Author: "Lin, Chien" - Searchworks@Jio Institute Digital Library Search Results

Author: Sie, Ming-Fong, Chang, Yen-Jui, Lin, Chien-Lung, Chang, Ching-Ray, and Liao, Shih-Wei
Subjects: Quantum Physics, Computer Science - Cryptography and Security
Abstract: Over 900 million Bitcoin transactions have been recorded, posing considerable challenges for machine learning in terms of computation time and maintaining prediction accuracy. We propose an innovative approach using quantum-inspired algorithms implemented with Simulated Annealing and Quantum Annealing to address the challenge of local minima in solution spaces. This method efficiently identifies key features linked to mixer addresses, significantly reducing model training time. By categorizing Bitcoin addresses into six classes: exchanges, faucets, gambling, marketplaces, mixers, and mining pools, and applying supervised learning methods, our results demonstrate that feature selection with SA reduced training time by 30.3% compared to using all features in a random forest model while maintaining a 91% F1-score for mixer addresses. This highlights the potential of quantum-inspired algorithms to swiftly and accurately identify high-risk Bitcoin addresses based on transaction features., Comment: 19 pages
Published: 2024

22. From an attention economy to an ecology of attending. A manifesto

Author: Bombaerts, Gunter, Hannes, Tom, Adam, Martin, Aloisi, Alessandra, Anderson, Joel, Berger, Lawrence, Bettera, Stefano Davide, Campo, Enrico, Candiotto, Laura, Panizza, Silvia Caprioglio, Citton, Yves, DâAngelo, Diego, Dennis, Matthew, Depraz, Nathalie, Doran, Peter, Drechsler, Wolfgang, Duane, Bill, Edelglass, William, Eisenberger, Iris, McGuire, Beverley Foulks, Fredriksson, Antony, Gill, Karamjit S., Hershock, Peter D., Hongladarom, Soraj, Jacobs, Beth, Karsai, Gábor, Lennerfors, Thomas, Lim, Jeanne, Lin, Chien-Te, Losoncz, Mark, Loy, David, Marin, Lavinia, Marosán, Bence Péter, Mascarello, Chiara, McMahan, David, Park, Jin Y., Petek, Nina, Puzio, Anna, Schaubroek, Katrien, Schlieter, Jens, Schroeder, Brian, Shakya, Shobhit, Shi, Juewei, Solomonova, Elizaveta, Tormen, Francesco, Uttam, Jitendra, Van Vugt, Marieke, Vörös, Sebastjan, Wehrle, Maren, Wellner, Galit, Wirth, Jason M., Witkowski, Olaf, Wongkitrungrueng, Apiradee, Wright, Dale S., and Zheng, Yutong
Subjects: Computer Science - Computers and Society
Abstract: As the signatories of this manifesto, we denounce the attention economy as inhumane and a threat to our sociopolitical and ecological well-being. We endorse policymakers' efforts to address the negative consequences of the attention economy's technology, but add that these approaches are often limited in their criticism of the systemic context of human attention. Starting from Buddhist philosophy, we advocate a broader approach: an ecology of attending, that centers on conceptualizing, designing, and using attention (1) in an embedded way and (2) focused on the alleviating of suffering. With 'embedded' we mean that attention is not a neutral, isolated mechanism but a meaning-engendering part of an 'ecology' of bodily, sociotechnical and moral frameworks. With 'focused on the alleviation of suffering' we explicitly move away from the (often implicit) conception of attention as a tool for gratifying desires., Comment: 21 pages, 1 figure
Published: 2024

23. NanoFlow: Towards Optimal Large Language Model Serving Throughput

Author: Zhu, Kan, Zhao, Yilong, Zhao, Liangyu, Zuo, Gefei, Gu, Yile, Xie, Dedong, Gao, Yufei, Xu, Qinyu, Tang, Tian, Ye, Zihao, Kamahori, Keisuke, Lin, Chien-Yu, Wang, Stephanie, Krishnamurthy, Arvind, and Kasikci, Baris
Subjects: Computer Science - Distributed, Parallel, and Cluster Computing
Abstract: The increasing usage of Large Language Models (LLMs) has resulted in a surging demand for planet-scale serving systems, where tens of thousands of GPUs continuously serve hundreds of millions of users. Consequently, throughput (under reasonable latency constraints) has emerged as a key metric that determines serving systems' performance. To boost throughput, various methods of inter-device parallelism (e.g., data, tensor, pipeline) have been explored. However, existing methods do not consider overlapping the utilization of different resources within a single device, leading to underutilization and sub-optimal performance. We propose NanoFlow, a novel serving framework that exploits intra-device parallelism, which overlaps the usage of resources including compute, memory, and network within a single device through operation co-scheduling. To exploit intra-device parallelism, NanoFlow introduces two key innovations: First, NanoFlow splits requests into nano-batches at the granularity of operations, which breaks the dependency of sequential operations in LLM inference and enables overlapping; then, to get benefit from overlapping, NanoFlow uses an operation-level pipeline with execution unit scheduling, which partitions the device's functional units and simultaneously executes different operations in each unit. NanoFlow automates the pipeline setup using a parameter search algorithm, which enables easily porting NanoFlow to different models. We implement NanoFlow on NVIDIA GPUs and evaluate end-to-end serving throughput on several popular models such as LLaMA-2-70B, Mixtral 8x7B, LLaMA-3-8B, etc.. With practical workloads, NanoFlow provides 1.91x throughput boost compared to state-of-the-art serving systems achieving 59% to 72% of optimal throughput across ported models.
Published: 2024

24. Palu: Compressing KV-Cache with Low-Rank Projection

Author: Chang, Chi-Chih, Lin, Wei-Cheng, Lin, Chien-Yu, Chen, Chong-Yan, Hu, Yu-Fang, Wang, Pei-Shuo, Huang, Ning-Chi, Ceze, Luis, Abdelfattah, Mohamed S., and Wu, Kai-Chiang
Subjects: Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract: Post-training KV-Cache compression methods typically either sample a subset of effectual tokens or quantize the data into lower numerical bit width. However, these methods cannot exploit redundancy in the hidden dimension of the KV tensors. This paper presents a hidden dimension compression approach called Palu, a KV-Cache compression framework that utilizes low-rank projection to reduce inference-time LLM memory usage. Palu decomposes the linear layers into low-rank matrices, caches compressed intermediate states, and reconstructs the full keys and values on the fly. To improve accuracy, compression rate, and efficiency, Palu further encompasses (1) a medium-grained low-rank decomposition scheme, (2) an efficient rank search algorithm, (3) low-rank-aware quantization compatibility enhancements, and (4) optimized GPU kernels with operators fusion. Extensive experiments with popular LLMs show that Palu compresses KV-Cache by 50% while maintaining strong accuracy and delivering up to 1.89x on the RoPE-based attention module. When combined with quantization, Palu's inherent quantization-friendly design yields small to negligible extra accuracy degradation while saving additional memory than quantization-only methods and achieving up to 2.91x speedup for the RoPE-based attention. Moreover, it maintains comparable or even better accuracy (up to 1.19 lower perplexity) compared to quantization-only methods. These results demonstrate Palu's superior capability to effectively address the efficiency and memory challenges of LLM inference posed by KV-Cache. Our code is publicly available at: https://github.com/shadowpa0327/Palu
Published: 2024

