Kramer, M., Kreczko, L., Krennrich, F., Kreslo, I., Kroupova, T., Kubota, S., Kubu, M., Kudenko, Y., Kudryavtsev, V. A., Kuhlmann, S., Kulagin, S., Kumar, J., Kumar, P., Kumaran, S., Kunze, P., Kunzmann, J., Kuravi, R., Kurita, N., Kuruppu, C., Kus, V., Kutter, T., Kvasnicka, J., Labree, T., Lackey, T., Lambert, A., Land, B. J., Lane, C. E., Lane, N., Lang, K., Langford, T., Langstaff, M., Lanni, F., Lantwin, O., Larkin, J., Lasorak, P., Last, D., Laudrain, A., Laundrie, A., Laurenti, G., Lavaut, E., Lawrence, A., Laycock, P., Lazanu, I., Lazzaroni, M., Le, T., Leardini, S., Learned, J., LeCompte, T., Lee, C., Legin, V., Miotto, G. Lehmann, Lehnert, R., de Oliveira, M. A. Leigui, Leitner, M., Silverio, D. Leon, Lepin, L. M., Li, J. -Y., Li, S. W., Li, Y., Liao, H., Lin, C. S., Lindebaum, D., Lineros, R. A., Ling, J., Lister, A., Littlejohn, B. R., Liu, H., Liu, J., Liu, Y., Lockwitz, S., Lokajicek, M., Lomidze, I., Long, K., Lopes, T. V., Lopez, J., de Rego, I. López, López-March, N., Lord, T., LoSecco, J. M., Louis, W. C., Sanchez, A. Lozano, Lu, X. -G., Luk, K. B., Lunday, B., Luo, X., Luppi, E., Maalmi, J., MacFarlane, D., Machado, A. A., Machado, P., Macias, C. T., Macier, J. R., MacMahon, M., Maddalena, A., Madera, A., Madigan, P., Magill, S., Magueur, C., Mahn, K., Maio, A., Major, A., Majumdar, K., Man, M., Mandujano, R. C., Maneira, J., Manly, S., Mann, A., Manolopoulos, K., Plata, M. Manrique, Corchado, S. Manthey, Manyam, V. N., Marchan, M., Marchionni, A., Marciano, W., Marfatia, D., Mariani, C., Maricic, J., Marinho, F., Marino, A. D., Markiewicz, T., Marques, F. Das Chagas, Marsden, D., Marshak, M., Marshall, C. M., Marshall, J., Martín-Albo, J., Martinez, N., Caicedo, D. A. Martinez, López, F. Martínez, Miravé, P. Martínez, Martynenko, S., Mascagna, V., Massari, C., Mastbaum, A., Matichard, F., Matsuno, S., Matteucci, G., Matthews, J., Mauger, C., Mauri, N., Mavrokoridis, K., Mawby, I., Mazza, R., Mazzacane, A., McAskill, T., McConkey, N., McFarland, K. S., McGrew, C., McNab, A., Meazza, L., Meddage, V. C. N., Mefodiev, A., Mehta, B., Mehta, P., Melas, P., Mena, O., Mendez, H., Mendez, P., Méndez, D. P., Menegolli, A., Meng, G., Messier, M. D., Metallo, S., Metcalf, J., Metcalf, W., Mewes, M., Meyer, H., Miao, T., Miccoli, A., Michna, G., Mikola, V., Milincic, R., Miller, G., Miller, W., Mineev, O., Minotti, A., Miralles, L., Miranda, O. G., Mironov, C., Miryala, S., Miscetti, S., Mishra, C. S., Mishra, S. R., Mislivec, A., Mitchell, M., Mladenov, D., Mocioiu, I., Mogan, A., Moggi, N., Mohanta, R., Mohayai, T. A., Mokhov, N., Molina, J., Bueno, L. Molina, Montagna, E., Montanari, A., Montanari, C., Montanari, D., Montanino, D., Zetina, L. M. Montaño, Mooney, M., Moor, A. F., Moore, Z., Moreno, D., Moreno-Palacios, O., Morescalchi, L., Moretti, D., Moretti, R., Morris, C., Mossey, C., Mote, M., Moura, C. A., Mouster, G., Mu, W., Mualem, L., Mueller, J., Muether, M., Muheim, F., Muir, A., Mulhearn, M., Munford, D., Munteanu, L. J., Muramatsu, H., Muraz, J., Murphy, M., Murphy, T., Muse, J., Mytilinaki, A., Nachtman, J., Nagai, Y., Nagu, S., Nalbandyan, M., Nandakumar, R., Naples, D., Narita, S., Nath, A., Navrer-Agasson, A., Nayak, N., Nebot-Guinot, M., Nehm, A., Nelson, J. K., Neogi, O., Nesbit, J., Nessi, M., Newbold, D., Newcomer, M., Nichol, R., Nicolas-Arnaldos, F., Nikolica, A., Nikolov, J., Niner, E., Nishimura, K., Norman, A., Norrick, A., Novella, P., Nowak, J. A., Oberling, M., Ochoa-Ricoux, J. P., Oh, S., Oh, S. B., Olivier, A., Olshevskiy, A., Olson, T., Onel, Y., Onishchuk, Y., Oranday, A., Osbiston, M., Vélez, J. A. Osorio, Ormachea, L. Otiniano, Ott, J., Pagani, L., Palacio, G., Palamara, O., Palestini, S., Paley, J. M., Pallavicini, M., Palomares, C., Pan, S., Panda, P., Vazquez, W. Panduro, Pantic, E., Paolone, V., Papadimitriou, V., Papaleo, R., Papanestis, A., Papoulias, D., Paramesvaran, S., Paris, A., Parke, S., Parozzi, E., Parsa, S., Parsa, Z., Parveen, S., Parvu, M., Pasciuto, D., Pascoli, S., Pasqualini, L., Pasternak, J., Patrick, C., Patrizii, L., Patterson, R. B., Patzak, T., Paudel, A., Paulucci, L., Pavlovic, Z., Pawloski, G., Payne, D., Pec, V., Pedreschi, E., Peeters, S. J. M., Pellico, W., Perez, A. Pena, Pennacchio, E., Penzo, A., Peres, O. L. G., Gonzalez, Y. F. Perez, Pérez-Molina, L., Pernas, C., Perry, J., Pershey, D., Pessina, G., Petrillo, G., Petta, C., Petti, R., Pia, V., Pickering, L., Pietropaolo, F., Pimentel, V. L., Pinaroli, G., Pinchault, J., Plows, K., Plunkett, R., Pollack, C., Pollman, T., Pompa, F., Pons, X., Poonthottathil, N., Poppi, F., Porter, J., Potekhin, M., Potenza, R., Pozimski, J., Pozzato, M., Prakash, S., Prakash, T., Pratt, C., Prest, M., Prosser, A., Psihas, F., Pugnere, D., Qian, X., Raaf, J. L., Radeka, V., Rademacker, J., Radics, B., Rafique, A., Raguzin, E., Rai, M., Rajagopalan, S., Rajaoalisoa, M., Rakhno, I., Rakotondravohitra, L., Ralte, L., Delgado, M. A. Ramirez, Ramson, B., Rappoldi, A., Raselli, G., Ratoff, P., Ray, R., Razafinime, H., Rea, E. M., Real, J. S., Rebel, B., Rechenmacher, R., Reggiani-Guzzo, M., Reichenbacher, J., Reitzner, S. D., Sfar, H. Rejeb, Renner, E., Renshaw, A., Rescia, S., Resnati, F., Restrepo, D., Reynolds, C., Ribas, M., Riboldi, S., Riccio, C., Riccobene, G., Ricol, J. S., Rigan, M., Rincón, E. V., Ritchie-Yates, A., Ritter, S., Rivera, D., Rivera, R., Robert, A., Rocha, J. L. Rocabado, Rochester, L., Roda, M., Rodrigues, P., Alonso, M. J. Rodriguez, Rondon, J. Rodriguez, Rosauro-Alcaraz, S., Rosier, P., Ross, D., Rossella, M., Rossi, M., Ross-Lonergan, M., Roy, N., Roy, P., Rubbia, C., Ruggeri, A., Ferreira, G. Ruiz, Russell, B., Ruterbories, D., Rybnikov, A., Saa-Hernandez, A., Saakyan, R., Sacerdoti, S., Sahoo, S. K., Sahu, N., Sakashita, K., Sala, P., Samios, N., Samoylov, O., Sanchez, M. C., Bravo, A. Sánchez, Sanchez-Lucas, P., Sandberg, V., Sanders, D. A., Sankey, D., Santoro, D., Saoulidou, N., Sapienza, P., Sarasty, C., Sarcevic, I., Sarra, I., Savage, G., Savinov, V., Scanavini, G., Scaramelli, A., Scarff, A., Schefke, T., Schellman, H., Schifano, S., Schlabach, P., Schmitz, D., Schneider, A. W., Scholberg, K., Schukraft, A., Schuld, B., Segreto, E., Selyunin, A., Senise, C. R., Sensenig, J., Shaevitz, M. H., Shanahan, P., Sharma, P., Kumar, R., Shaw, K., Shaw, T., Shchablo, K., Shepherd-Themistocleous, C., Sheshukov, A., Shi, W., Shin, S., Shivakoti, S., Shoemaker, I., Shooltz, D., Shrock, R., Siddi, B., Silber, J., Simard, L., Sinclair, J., Sinev, G., Singh, Jaydip, Singh, J., Singh, L., Singh, P., Singh, V., Chauhan, S. Singh, Sipos, R., Sironneau, C., Sirri, G., Siyeon, K., Skarpaas, K., Smedley, J., Smith, E., Smith, J., Smith, P., Smolik, J., Smy, M., Snape, M., Snider, E. L., Snopok, P., Snowden-Ifft, D., Nunes, M. Soares, Sobel, H., Soderberg, M., Sokolov, S., Salinas, C. J. Solano, Söldner-Rembold, S., Soleti, S. R., Solomey, N., Solovov, V., Sondheim, W. E., Sorel, M., Sotnikov, A., Soto-Oton, J., Sousa, A., Soustruznik, K., Spinella, F., Spitz, J., Spooner, N. J. C., Spurgeon, K., Stalder, D., Stancari, M., Stanco, L., Steenis, J., Stein, R., Steiner, H. M., Lisbôa, A. F. Steklain, Stepanova, A., Stewart, J., Stillwell, B., Stock, J., Stocker, F., Stokes, T., Strait, M., Strauss, T., Strigari, L., Stuart, A., Suarez, J. G., Subash, J., Surdo, A., Suter, L., Sutera, C. M., Sutton, K., Suvorov, Y., Svoboda, R., Swain, S. K., Szczerbinska, B., Szelc, A. M., Sztuc, A., Taffara, A., Talukdar, N., Tamara, J., Tanaka, H. A., Tang, S., Taniuchi, N., Casanova, A. M. Tapia, Oregui, B. Tapia, Tapper, A., Tariq, S., Tarpara, E., Tatar, E., Tayloe, R., Tedeschi, D., Teklu, A. M., Vidal, J. Tena, Tennessen, P., Tenti, M., Terao, K., Terranova, F., Testera, G., Thakore, T., Thea, A., Thiebault, A., Thompson, A., Thorn, C., Timm, S. C., Tiras, E., Tishchenko, V., Todorović, N., Tomassetti, L., Tonazzo, A., Torbunov, D., Torti, M., Tortola, M., Tortorici, F., Tosi, N., Totani, D., Toups, M., Touramanis, C., Travaglini, R., Trevor, J., Triller, E., Trilov, S., Truncali, D., Trzaska, W. H., Tsai, Y., Tsai, Y. -T., Tsamalaidze, Z., Tsang, K. V., Tsverava, N., Tu, S. Z., Tufanli, S., Turner, J., Tuzi, M., Tyler, J., Tyley, E., Tzanov, M., Uchida, M. A., González, J. Ureña, Urheim, J., Usher, T., Utaegbulam, H., Uzunyan, S., Vagins, M. R., Vahle, P., Valder, S., Valdiviesso, G. A., Valencia, E., Valentim, R., Vallari, Z., Vallazza, E., Valle, J. W. F., Van Berg, R., Van de Water, R. G., Forero, D. V., Van Nuland-Troost, M., Varanini, F., Oliva, D. Vargas, Varner, G., Vasina, S., Vaughan, N., Vaziri, K., Vega, J., Ventura, S., Verdugo, A., Vergani, S., Verzocchi, M., Vetter, K., Vicenzi, M., de Souza, H. Vieira, Vignoli, C., Vilela, C., Villa, E., Viren, B., Vizcaya-Hernandez, A., Vrba, T., Vuong, Q., Waldron, A. V., Wallbank, M., Walsh, J., Walton, T., Wang, H., Wang, J., Wang, L., Wang, M. H. L. S., Wang, X., Wang, Y., Warburton, K., Warner, D., Warsame, L., Wascko, M. O., Waters, D., Watson, A., Wawrowska, K., Weber, A., Weber, M., Wei, H., Weinstein, A., Wenzel, H., Westerdale, S., Wetstein, M., Whalen, K., Whilhelmi, J., White, A., Whitehead, L. H., Whittington, D., Wilking, M. J., Wilkinson, A., Wilkinson, C., Wilson, F., Wilson, R. J., Winter, P., Wisniewski, W., Wolcott, J., Wolfs, J., Wongjirad, T., Wood, A., Wood, K., Worcester, E., Worcester, M., Wospakrik, M., Wresilo, K., Wret, C., Wu, S., Wu, W., Wurm, M., Wyenberg, J., Xiao, Y., Xiotidis, I., Yaeggy, B., Yahlali, N., Yandel, E., Yang, K., Yang, T., Yankelevich, A., Yershov, N., Yonehara, K., Young, T., Yu, B., Yu, H., Yu, J., Yu, Y., Yuan, W., Zaki, R., Zalesak, J., Zambelli, L., Zamorano, B., Zani, A., Zapata, O., Zazueta, L., Zeller, G. P., Zennamo, J., Zeug, K., Zhang, C., Zhang, S., Zhao, M., Zhivun, E., Zimmerman, E. D., Zucchelli, S., Zuklin, J., Zutshi, V., and Zwaska, R.