25. SE3ET: SE(3)-Equivariant Transformer for Low-Overlap Point Cloud Registration

Author: Lin, Chien Erh, Zhu, Minghan, and Ghaffari, Maani
Subjects: Computer Science - Robotics
Abstract: Partial point cloud registration is a challenging problem in robotics, especially when the robot undergoes a large transformation, causing a significant initial pose error and a low overlap between measurements. This work proposes exploiting equivariant learning from 3D point clouds to improve registration robustness. We propose SE3ET, an SE(3)-equivariant registration framework that employs equivariant point convolution and equivariant transformer designs to learn expressive and robust geometric features. We tested the proposed registration method on indoor and outdoor benchmarks where the point clouds are under arbitrary transformations and low overlapping ratios. We also provide generalization tests and run-time performance.
Published: 2024

26. Swift-BAT GUANO follow-up of gravitational-wave triggers in the third LIGO-Virgo-KAGRA observing run

Author: Raman, Gayathri, Ronchini, Samuele, Delaunay, James, Tohuvavohu, Aaron, Kennea, Jamie A., Parsotan, Tyler, Ambrosi, Elena, Bernardini, Maria Grazia, Campana, Sergio, Cusumano, Giancarlo, D'Ai, Antonino, D'Avanzo, Paolo, D'Elia, Valerio, De Pasquale, Massimiliano, Dichiara, Simone, Evans, Phil, Hartmann, Dieter, Kuin, Paul, Melandri, Andrea, O'Brien, Paul, Osborne, Julian P., Page, Kim, Palmer, David M., Sbarufatti, Boris, Tagliaferri, Gianpiero, Troja, Eleonora, Abac, A. G., Abbott, R., Abe, H., Abouelfettouh, I., Acernese, F., Ackley, K., Adamcewicz, C., Adhicary, S., Adhikari, N., Adhikari, R. X., Adkins, V. K., Adya, V. B., Affeldt, C., Agarwal, D., Agathos, M., Aguiar, O. D., Aguilar, I., Aiello, L., Ain, A., Akutsu, T., Albanesi, S., Alfaidi, R. A., Al-Jodah, A., Alléné, C., Allocca, A., Al-Shammari, S., Altin, P. A., Alvarez-Lopez, S., Amato, A., Amez-Droz, L., Amorosi, A., Amra, C., Anand, S., Ananyeva, A., Anderson, S. B., Anderson, W. G., Andia, M., Ando, M., Andrade, T., Andres, N., Andrés-Carcasona, M., Andrić, T., Anglin, J., Ansoldi, S., Antelis, J. M., Antier, S., Aoumi, M., Appavuravther, E. Z., Appert, S., Apple, S. K., Arai, K., Araya, A., Araya, M. C., Areeda, J. S., Aritomi, N., Armato, F., Arnaud, N., Arogeti, M., Aronson, S. M., Ashton, G., Aso, Y., Assiduo, M., Melo, S. Assis de Souza, Aston, S. M., Astone, P., Aubin, F., AultONeal, K., Avallone, G., Babak, S., Badaracco, F., Badger, C., Bae, S., Bagnasco, S., Bagui, E., Bai, Y., Baier, J. G., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. W., Banagiri, S., Banerjee, B., Bankar, D., Baral, P., Barayoga, J. C., Barish, B. C., Barker, D., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Barthelmy, S. D., Barton, M. A., Bartos, I., Basak, S., Basalaev, A., Bassiri, R., Basti, A., Bawaj, M., Baxi, P., Bayley, J. C., Baylor, A. C., Bazzan, M., Bécsy, B., Bedakihale, V. M., Beirnaert, F., Bejger, M., Belardinelli, D., Bell, A. S., Benedetto, V., Beniwal, D., Benoit, W., Bentley, J. D., Yaala, M. Ben, Bera, S., Berbel, M., Bergamin, F., Berger, B. K., Bernuzzi, S., Beroiz, M., Berry, C. P. L., Bersanetti, D., Bertolini, A., Betzwieser, J., Beveridge, D., Bevins, N., Bhandare, R., Bhardwaj, U., Bhatt, R., Bhattacharjee, D., Bhaumik, S., Bhowmick, S., Bianchi, A., Bilenko, I. A., Billingsley, G., Binetti, A., Bini, S., Birnholtz, O., Biscoveanu, S., Bisht, A., Bitossi, M., Bizouard, M. -A., Blackburn, J. K., Blair, C. D., Blair, D. G., Bobba, F., Bode, N., Bogaert, G., Boileau, G., Boldrini, M., Bolingbroke, G. N., Bolliand, A., Bonavena, L. D., Bondarescu, R., Bondu, F., Bonilla, E., Bonilla, M. S., Bonino, A., Bonnand, R., Booker, P., Borchers, A., Boschi, V., Bose, S., Bossilkov, V., Boudart, V., Boumerdassi, A., Bozzi, A., Bradaschia, C., Brady, P. R., Braglia, M., Branch, A., Branchesi, M., Breschi, M., Briant, T., Brillet, A., Brinkmann, M., Brockill, P., Brockmueller, E., Brooks, A. F., Brown, D. D., Brozzetti, M. L., Brunett, S., Bruno, G., Bruntz, R., Bryant, J., Bucci, F., Buchanan, J., Bulashenko, O., Bulik, T., Bulten, H. J., Buonanno, A., Burtnyk, K., Buscicchio, R., Buskulic, D., Buy, C., Byer, R. L., Davies, G. S. Cabourn, Cabras, G., Cabrita, R., Cadonati, L., Cagnoli, G., Cahillane, C., Bustillo, J. Calderón, Callaghan, J. D., Callister, T. A., Calloni, E., Camp, J. B., Canepa, M., Santoro, G. Caneva, Cannavacciuolo, M., Cannon, K. C., Cao, H., Cao, Z., Capistran, L. A., Capocasa, E., Capote, E., Carapella, G., Carbognani, F., Carlassara, M., Carlin, J. B., Carpinelli, M., Carrillo, G., Carter, J. J., Carullo, G., Diaz, J. Casanueva, Casentini, C., Castaldi, G., Castro-Lucas, S. Y., Caudill, S., Cavaglià, M., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, W., Chakraborty, P., Subrahmanya, S. Chalathadka, Chan, C., Chan, J. C. L., Chan, K. H. M., Chan, M., Chan, W. L., Chandra, K., Chang, R. -J., Chanial, P., Chao, S., Chapman-Bird, C., Charlton, E. L., Charlton, P., Chassande-Mottin, E., Chatterjee, C., Chatterjee, Debarati, Chatterjee, Deep, Chaturvedi, M., Chaty, S., Chen, A., Chen, A. H. -Y., Chen, D., Chen, H., Chen, H. Y., Chen, K. H., Chen, X., Chen, Yi-Ru, Chen, Yanbei, Chen, Yitian, Cheng, H. P., Chessa, P., Cheung, H. T., Chia, H. Y., Chiadini, F., Chiang, C., Chiarini, G., Chiba, A., Chiba, R., Chierici, R., Chincarini, A., Chiofalo, M. L., Chiummo, A., Chou, C., Choudhary, S., Christensen, N., Chua, S. S. Y., Chung, K. W., Ciani, G., Ciecielag, P., Cieślar, M., Cifaldi, M., Ciobanu, A. A., Ciolfi, R., Clara, F., Clark, J. A., Clarke, T. A., Clearwater, P., Clesse, S., Cleva, F., Coccia, E., Codazzo, E., Cohadon, P. -F., Colleoni, M., Collette, C. G., Collins, J., Colloms, S., Colombo, A., Colpi, M., Compton, C. M., Conti, L., Cooper, S. J., Corbitt, T. R., Cordero-Carrión, I., Corezzi, S., Cornish, N. J., Corsi, A., Cortese, S., Costa, C. A., Cottingham, R., Coughlin, M. W., Couineaux, A., Coulon, J. -P., Countryman, S. T., Coupechoux, J. -F., Cousins, B., Couvares, P., Coward, D. M., Cowart, M. J., Coyne, D. C., Coyne, R., Craig, K., Creed, R., Creighton, J. D. E., Creighton, T. D., Cremonese, P., Criswell, A. W., Crockett-Gray, J. C. G., Croquette, M., Crouch, R., Crowder, S. G., Cudell, J. R., Cullen, T. J., Cumming, A., Cuoco, E., Cusinato, M., Dabadie, P., Canton, T. Dal, Dall'Osso, S., Dálya, G., D'Angelo, B., Danilishin, S., D'Antonio, S., Danzmann, K., Darroch, K. E., Dartez, L. P., Dasgupta, A., Datta, S., Dattilo, V., Daumas, A., Davari, N., Dave, I., Davenport, A., Davier, M., Davies, T. F., Davis, D., Davis, L., Davis, M. C., Daw, E. J., Dax, M., De Bolle, J., Deenadayalan, M., Degallaix, J., De Laurentis, M., Deléglise, S., Del Favero, V., De Lillo, F., Dell'Aquila, D., Del Pozzo, W., De Marco, F., De Matteis, F., D'Emilio, V., Demos, N., Dent, T., Depasse, A., DePergola, N., De Pietri, R., De Rosa, R., De Rossi, C., De Simone, R., Dhani, A., Dhurandhar, S., Diab, R., Díaz, M. C., Di Cesare, M., Dideron, G., Didio, N. A., Dietrich, T., Di Fiore, L., Di Fronzo, C., Di Giovanni, F., Di Giovanni, M., Di Girolamo, T., Diksha, D., Di Michele, A., Ding, J., Di Pace, S., Di Palma, I., Di Renzo, F., Divyajyoti, Dmitriev, A., Doctor, Z., Dohmen, E., Doleva, P. P., Donahue, L., D'Onofrio, L., Donovan, F., Dooley, K. L., Dooney, T., Doravari, S., Dorosh, O., Drago, M., Driggers, J. C., Drori, Y., Ducoin, J. -G., Dunn, L., Dupletsa, U., D'Urso, D., Duval, H., Duverne, P. -A., Dwyer, S. E., Eassa, C., Ebersold, M., Eckhardt, T., Eddolls, G., Edelman, B., Edo, T. B., Edy, O., Effler, A., Eichholz, J., Einsle, H., Eisenmann, M., Eisenstein, R. A., Ejlli, A., Emma, M., Engelby, E., Engl, A. J., Errico, L., Essick, R. C., Estellés, H., Estevez, D., Etzel, T., Evans, M., Evstafyeva, T., Ewing, B. E., Ezquiaga, J. M., Fabrizi, F., Faedi, F., Fafone, V., Fairhurst, S., Fan, P. C., Farah, A. M., Farr, B., Farr, W. M., Favaro, G., Favata, M., Fays, M., Fazio, M., Feicht, J., Fejer, M. M., Fenyvesi, E., Ferguson, D. L., Ferrante, I., Ferreira, T. A., Fidecaro, F., Fiori, A., Fiori, I., Fishbach, M., Fisher, R. P., Fittipaldi, R., Fiumara, V., Flaminio, R., Fleischer, S. M., Fleming, L. S., Floden, E., Foley, E. M., Fong, H., Font, J. A., Fornal, B., Forsyth, P. W. F., Franceschetti, K., Franchini, N., Frasca, S., Frasconi, F., Mascioli, A. Frattale, Frei, Z., Freise, A., Freitas, O., Frey, R., Frischhertz, W., Fritschel, P., Frolov, V. V., Fronzé, G. G., Fuentes-Garcia, M., Fujii, S., Fukunaga, I., Fulda, P., Fyffe, M., Gabella, W. 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D., Lawrence, J., Laxen, M., Lazzarini, A., Lazzaro, C., Leaci, P., LeBohec, S., Lecoeuche, Y. K., Lee, H. M., Lee, H. W., Lee, K., Lee, R. -K., Lee, R., Lee, S., Lee, Y., Legred, I. N., Lehmann, J., Lehner, L., Lemaître, A., Lenti, M., Leonardi, M., Leonova, E., Lequime, M., Leroy, N., Lesovsky, M., Letendre, N., Lethuillier, M., Levesque, C., Levin, Y., Leyde, K., Li, A. K. Y., Li, K. L., Li, T. G. F., Li, X., Lin, Chien-Yu, Lin, Chun-Yu, Lin, E. T., Lin, F., Lin, H., Lin, L. C. -C., Linde, F., Linker, S. D., Littenberg, T. B., Liu, A., Liu, G. C., Liu, Jian, Llamas, F., Llobera-Querol, J., Lo, R. K. L., Locquet, J. -P., London, L., Longo, A., Lopez, D., Portilla, M. Lopez, Lorenzini, M., Loriette, V., Lormand, M., Losurdo, G., Lott IV, T. P., Lough, J. D., Loughlin, H. A., Lousto, C. O., Lowry, M. J., Lück, H., Lumaca, D., Lundgren, A. P., Lussier, A. W., Ma, L. -T., Ma, S., Ma'arif, M., Macas, R., MacInnis, M., Maciy, R. R., Macleod, D. M., MacMillan, I. A. O., Macquet, A., Macri, D., Maeda, K., Maenaut, S., Hernandez, I. Magaña, Magare, S. S., Magazzù, C., Magee, R. M., Maggio, E., Maggiore, R., Magnozzi, M., Mahesh, M., Mahesh, S., Maini, M., Majhi, S., Majorana, E., Makarem, C. N., Malaquias-Reis, J. A., Maliakal, S., Malik, A., Man, N., Mandic, V., Mangano, V., Mannix, B., Mansell, G. L., Manske, M., Mantovani, M., Mapelli, M., Marchesoni, F., Pina, D. Marín, Marion, F., Márka, S., Márka, Z., Markakis, C., Markosyan, A. S., Markowitz, A., Maros, E., Marquina, A., Marsat, S., Martelli, F., Martin, I. W., Martin, R. M., Martinez, B. B., Martinez, M., Martinez, V., Martini, A., Martinovic, K., Martins, J. C., Martynov, D. V., Marx, E. J., Massaro, L., Masserot, A., Masso-Reid, M., Mastrodicasa, M., Mastrogiovanni, S., Mateu-Lucena, M., Matiushechkina, M., Matsuyama, M., Mavalvala, N., Maxwell, N., McCarrol, G., McCarthy, R., McClelland, D. E., McCormick, S., McCuller, L., McGhee, G. I., McGowan, K. B. 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P., Spera, M., Spinicelli, P., Srivastava, A. K., Stachurski, F., Steer, D. A., Steinlechner, J., Steinlechner, S., Stergioulas, N., Stevens, P., StPierre, M., Strang, L. C., Stratta, G., Strong, M. D., Strunk, A., Sturani, R., Stuver, A. L., Suchenek, M., Sudhagar, S., Sueltmann, N., Sullivan, A. G., Sullivan, K. D., Sun, L., Sunil, S., Sur, A., Suresh, J., Sutton, P. J., Suzuki, Takamasa, Suzuki, Takanori, Swinkels, B. L., Syx, A., Szczepańczyk, M. J., Szewczyk, P., Tacca, M., Tagoshi, H., Tait, S. C., Takahashi, H., Takahashi, R., Takamori, A., Takatani, K., Takeda, H., Takeda, M., Talbot, C. J., Talbot, C., Tamaki, M., Tamanini, N., Tanabe, D., Tanaka, K., Tanaka, S. J., Tanaka, T., Tanasijczuk, A. J., Tang, D., Tanioka, S., Tanner, D. B., Tao, L., Tapia, R. D., Martín, E. N. Tapia San, Tarafder, R., Taranto, C., Taruya, A., Tasson, J. D., Teloi, M., Tenorio, R., Themann, H., Theodoropoulos, A., Thirugnanasambandam, M. P., Thomas, L. M., Thomas, M., Thomas, P., Thompson, J. 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A., Weinert, M., Weinstein, A. J., Weiss, R., Weller, C. M., Weller, R. A., Wellmann, F., Wen, L., Weßels, P., Wette, K., Whelan, J. T., White, D. D., Whiting, B. F., Whittle, C., Wildberger, J. B., Wilk, O. S., Wilken, D., Willetts, K., Williams, D., Williams, M. J., Williams, N. S., Willis, J. L., Willke, B., Wils, M., Wipf, C. C., Woan, G., Woehler, J., Wofford, J. K., Wolfe, N. E., Wong, D., Wong, H. T., Wong, H. W. Y., Wong, I. C. F., Wright, J. L., Wright, M., Wu, C., Wu, D. S., Wu, H., Wysocki, D. M., Xiao, L., Xu, V. A., Xu, Y., Yadav, N., Yamamoto, H., Yamamoto, K., Yamamoto, M., Yamamoto, T. S., Yamamoto, T., Yamamura, S., Yamazaki, R., Yan, S., Yan, T., Yang, F. W., Yang, F., Yang, K. Z., Yang, L. -C., Yang, Y., Yarbrough, Z., Yeh, S. -W., Yelikar, A. B., Yeung, S. M. C., Yin, X., Yokoyama, J., Yokozawa, T., Yoo, J., Yu, H., Yuzurihara, H., Zadrożny, A., Zannelli, A. J., Zanolin, M., Zeeshan, M., Zelenova, T., Zendri, J. -P., Zeoli, M., Zerrad, M., Zevin, M., Zhang, A. C., Zhang, J., Zhang, L., Zhang, R., Zhang, T., Zhang, Y., Zhao, C., Zhao, Yue, Zhao, Yuhang, Zheng, Y., Zhong, H., Zhong, S., Zhou, R., Zhu, Z. -H., Zimmerman, A. B., Zucker, M. E., and Zweizig, J.
Subjects: Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology
Abstract: We present results from a search for X-ray/gamma-ray counterparts of gravitational-wave (GW) candidates from the third observing run (O3) of the LIGO-Virgo-KAGRA (LVK) network using the Swift Burst Alert Telescope (Swift-BAT). The search includes 636 GW candidates received in low latency, 86 of which have been confirmed by the offline analysis and included in the third cumulative Gravitational-Wave Transient Catalogs (GWTC-3). Targeted searches were carried out on the entire GW sample using the maximum--likelihood NITRATES pipeline on the BAT data made available via the GUANO infrastructure. We do not detect any significant electromagnetic emission that is temporally and spatially coincident with any of the GW candidates. We report flux upper limits in the 15-350 keV band as a function of sky position for all the catalog candidates. For GW candidates where the Swift-BAT false alarm rate is less than 10$^{-3}$ Hz, we compute the GW--BAT joint false alarm rate. Finally, the derived Swift-BAT upper limits are used to infer constraints on the putative electromagnetic emission associated with binary black hole mergers., Comment: 50 pages, 10 figures, 4 tables
Published: 2024