Subjects
High Energy Physics - Experiment, Physics - Instrumentation and Detectors
Abstract

DUNE is an international experiment dedicated to addressing some of the questions at the forefront of particle physics and astrophysics, including the mystifying preponderance of matter over antimatter in the early universe. The dual-site experiment will employ an intense neutrino beam focused on a near and a far detector as it aims to determine the neutrino mass hierarchy and to make high-precision measurements of the PMNS matrix parameters, including the CP-violating phase. It will also stand ready to observe supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. The DUNE far detector implements liquid argon time-projection chamber (LArTPC) technology, and combines the many tens-of-kiloton fiducial mass necessary for rare event searches with the sub-centimeter spatial resolution required to image those events with high precision. The addition of a photon detection system enhances physics capabilities for all DUNE physics drivers and opens prospects for further physics explorations. Given its size, the far detector will be implemented as a set of modules, with LArTPC designs that differ from one another as newer technologies arise. In the vertical drift LArTPC design, a horizontal cathode bisects the detector, creating two stacked drift volumes in which ionization charges drift towards anodes at either the top or bottom. The anodes are composed of perforated PCB layers with conductive strips, enabling reconstruction in 3D. Light-trap-style photon detection modules are placed both on the cryostat's side walls and on the central cathode where they are optically powered. This Technical Design Report describes in detail the technical implementations of each subsystem of this LArTPC that, together with the other far detector modules and the near detector, will enable DUNE to achieve its physics goals., Comment: 425 pages; 281 figures Central editing team: A. Heavey, S. Kettell, A. Marchionni, S. Palestini, S. Rajogopalan, R. J. Wilson