27. Expression of dehydroshikimate dehydratase in poplar induces transcriptional and metabolic changes in the phenylpropanoid pathway

Author: Turumtay, Emine Akyuz, Turumtay, Halbay, Tian, Yang, Lin, Chien-Yuan, Chai, Yen Ning, Louie, Katherine B, Chen, Yan, Lipzen, Anna, Harwood, Thomas, Kumar, Kavitha Satish, Bowen, Benjamin P, Wang, Qian, Mansfield, Shawn D, Blow, Matthew J, Petzold, Christopher J, Northen, Trent R, Mortimer, Jenny C, Scheller, Henrik V, and Eudes, Aymerick
Subjects: Biological Sciences, Industrial Biotechnology, Genetics, Biotechnology, 2.1 Biological and endogenous factors, Populus, Lignin, Hydro-Lyases, Gene Expression Regulation, Plant, Plants, Genetically Modified, Plant Proteins, Xylem, Aromatics, bioenergy, cell wall, lignin, metabolomics, RNA-seq, systems biology, Plant Biology, Crop and Pasture Production, Plant Biology & Botany, Crop and pasture production, Biochemistry and cell biology, Plant biology
Abstract: Modification of lignin in feedstocks via genetic engineering aims to reduce biomass recalcitrance to facilitate efficient conversion processes. These improvements can be achieved by expressing exogenous enzymes that interfere with native biosynthetic pathways responsible for the production of the lignin precursors. In planta expression of a bacterial 3-dehydroshikimate dehydratase in poplar trees reduced lignin content and altered the monomer composition, which enabled higher yields of sugars after cell wall polysaccharide hydrolysis. Understanding how plants respond to such genetic modifications at the transcriptional and metabolic levels is needed to facilitate further improvement and field deployment. In this work, we acquired fundamental knowledge on lignin-modified poplar expressing 3-dehydroshikimate dehydratase using RNA-seq and metabolomics. The data clearly demonstrate that changes in gene expression and metabolite abundance can occur in a strict spatiotemporal fashion, revealing tissue-specific responses in the xylem, phloem, or periderm. In the poplar line that exhibited the strongest reduction in lignin, we found that 3% of the transcripts had altered expression levels and ~19% of the detected metabolites had differential abundance in the xylem from older stems. The changes affected predominantly the shikimate and phenylpropanoid pathways as well as secondary cell wall metabolism, and resulted in significant accumulation of hydroxybenzoates derived from protocatechuate and salicylate.
Published: 2024

28. On the existence of conic Sasaki-Einstein metrics on log Fano Sasakian manifolds of dimension five

Author: Chang, Shu-Cheng, Li, Fengjiang, Lin, Chien, and Wu, Chin-Tung
Subjects: Mathematics - Differential Geometry
Abstract: In this paper, we derive the uniform L^{4}-bound of the transverse conic Ricci curvature along the conic Sasaki-Ricci flow on a compact transverse log Fano Sasakian manifold M of dimension five and the space of leaves of the characteristic foliation is not well-formed. Then we first show that any solution of the conic Sasaki-Ricci flow converges in the Cheeger-Gromov sense to the unique singular orbifold conic Sasaki-Ricci soliton on M_{infinite} which is a S^{1}-orbibundle over the unique singular conic Keahler-Ricci soliton on a log del Pezzo orbifold surface. As a consequence, there exists a Keahler-Ricci soliton orbifold metric on its leave space which is a log del Pezzo orbifold surface. Second, we show that the conic Sasaki-Ricci soliton is the conic Sasaki-Einstein if M is transverse log K-polystable. In summary, we have the existence theorems of orbifold Sasaki-Ricci solitons and Sasaki-Einstein metrics on a compact quasi-regular Sasakian manifold of dimension five.
Published: 2024

29. Discovery and Extensive Follow-Up of SN 2024ggi, a nearby type IIP supernova in NGC 3621

Author: Chen, Ting-Wan, Yang, Sheng, Srivastav, Shubham, Moriya, Takashi J., Smartt, Stephen J., Rest, Sofia, Rest, Armin, Lin, Hsing Wen, Miao, Hao-Yu, Cheng, Yu-Chi, Aryan, Amar, Cheng, Chia-Yu, Fraser, Morgan, Huang, Li-Ching, Lee, Meng-Han, Lai, Cheng-Han, Liu, Yu Hsuan, K, Aiswarya Sankar., Smith, Ken W., Stevance, Heloise F., Wang, Ze-Ning, Anderson, Joseph P., Angus, Charlotte R., de Boer, Thomas, Chambers, Kenneth, Duan, Hao-Yuan, Erasmus, Nicolas, Gao, Hua, Herman, Joanna, Hou, Wei-Jie, Hsiao, Hsiang-Yao, Huber, Mark E., Lin, Chien-Cheng, Lin, Hung-Chin, Magnier, Eugene A., Man, Ka Kit, Moore, Thomas, Ngeow, Chow-Choong, Nicholl, Matt, Ou, Po-Sheng, Pignata, Giuliano, Shiau, Yu-Chien, Sommer, Julian Silvester, Tonry, John L., Wang, Xiao-Feng, Young, David R., Yeh, You-Ting, and Zhang, Jujia
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: We present the discovery and early observations of the nearby Type II supernova (SN) 2024ggi in NGC 3621 at 6.64 +/- 0.3 Mpc. The SN was caught 5.8 (+1.9 -2.9) hours after its explosion by the ATLAS survey. Early-phase, high-cadence, and multi-band photometric follow-up was performed by the Kinder (Kilonova Finder) project, collecting over 1000 photometric data points within a week. The combined o- and r-band light curves show a rapid rise of 3.3 magnitudes in 13.7 hours, much faster than SN 2023ixf (another recent, nearby, and well-observed SN II). Between 13.8 and 18.8 hours after explosion SN 2024ggi became bluer, with u-g colour dropping from 0.53 to 0.15 mag. The rapid blueward evolution indicates a wind shock breakout (SBO) scenario. No hour-long brightening expected for the SBO from a bare stellar surface was detected during our observations. The classification spectrum, taken 17 hours after the SN explosion, shows flash features of high-ionization species such as Balmer lines, He I, C III, and N III. Detailed light curve modeling reveals critical insights into the properties of the circumstellar material (CSM). Our favoured model has an explosion energy of 2 x 10^51 erg, a mass-loss rate of 10^-3 solar_mass/yr (with an assumed 10 km/s wind), and a confined CSM radius of 6 x 10^14 cm. The corresponding CSM mass is 0.4 solar_mass. Comparisons with SN 2023ixf highlight that SN 2024ggi has a smaller CSM density, resulting in a faster rise and fainter UV flux. The extensive dataset and the involvement of citizen astronomers underscore that a collaborative network is essential for SBO searches, leading to more precise and comprehensive SN characterizations., Comment: 11 pages, 5 figures in manuscript, 6 pages in appendix, submitted to ApJL
Published: 2024

30. SN 2023zaw: the low-energy explosion of an ultra-stripped star, with non-radioactive heating

Author: Moore, Thomas, Gillanders, James, Nicholl, Matt, Huber, Mark, Smartt, Stephen, Srivastav, Shubham, Stevance, Heloise, Chen, Ting-Wan, Chambers, Kenneth, Anderson, Joseph, Fulton, Michael, Oates, Samantha, Angus, Charlotte, Pignata, Giuliano, Erasmus, Nicolas, Gao, Hua, Bulger, Joanna, Lin, Chien-Cheng, Lowe, Thomas, Magnier, Eugene, Minguez, Paloma, Ngeow, Chow-Choong, Sheng, Xinyue, Sim, Stuart A., Smith, Ken, Wainscoat, Richard, Yang, Sheng, Young, David, and Zeng, Kuang-Jie
Subjects: Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Solar and Stellar Astrophysics
Abstract: Most stripped envelope supernova progenitors are formed through binary interaction, losing hydrogen and/or helium from their outer layers. An emerging class of supernovae with the highest degree of envelope-stripping are thought to be the product of stripping by a NS companion. However, relatively few examples are known and the outcomes of such systems can be diverse and are poorly understood at present. Here, we present spectroscopic observations and high cadence multi-band photometry of SN 2023zaw, a low ejecta mass and rapidly evolving supernova. SN 2023zaw was discovered in a nearby spiral galaxy at D = 39.7 Mpc, with significant Milky Way extinction, $E(B-V) = 0.21$, and significant (but uncertain) host extinction. Bayesian evidence comparison reveals that nickel is not the only power source and an additional energy source is required to explain our observations. Our models suggest an ejecta mass of $M_{\rm ej} \sim 0.07\,\rm M_\odot$ and a synthesised nickel mass of $M_{\rm ej} \sim 0.007\,\rm M_\odot$ is required to explain the explosion. However an additional heating from a magnetar or interaction with circumstellar material is required to power the early light curve.
Published: 2024

31. The Extremely Metal-Poor SN 2023ufx: A Local Analog to High-Redshift Type II Supernovae

Author: Tucker, Michael A., Hinkle, Jason, Angus, Charlotte R., Auchettl, Katie, Hoogendam, Willem B., Shappee, Benjamin, Kochanek, Christopher S., Ashall, Chris, de Boer, Thomas, Chambers, Kenneth C., Desai, Dhvanil D., Do, Aaron, Fulton, Michael D., Gao, Hua, Herman, Joanna, Huber, Mark, Lidman, Chris, Lin, Chien-Cheng, Lowe, Thomas B., Magnier, Eugene A., Martin, Bailey, Minguez, Paloma, Nicholl, Matt, Pursiainen, Miika, Smartt, S. J., Smith, Ken W., Srivastav, Shubham, Tucker, Brad E., and Wainscoat, Richard J.
Subjects: Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Astrophysics of Galaxies, Astrophysics - High Energy Astrophysical Phenomena
Abstract: We present extensive observations of the Type II supernova (SN II) 2023ufx which is likely the most metal-poor SN II observed to-date. It exploded in the outskirts of a low-metallicity ($Z_{\rm host} \sim 0.1~Z_\odot$) dwarf ($M_g = -13.23\pm0.15$~mag; $r_e\sim 1$~kpc) galaxy. The explosion is luminous, peaking at $M_g\approx -18.5~$mag, and shows rapid evolution. The $r$-band (pseudo-bolometric) light curve has a shock-cooling phase lasting 20 (17) days followed by a 19 (23)-day plateau. The entire optically-thick phase lasts only $\approx 55~$days following explosion, indicating that the red supergiant progenitor had a thinned H envelope prior to explosion. The early spectra obtained during the shock-cooling phase show no evidence for narrow emission features and limit the pre-explosion mass-loss rate to $\dot{M} \lesssim 10^{-3}~\rm M_\odot$/yr. The photospheric-phase spectra are devoid of prominent metal absorption features, indicating a progenitor metallicity of $\lesssim 0.1~Z_\odot$. The semi-nebular ($\sim 60-130~$d) spectra reveal weak Fe II, but other metal species typically observed at these phases (Ti II, Sc II, Ba II) are conspicuously absent. The late-phase optical and near-infrared spectra also reveal broad ($\approx 10^4~\rm{km}~\rm s^{-1}$) double-peaked H$\alpha$, P$\beta$, and P$\gamma$ emission profiles suggestive of a fast outflow launched during the explosion. Outflows are typically attributed to rapidly-rotating progenitors which also prefer metal-poor environments. This is only the second SN II with $\lesssim 0.1~Z_\odot$ and both exhibit peculiar evolution, suggesting a sizable fraction of metal-poor SNe II have distinct properties compared to nearby metal-enriched SNe II. These observations lay the groundwork for modeling the metal-poor SNe II expected in the early Universe., Comment: 17 pages, 15 figures and 3 tables in main text, an additional 5 pages, 4 figures, and 2 tables in the appendix. Accepted by ApJ, spectra and photometry are included as ancillary data
Published: 2024
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32. The Effect of a Name-Based Mask Rationing Plan in Taiwan on Public Anxiety Regarding a Mask Shortage During the COVID-19 Pandemic: Observational Study