Published
2023

70. Assessment of meniscal extrusion with ultrasonography: a systematic review and meta-analysis

Author

Khalis Boksh, Duncan E. T. Shepherd, Daniel M. Espino, Jenna Shepherd, Arijit Ghosh, Randeep Aujla, and Tarek Boutefnouchet

Subjects
Meniscal extrusion, Ultrasonography, Osteoarthritis, Meniscus pathology, Correlation, Orthopedic surgery, RD701-811
Abstract

Abstract Background Magnetic resonance imaging (MRI) is the imaging of choice for meniscal extrusion (ME). However, they may underappreciate the load-dependent changes of the meniscus. There is growing evidence that weight-bearing ultrasound (WB US) is more suitable, particularly in revealing occult extrusion. We therefore perform a systematic review and meta-analysis on the validity and reliability of US in diagnosing extrusion. Furthermore, we explored whether it detects differences in extrusion between loaded and unloaded positions and those with pathological (osteoarthritis and meniscal injury) and healthy knees. Methods The Cochrane Controlled Register of Trials, PubMed, Medline, and Embase were used to perform a systematic review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria. Data pertaining to intra- and interrater reliability of US in measuring meniscal extrusion (ME), its correlation with magnetic resonance imaging (MRI), and head-to-head comparison of potential factors to influence ME were included [loading versus unloading position; osteoarthritis (OA) or pathological menisci (PM) versus healthy knees; mild versus moderate–severe knee OA]. Pooled data were analyzed by random or fixed-effects models. Results A total of 31 studies were included. Intraclass correlation coefficients (ICC) for intra- and interrater reliability were minimum 0.94 and 0.91, respectively. The correlation between US and MRI was (r = 0.76). US detected ME to be greater in the loaded position in all knees (healthy, p

Published
2024
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71. Navigate: an open-source platform for smart light-sheet microscopy

Author

Marin, Zach, Wang, Xiaoding, Collison, Dax W., McFadden, Conor, Lin, Jinlong, Borges, Hazel M., Chen, Bingying, Mehra, Dushyant, Shen, Qionghua, Gałecki, Seweryn, Daetwyler, Stephan, Sheppard, Steven J., Thien, Phu, Porter, Baylee A., Conzen, Suzanne D., Shepherd, Douglas P., Fiolka, Reto, and Dean, Kevin M.

Published
2024
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77. Exploring Occupational Therapy Student and Entry-Level Practitioner Perceptions of Mental Health Accommodations

Author

Allison J. Naber, Ranelle Nissen, Whitney Lucas Molitor, Susan E. Puumala, and Jewel Goodman Shepherd

Abstract

Mental health concerns are prevalent among occupational therapy graduate students and entry-level practitioners entering the workforce. Prior research has highlighted that the rise in mental health concerns and the high-achieving nature of occupational therapy students impacts their success in the classroom and the clinic. While formal and informal mental health accommodations are beneficial, obtaining and implementing such accommodations has been cited as a challenging process plagued with negative stigma. This study aimed to understand the perceived effectiveness of common academic and work-related mental health accommodations for meeting the role demands that occupational therapy students and practitioners encounter in the classroom, during fieldwork and capstone, and in entry-level practice. Data were gathered from 218 occupational therapy students and entry-level practitioners who completed an electronic survey, including checklists and Likert scale items. Results include the prevalence of mental health concerns, the use of formal and informal mental health accommodations, and the perceived effectiveness of mental health accommodations in meeting the role demands of occupational therapy students and entry-level practitioners. Participants reported that the commonly prescribed mental health accommodations effectively met role demands in academic and work settings. Qualitative responses to the survey provided a deeper understanding of these perceptions and the barriers students encountered when attaining or implementing such accommodations in the classroom and clinical settings. Implications for occupational therapy education address the prevalence of mental health concerns and the barriers occupational therapy students face when attaining and implementing mental health accommodations.