Author: Tai, Yu-Lin, Chi, Hsin, Chiu, Nan-Chang, Tseng, Cheng-Yin, Huang, Ya-Ning, and Lin, Chien-Yu
Subjects: Medicine
Abstract: BackgroundThe COVID-19 pandemic is a severe global health crisis. Wearing a mask is a straightforward action that can be taken, but shortage of stock and equity of allocation were important issues in Taiwan. Furthermore, increased anxiety leading to the stockpiling of masks has been common during the pandemic. ObjectiveWe aim to summarize the name-based mask rationing plan implemented in Taiwan and explore the public’s perceived anxiety about mask shortages. MethodsThe government of Taiwan took action to control the supply and allocation of face masks. We summarize the timeline and important components of the mask rationing plan. A survey that aimed to investigate the overall response to the mask rationing plan was answered by 44 participants. ResultsThe mask rationing plan was implemented in late January 2020. Daily production capacity was increased from 2 million masks to 16 million masks in April 2020. People could buy 9 masks in 14 days by verification via their National Health Insurance card. Digital face mask availability maps were created. Moreover, the mask plan safeguarded the purchase of masks and resulted in decreased anxiety about a mask shortage (4.05 [SD 1.15] points; 72.7% [n=32] of participants answered “agree” or “strongly agree”). The majority of people felt that the mask plan was satisfactory (4.2 [SD 0.92] points; 79.5% [n=35] of participants answered “agree” or “strongly agree”). ConclusionsWe found that the unique name-based mask rationing plan allowed for control of the production and supply of masks, and contributed to the appropriate allocation of masks. The mask rationing plan not only provided the public with physical protection, but also resulted in reduced anxiety about mask shortages during the pandemic.
Published: 2021
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33. Age- and gender-dependent impact of titanium vertebral augmentation implants combined with cementing on subsequent vertebral fracture incidence: A comparative study with cementing alone

Author: Sun, Chien-Ting, Yang, Yi-Shan, Lan, Chen-Ling, Tran, Huy Minh, Pham, Tuan Anh, Chiang, Yung-Hsiao, Lin, Chien-Min, Su, Yu-Kai, Hsieh, Yi-Chen, and Lin, Jiann-Her
Published: 2024
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34. Positive Association Between Serum Concentration of 4-Tertiary-octylphenol and Oxidation of DNA and Lipid in Adolescents and Young Adults

Author: Lin, Chien-Yu, Lee, Hui-Ling, Wang, Chikang, Sung, Fung-Chang, and Su, Ta-Chen
Published: 2024
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35. The Association Among Urinary Di-(2-ethylhexyl) Phthalate Metabolites, Serum Lipid Profiles, and Serum Apoptotic Microparticles in a Young Taiwanese Population

Author: Lin, Chien-Yu, Hsu, Sandy Huey-Jen, Chen, Ching-Way, Wang, Chikang, Sung, Fung-Chang, and Su, Ta-Chen
Published: 2024
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36. Analysis of Torsional Mechanical Behavior of Adjustable Air Cushion Sole Structures: Impact Simulation on Cutting Maneuvers

Author: Arefin, Md Samsul, Lin, Chien-Ju, Chieh, Hsiao-Feng, An, Kai-Nan, Huang, Ying-Chun, and Su, Fong-Chin
Published: 2024
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37. The association between myasthenia gravis and risk of fracture: a systematic review and meta-analysis

Author: Lin, Chien-Ju, Lee, Yu-Shan, Yeh, Jiann-Horng, Liu, Shu-Jung, and Lin, Kuan-Yu
Published: 2024
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38. Impact of Wearing Masks, Hand Hygiene, and Social Distancing on Influenza, Enterovirus, and All-Cause Pneumonia During the Coronavirus Pandemic: Retrospective National Epidemiological Surveillance Study

Author: Chiu, Nan-Chang, Chi, Hsin, Tai, Yu-Lin, Peng, Chun-Chih, Tseng, Cheng-Yin, Chen, Chung-Chu, Tan, Boon Fatt, and Lin, Chien-Yu
Subjects: Computer applications to medicine. Medical informatics, R858-859.7, Public aspects of medicine, RA1-1270
Abstract: BackgroundThe coronavirus disease (COVID-19) pandemic is an important health crisis worldwide. Several strategies were implemented to combat COVID-19, including wearing masks, hand hygiene, and social distancing. The impact of these strategies on COVID-19 and other viral infections remains largely unclear. ObjectiveWe aim to investigate the impact of implemented infectious control strategies on the incidences of influenza, enterovirus infection, and all-cause pneumonia during the COVID-19 pandemic. MethodsWe utilized the electronic database of the Taiwan National Infectious Disease Statistics System and extracted incidences of COVID-19, influenza virus, enterovirus, and all-cause pneumonia. We compared the incidences of these diseases from week 45 of 2016 to week 21 of 2020 and performed linear regression analyses. ResultsThe first case of COVID-19 in Taiwan was reported in late January 2020 (week 4). Infectious control strategies have been promoted since late January. The influenza virus usually peaks in winter and decreases around week 14. However, a significant decrease in influenza was observed after week 6 of 2020. Regression analyses produced the following results: 2017, R2=0.037; 2018, R2=0.021; 2019, R2=0.046; and 2020, R2=0.599. A dramatic decrease in all-cause pneumonia was also reported (R2 values for 2017-2020 were 0.435, 0.098, 0.352, and 0.82, respectively). Enterovirus had increased by week 18 in 2017-2019, but this was not observed in 2020. ConclusionsUsing this national epidemiological database, we found a significant decrease in cases of influenza, enterovirus, and all-cause pneumonia during the COVID-19 pandemic. Wearing masks, hand hygiene, and social distancing may contribute not only to the prevention of COVID-19 but also to the decline of other respiratory infectious diseases. Further studies are warranted to elucidate the causal relationship.
Published: 2020
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39. A Double Triage and Telemedicine Protocol to Optimize Infection Control in an Emergency Department in Taiwan During the COVID-19 Pandemic: Retrospective Feasibility Study

Author: Lin, Chien-Hao, Tseng, Wen-Pin, Wu, Jhong-Lin, Tay, Joyce, Cheng, Ming-Tai, Ong, Hooi-Nee, Lin, Hao-Yang, Chen, Yi-Ying, Wu, Chih-Hsien, Chen, Jiun-Wei, Chen, Shey-Ying, Chan, Chang-Chuan, Huang, Chien-Hua, and Chen, Shyr-Chyr
Subjects: Computer applications to medicine. Medical informatics, R858-859.7, Public aspects of medicine, RA1-1270
Abstract: BackgroundFrontline health care workers, including physicians, are at high risk of contracting coronavirus disease (COVID-19) owing to their exposure to patients suspected of having COVID-19. ObjectiveThe aim of this study was to evaluate the benefits and feasibility of a double triage and telemedicine protocol in improving infection control in the emergency department (ED). MethodsIn this retrospective study, we recruited patients aged ≥20 years referred to the ED of the National Taiwan University Hospital between March 1 and April 30, 2020. A double triage and telemedicine protocol was developed to triage suggested COVID-19 cases and minimize health workers’ exposure to this disease. We categorized patients attending video interviews into a telemedicine group and patients experiencing face-to-face interviews into a conventional group. A questionnaire was used to assess how patients perceived the quality of the interviews and their communication with physicians as well as perceptions of stress, discrimination, and privacy. Each question was evaluated using a 5-point Likert scale. Physicians’ total exposure time and total evaluation time were treated as primary outcomes, and the mean scores of the questions were treated as secondary outcomes. ResultsThe final sample included 198 patients, including 93 cases (47.0%) in the telemedicine group and 105 cases (53.0%) in the conventional group. The total exposure time in the telemedicine group was significantly shorter than that in the conventional group (4.7 minutes vs 8.9 minutes, P
Published: 2020
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40. Efficient Encoder-Decoder Transformer Decoding for Decomposable Tasks

Author: Lu, Bo-Ru, Haduong, Nikita, Lin, Chien-Yu, Cheng, Hao, Smith, Noah A., and Ostendorf, Mari
Subjects: Computer Science - Computation and Language
Abstract: Transformer-based NLP models are powerful but have high computational costs that limit deployment. Finetuned encoder-decoder models are popular in specialized domains and can outperform larger more generalized decoder-only models, such as GPT-4. We introduce a new configuration for encoder-decoder models that improves efficiency on structured output and decomposable tasks where multiple outputs are required for a single shared input. Our method, prompt-in-decoder (PiD), encodes the input once and decodes the output in parallel, boosting both training and inference efficiency by avoiding duplicate input encoding and increasing the operational intensity (ratio of numbers of arithmetic operation to memory access) of decoding process by sharing the input key-value cache. We achieve computation reduction that roughly scales with the number of subtasks, gaining up to 4.6x speed-up over state-of-the-art models for dialogue state tracking, summarization, and question-answering tasks, with comparable or better performance., Comment: 18 pages
Published: 2024

41. Ultralight vector dark matter search using data from the KAGRA O3GK run

Author: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, Abac, A. G., Abbott, R., Abe, H., Abouelfettouh, I., Acernese, F., Ackley, K., Adamcewicz, C., Adhicary, S., Adhikari, N., Adhikari, R. X., Adkins, V. K., Adya, V. B., Affeldt, C., Agarwal, D., Agathos, M., Aguiar, O. D., Aguilar, I., Aiello, L., Ain, A., Ajith, P., Akutsu, T., Albanesi, S., Alfaidi, R. A., Al-Jodah, A., Alléné, C., Allocca, A., Al-Shammari, S., Altin, P. A., Alvarez-Lopez, S., Amato, A., Amez-Droz, L., Amorosi, A., Amra, C., Anand, S., Ananyeva, A., Anderson, S. B., Anderson, W. G., Andia, M., Ando, M., Andrade, T., Andres, N., Andrés-Carcasona, M., Andrić, T., Anglin, J., Ansoldi, S., Antelis, J. M., Antier, S., Aoumi, M., Appavuravther, E. Z., Appert, S., Apple, S. K., Arai, K., Araya, A., Araya, M. C., Areeda, J. S., Aritomi, N., Armato, F., Arnaud, N., Arogeti, M., Aronson, S. M., Arun, K. G., Ashton, G., Aso, Y., Assiduo, M., Melo, S. Assis de Souza, Aston, S. M., Astone, P., Aubin, F., AultONeal, K., Avallone, G., Babak, S., Badaracco, F., Badger, C., Bae, S., Bagnasco, S., Bagui, E., Bai, Y., Baier, J. G., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. W., Banagiri, S., Banerjee, B., Bankar, D., Baral, P., Barayoga, J. C., Barish, B. C., Barker, D., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Barthelmy, S. D., Barton, M. A., Bartos, I., Basak, S., Basalaev, A., Bassiri, R., Basti, A., Bawaj, M., Baxi, P., Bayley, J. C., Baylor, A. C., Bazzan, M., Bécsy, B., Bedakihale, V. M., Beirnaert, F., Bejger, M., Belardinelli, D., Bell, A. S., Benedetto, V., Beniwal, D., Benoit, W., Bentley, J. D., Yaala, M. Ben, Bera, S., Berbel, M., Bergamin, F., Berger, B. K., Bernuzzi, S., Beroiz, M., Bersanetti, D., Bertolini, A., Betzwieser, J., Beveridge, D., Bevins, N., Bhandare, R., Bhardwaj, U., Bhatt, R., Bhattacharjee, D., Bhaumik, S., Bhowmick, S., Bianchi, A., Bilenko, I. A., Billingsley, G., Binetti, A., Bini, S., Birnholtz, O., Biscoveanu, S., Bisht, A., Bitossi, M., Bizouard, M. -A., Blackburn, J. K., Blair, C. D., Blair, D. G., Bobba, F., Bode, N., Bogaert, G., Boileau, G., Boldrini, M., Bolingbroke, G. N., Bolliand, A., Bonavena, L. D., Bondarescu, R., Bondu, F., Bonilla, E., Bonilla, M. S., Bonino, A., Bonnand, R., Booker, P., Borchers, A., Boschi, V., Bose, S., Bossilkov, V., Boudart, V., Boumerdassi, A., Bozzi, A., Bradaschia, C., Brady, P. R., Braglia, M., Branch, A., Branchesi, M., Breschi, M., Briant, T., Brillet, A., Brinkmann, M., Brockill, P., Brockmueller, E., Brooks, A. F., Brown, D. D., Brozzetti, M. L., Brunett, S., Bruno, G., Bruntz, R., Bryant, J., Bucci, F., Buchanan, J., Bulashenko, O., Bulik, T., Bulten, H. J., Buonanno, A., Burtnyk, K., Buscicchio, R., Buskulic, D., Buy, C., Byer, R. L., Davies, G. S. Cabourn, Cabras, G., Cabrita, R., Cadonati, L., Cagnoli, G., Cahillane, C., Bustillo, J. Calderón, Callaghan, J. D., Callister, T. A., Calloni, E., Camp, J. B., Santoro, G. Caneva, Cannavacciuolo, M., Cannon, K. C., Cao, H., Cao, Z., Capistran, L. A., Capocasa, E., Capote, E., Carapella, G., Carbognani, F., Carlassara, M., Carlin, J. B., Carpinelli, M., Carrillo, G., Carter, J. J., Carullo, G., Diaz, J. Casanueva, Casentini, C., Castaldi, G., Castro-Lucas, S. Y., Caudill, S., Cavaglià, M., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, W., Chakraborty, P., Subrahmanya, S. Chalathadka, Chan, C., Chan, J. C. L., Chan, K. H. M., Chan, M., Chan, W. L., Chandra, K., Chang, R. -J., Chanial, P., Chao, S., Chapman-Bird, C., Charlton, E. L., Charlton, P., Chassande-Mottin, E., Chatterjee, C., Chatterjee, Debarati, Chatterjee, Deep, Chaturvedi, M., Chaty, S., Chatziioannou, K., Chen, A., Chen, A. H. -Y., Chen, D., Chen, H., Chen, H. Y., Chen, K. H., Chen, X., Chen, Yi-Ru, Chen, Yanbei, Chen, Yitian, Cheng, H. P., Chessa, P., Cheung, H. T., Chia, H. Y., Chiadini, F., Chiang, C., Chiarini, G., Chiba, A., Chiba, R., Chierici, R., Chincarini, A., Chiofalo, M. L., Chiummo, A., Chou, C., Choudhary, S., Christensen, N., Chua, S. S. Y., Chung, K. W., Ciani, G., Ciecielag, P., Cieślar, M., Cifaldi, M., Ciobanu, A. A., Ciolfi, R., Clara, F., Clark, J. A., Clarke, T. A., Clearwater, P., Clesse, S., Cleva, F., Coccia, E., Codazzo, E., Cohadon, P. -F., Colleoni, M., Collette, C. G., Collins, J., Colloms, S., Colombo, A., Colpi, M., Compton, C. M., Conti, L., Cooper, S. J., Corbitt, T. R., Cordero-Carrión, I., Corezzi, S., Cornish, N. J., Corsi, A., Cortese, S., Costa, C. A., Cottingham, R., Coughlin, M. W., Couineaux, A., Coulon, J. -P., Countryman, S. T., Coupechoux, J. -F., Cousins, B., Couvares, P., Coward, D. M., Cowart, M. J., Coyne, D. C., Coyne, R., Craig, K., Creed, R., Creighton, J. D. E., Creighton, T. D., Cremonese, P., Criswell, A. W., Crockett-Gray, J. C. G., Croquette, M., Crouch, R., Crowder, S. G., Cudell, J. R., Cullen, T. J., Cumming, A., Cuoco, E., Cusinato, M., Dabadie, P., Canton, T. Dal, Dall'Osso, S., Dálya, G., D'Angelo, B., Danilishin, S., D'Antonio, S., Danzmann, K., Darroch, K. E., Dartez, L. P., Dasgupta, A., Datta, S., Dattilo, V., Daumas, A., Davari, N., Dave, I., Davenport, A., Davier, M., Davies, T. F., Davis, D., Davis, L., Davis, M. C., Daw, E. J., Dax, M., De