Published
2023

78. Developing College Student Intercultural Competence in a Childhood Diversity Course: A Pilot Study

Author

Diana Coyl-Shepherd

Abstract

The primary aim of this study was to investigate pedagogical mechanisms that promote student understanding of diversity and intersectionality in national and global childhood experiences in order to foster openness, acceptance of diversity, and civic engagement. In this mixed-methods study, participants included 127 undergraduate students in a child development diversity (CDD) course and a control group of 63 undergraduate students in a research methods psychology (RMP) course. Students in both groups self-rated their knowledge of 18 diversity topics, their Openness to diversity, Acceptance of cultural differences, Awareness of racism and sexism, and Plans to advocate for others (OAAP variables). Quantitative results showed significant increases in CDD course groups' knowledge of all topics from beginning to semester-end and greater knowledge compared with the RMP course control group. For CDD course students, diversity knowledge was positively and more strongly correlated with their OAAP scores. Qualitative written responses from CDD course students illustrate their perceptions of the importance of intercultural awareness and knowledge of childhood intersectionality and diversity, the effectiveness of specific content delivery methods, and how they relate to their advocacy and volunteer plans.

Published
2023

79. Development and Validation of the Sense of Online Community Scale

Author

Craig E. Shepherd, Doris U. Bolliger, and Courtney McKim

Abstract

This study focused on the development and validation of the Sense of Online Community Scale (SOCS), which includes 28 Likert-type scale items across six subscales: (1) program community; (2) program academic activities; (3) program social activities; (4) institutional academic activities; (5) institutional social activities; and (6) affiliation. The validation process included an implementation with 293 learners enrolled in online programs at a higher education institution in the eastern United States. The model was evaluated with and without outliers, and results show that the model aligned well with the SOCS. The means of all items except one exceeded 3.5 on a 5.0 scale, ranging from 1 (strongly disagree) to 5 (strongly agree). Time in an online program was not a statistically significant predictor of the validation model, though most of our participants were in the first or second year of their degree programs. Findings demonstrate that the SOCS is a reliable and valid instrument that other researchers may use to investigate community in online environments on both the program and the institutional level.

Published
2023

91. Impact of SARS-CoV-2 Infection on Long-Term Depression Symptoms among Veterans

Author

Chen, Jason I., Bui, David, Iwashyna, Theodore J., Shahoumian, Troy A., Hickok, Alex, Shepherd-Banigan, Megan, Hawkins, Eric J., Naylor, Jennifer, Govier, Diana J., Osborne, Thomas F., Smith, Valerie A., Bowling, C. Barrett, Boyko, Edward J., Ioannou, George N., Maciejewski, Matthew L., O’Hare, Ann M., Viglianti, Elizabeth M., Bohnert, Amy S.-B., and Hynes, Denise M.

Published
2024
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95. Sampling the reciprocal Coulomb potential in finite and anisotropic cells

Author

Schäfer, Tobias, Van Benschoten, William Z., Shepherd, James J., and Grüneis, Andreas

Subjects
Physics - Computational Physics, Physics - Chemical Physics
Abstract

We present a robust strategy to numerically sample the Coulomb potential in reciprocal space for periodic Born-von Karman cells of general shape. Our approach tackles two common issues of plane-wave based implementations of Coulomb integrals under periodic boundary conditions, the treatment of the singularity at the Brillouin-zone center, as well as quadrature errors, which can cause severe convergence problems in anisotropic cells, necessary for the calculation of low-dimensional systems. We apply our strategy to the Hartree-Fock (HF) and coupled cluster (CC) theory and discuss the consequences of different sampling strategies on the different theories. We show that sampling the Coulomb potential via the widely used probe-charge Ewald method is unsuitable for CC calculations in anisotropic cells. To demonstrate the applicability of our developed approach, we study two representative, low-dimensional use cases: the infinite carbon chain, for which we report the first periodic CCSD(T) potential energy surface, as well as a surface slab of lithium hydride, for which we demonstrate the impact of different sampling strategies for calculating surface energies. We find that our Coulomb sampling strategy serves as a vital solution, addressing the critical need for improved accuracy in plane-wave based CC calculations for low-dimensional systems., Comment: 7 pages, 3 figures

Published
2023
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96. Slip Detection and Surface Prediction Through Bio-Inspired Tactile Feedback

Author

Shepherd, Dexter R., Husbands, Phil, Philippides, Andy, and Johnson, Chris

Subjects
Computer Science - Robotics
Abstract

High resolution tactile sensing has great potential in autonomous mobile robotics, particularly for legged robots. One particular area where it has significant promise is the traversal of challenging, varied terrain. Depending on whether an environment is slippery, soft, hard or dry, a robot must adapt its method of locomotion accordingly. Currently many multi-legged robots, such as Boston Dynamic's Spot robot, have preset gaits for different surface types, but struggle over terrains where the surface type changes frequently. Being able to automatically detect changes within an environment would allow a robot to autonomously adjust its method of locomotion to better suit conditions, without requiring a human user to manually set the change in surface type. In this paper we report on the first detailed investigation of the properties of a particular bio-inspired tactile sensor, the TacTip, to test its suitability for this kind of automatic detection of surface conditions. We explored different processing techniques and a regression model, using a custom made rig for data collection to determine how a robot could sense directional and general force on the sensor in a variety of conditions. This allowed us to successfully demonstrate how the sensor can be used to distinguish between soft, hard, dry and (wet) slippery surfaces. We further explored a neural model to classify specific surface textures. Pin movement (the movement of optical markers within the sensor) was key to sensing this information, and all models relied on some form of temporal information. Our final trained models could successfully determine the direction the sensor is heading in, the amount of force acting on it, and determine differences in the surface texture such as Lego vs smooth hard surface, or concrete vs smooth hard surface., Comment: 6 pages + references, under review for ICRA 2024

Published
2023

97. A smoking gun signature of the 3HDM

Author

Dey, A., Keus, V., Moretti, S., and Shepherd-Themistocleous, C.

Subjects
High Energy Physics - Phenomenology
Abstract

We analyse new signals of a 3-Higgs Doublet Model (3HDM) at the Large Hadron Collider (LHC) where only one doublet acquires a Vacuum Expectation Value (VEV), preserving a $Z_2$ parity. The other two doublets are \textit{inert} and do not develop a VEV, leading to a \textit{dark scalar sector} controlled by $Z_2$, with the lightest CP-even dark scalar $H_1$ being the Dark Matter (DM) candidate. This leads to the loop induced decay of the next-to-lightest scalar, $H_2 \to H_1 \ell \bar \ell $ ($\ell =e,\mu$), mediated by both dark CP-odd neutral and charged scalars. This is a smoking-gun signal of the 3HDM since it is not allowed in the 2-Higgs Doublet Model (2HDM) with one inert doublet and is expected to be important when $H_2$ and $H_1$ are close in mass. In practice, this signature can be observed in the cascade decay of the SM-like Higgs boson, $h\to H_1 H_2\to H_1 H_1 \ell \bar \ell$ into two DM particles and di-leptons or $h\to H_2 H_2\to H_1 H_1 \ell \bar \ell \ell \bar \ell$ into two DM particles and four-leptons, where $h$ is produced from gluon-gluon Fusion. In order to test the feasibility of these channels at the LHC, we devise some benchmarks, compliant with collider, DM and cosmological data, for which the interplay between these production and decay modes is discussed. In particular, we show that the resulting detector signatures, $\Et \ell \bar \ell$ or $\Et \ell \bar \ell \ell \bar \ell$, with the invariant mass of $ \ell \bar \ell$ pairs much smaller than $m_Z$, can potentially be extracted already from Run 3 data and at the High-Luminosity phase of the LHC., Comment: 27 pages, 13 figures. arXiv admin note: text overlap with arXiv:1712.09598

Published
2023

98. Searching for $H \to hh \to b\bar b\tau\tau$ in the 2HDM Type-I at the LHC

Author

Arhrib, A., Moretti, S., Semlali, S., Shepherd-Themistocleous, C. H., Wang, Y., and Yan, Q. S.

Subjects
High Energy Physics - Phenomenology
Abstract

Unlike other realisations of the 2-Higgs Doublet Model (2HDM), the so-called Type-I allows for a very light Higgs boson spectrum. Specifically, herein, the heaviest of the two CP-even neutral Higgs states, $H$, can be the one discovered at the Large Hadron Collider (LHC) in 2012, with a mass of $\approx 125$ GeV and couplings consistent with those predicted by the Standard Model (SM). In such a condition of the model, referred to as `inverted mass hierarchy', the decay of the SM-like Higgs state into pairs of the lightest CP-even neutral Higgs boson, $h$, is possible, for masses of the latter ranging from $M_H/2\approx 65$ GeV down to 15 GeV or so, all compatible with experimental constraints. In this paper, we investigate the scope of the LHC in accessing the process $gg\to H \to hh\to b\bar b\tau\tau$ by performing a Monte Carlo (MC) analysis aimed at extracting this signal from the SM backgrounds, in presence of a dedicated trigger choice and kinematic selection. We prove that some sensitivity to such a channel exists already at Run 3 of the LHC while the High-Luminosity LHC (HL-LHC) will be able to either confirm or disprove this theoretical scenario over sizable regions of its parameter space.

Published
2023

99. How to Model Brushless Electric Motors for the Design of Lightweight Robotic Systems

Author

Lee, Ung Hee, Shepherd, Tor, Kim, Sangbae, De, Avik, Su, Hao, Gregg, Robert, Mooney, Luke, and Rouse, Elliott

Subjects
Computer Science - Robotics
Abstract

A key step in the development of lightweight, high performance robotic systems is the modeling and selection of permanent magnet brushless direct current (BLDC) electric motors. Typical modeling analyses are completed a priori, and provide insight for properly sizing a motor for an application, specifying the required operating voltage and current, as well as assessing the thermal response and other design attributes (e.g.transmission ratio). However, to perform these modeling analyses, proper information about the motor's characteristics are needed, which are often obtained from manufacturer datasheets. Through our own experience and communications with manufacturers, we have noticed a lack of clarity and standardization in modeling BLDC motors, compounded by vague or inconsistent terminology used in motor datasheets. The purpose of this tutorial is to concisely describe the governing equations for BLDC motor analyses used in the design process, as well as highlight potential errors that can arise from incorrect usage. We present a power-invariant conversion from phase and line-to-line reference frames to a familiar q-axis DC motor representation, which provides a ``brushed'' analogue of a three phase BLDC motor that is convenient for analysis and design. We highlight potential errors including incorrect calculations of winding resistive heat loss, improper estimation of motor torque via the motor's torque constant, and incorrect estimation of the required bus voltage or resulting angular velocity limitations. A unified and condensed set of governing equations is available for designers in the Appendix. The intent of this work is to provide a consolidated mathematical foundation for modeling BLDC motors that addresses existing confusion and fosters high performance designs of future robotic systems.

Published
2023

100. Fourier synthesis optical diffraction tomography for kilohertz rate volumetric imaging

Author

Brown, Peter T., Jabbarzadeh, Nikta, Pintuff, Aidan, Meneses, Luis, Monakhova, Ekaterina, Kruithoff, Rory, Wadhwa, Navish, Galati, Domenico F., and Shepherd, Douglas P.

Subjects
Physics - Optics, Physics - Biological Physics
Abstract

Many biological and soft matter processes occur at high speeds in complex 3D environments, and developing imaging techniques capable of elucidating their dynamics is an outstanding experimental challenge. Here, we introduce Fourier Synthesis Optical Diffraction Tomography (FS-ODT), a novel approach for high-speed quantitative phase imaging capable of recording the 3D refractive index at kilohertz rates. FS-ODT introduces new pattern generation and inverse computational strategies that multiplex tens of illumination angles in a single tomogram, dramatically increasing the volumetric imaging rate. We validate FS-ODT performance by imaging samples of known composition and accurately recovering the refractive index for increasing pattern complexity. We further demonstrate the capabilities of FS-ODT for probing complex systems by studying the hindered diffusion of colloids in solution and the motility of single-cellular bacterial swimmers. We believe that FS-ODT is a promising approach for unlocking challenging imaging regimes in biophysics and soft matter that have been little explored, including understanding the physical interactions of colloids and microswimmers with their viscous 3D environment and the interplay between these stimuli and the molecular response of biological systems.

Published
2023

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