Bolle, J., Deenadayalan, M., Degallaix, J., De Laurentis, M., Deléglise, S., Del Favero, V., De Lillo, F., Dell'Aquila, D., Del Pozzo, W., De Marco, F., De Matteis, F., D'Emilio, V., Demos, N., Dent, T., Depasse, A., DePergola, N., De Pietri, R., De Rosa, R., De Rossi, C., De Simone, R., Dhani, A., Dhurandhar, S., Diab, R., Díaz, M. C., Di Cesare, M., Dideron, G., Didio, N. A., Dietrich, T., Di Fiore, L., Di Fronzo, C., Di Giovanni, F., Di Giovanni, M., Di Girolamo, T., Diksha, D., Di Michele, A., Ding, J., Di Pace, S., Di Palma, I., Di Renzo, F., Divyajyoti, Dmitriev, A., Doctor, Z., Dohmen, E., Doleva, P. P., Donahue, L., D'Onofrio, L., Donovan, F., Dooley, K. L., Dooney, T., Doravari, S., Dorosh, O., Drago, M., Driggers, J. C., Drori, Y., Ducoin, J. -G., Dunn, L., Dupletsa, U., D'Urso, D., Duval, H., Duverne, P. -A., Dwyer, S. E., Eassa, C., Ebersold, M., Eckhardt, T., Eddolls, G., Edelman, B., Edo, T. B., Edy, O., Effler, A., Eichholz, J., Einsle, H., Eisenmann, M., Eisenstein, R. A., Ejlli, A., Emma, M., Engelby, E., Engl, A. J., Errico, L., Essick, R. C., Estellés, H., Estevez, D., Etzel, T., Evans, M., Evstafyeva, T., Ewing, B. E., Ezquiaga, J. M., Fabrizi, F., Faedi, F., Fafone, V., Fairhurst, S., Fan, P. C., Farah, A. M., Farr, B., Farr, W. M., Favaro, G., Favata, M., Fays, M., Fazio, M., Feicht, J., Fejer, M. M., Fenyvesi, E., Ferguson, D. L., Ferrante, I., Ferreira, T. A., Fidecaro, F., Fiori, A., Fiori, I., Fishbach, M., Fisher, R. P., Fittipaldi, R., Fiumara, V., Flaminio, R., Fleischer, S. M., Fleming, L. S., Floden, E., Foley, E. M., Fong, H., Font, J. A., Fornal, B., Forsyth, P. W. F., Franceschetti, K., Franchini, N., Frasca, S., Frasconi, F., Mascioli, A. Frattale, Frei, Z., Freise, A., Freitas, O., Frey, R., Frischhertz, W., Frolov, V. V., Fronzé, G. G., Fuentes-Garcia, M., Fujii, S., Fukunaga, I., Fulda, P., Fyffe, M., Gabella, W. E., Gadre, B., Gair, J. R., Galaudage, S., Gallardo, S., Gallego, B., Gamba, R., Gamboa, A., Ganapathy, D., Ganguly, A., Gaonkar, S. G., Garaventa, B., Garcia-Bellido, J., García-Núñez, C., García-Quirós, C., Gardner, J. W., Gardner, K. A., Gargiulo, J., Garron, A., Garufi, F., Gasbarra, C., Gateley, B., Gayathri, V., Gemme, G., Gennai, A., George, J., George, R., Gerberding, O., Gergely, L., Ghadiri, N., Ghosh, Archisman, Ghosh, Shaon, Ghosh, Shrobana, Ghosh, Suprovo, Ghosh, Tathagata, Giacoppo, L., Giaime, J. A., Giardina, K. D., Gibson, D. R., Gibson, D. T., Gier, C., Giri, P., Gissi, F., Gkaitatzis, S., Glanzer, J., Gleckl, A. E., Glotin, F., Godfrey, J., Godwin, P., Goebbels, N. L., Goetz, E., Golomb, J., Lopez, S. Gomez, Goncharov, B., González, G., Goodarzi, P., Goodwin-Jones, A. W., Gosselin, M., Göttel, A. S., Gouaty, R., Gould, D. W., Goyal, S., Grace, B., Grado, A., Graham, V., Granados, A. E., Granata, M., Granata, V., Argianas, L. Granda, Gras, S., Grassia, P., Gray, C., Gray, R., Greco, G., Green, A. C., Green, S. M., Green, S. R., Gretarsson, A. M., Gretarsson, E. M., Griffith, D., Griffiths, W. L., Griggs, H. L., Grignani, G., Grimaldi, A., Grimaud, C., Grote, H., Gruson, A. S., Guerra, D., Guetta, D., Guidi, G. M., Guimaraes, A. R., Gulati, H. K., Gulminelli, F., Gunny, A. M., Guo, H., Guo, W., Guo, Y., Gupta, Anchal, Gupta, Anuradha, Gupta, Ish, Gupta, N. C., Gupta, P., Gupta, S. K., Gupta, T., Gupte, N., Gurav, R., Gurs, J., Gutierrez, N., Guzman, F., Haba, D., Haberland, M., Haegel, L., Hain, G., Haino, S., Hall, E. D., Hamilton, E. Z., Hammond, G., Han, W. -B., Haney, M., Hanks, J., Hanna, C., Hannam, M. D., Hannuksela, O. A., Hanselman, A. G., Hansen, H., Hanson, J., Harada, R., Harder, T., Haris, K., Harmark, T., Harms, J., Harry, G. M., Harry, I. W., Haskell, B., Haster, C. -J., Hathaway, J. S., Haughian, K., Hayakawa, H., Hayama, K., Healy, J., Heffernan, A., Heidmann, A., Heintze, M. C., Heinze, J., Heinzel, J., Heitmann, H., Hellman, F., Hello, P., Helmling-Cornell, A. F., Hemming, G., Hendry, M., Heng, I. S., Hennes, E., Hennig, J. -S., Hennig, M., Henshaw, C., Hernandez, A., Hertog, T., Heurs, M., Hewitt, A. L., Higginbotham, S., Hild, S., Hill, P., Hill, S., Himemoto, Y., Hines, A. S., Hirata, N., Hirose, C., Ho, J., Hoang, S., Hochheim, S., Hofman, D., Holland, N. A., Holley-Bockelmann, K., Hollows, I. J., Holmes, Z. J., Holz, D. E., Hong, C., Hornung, J., Hoshino, S., Hourihane, S., Howell, E. J., Hoy, C. G., Hoyland, D., Hrishikesh, C. A., Hsieh, H. -F., Hsiung, C., Hsu, H. C., Hsu, S. -C., Hsu, W. -F., Hu, P., Hu, Q., Huang, H. Y., Huang, Y. -J., Huang, Y., Huang, Y. T., Huddart, A. D., Hughey, B., Hui, D. 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Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, General Relativity and Quantum Cosmology, High Energy Physics - Phenomenology
Abstract: Among the various candidates for dark matter (DM), ultralight vector DM can be probed by laser interferometric gravitational wave detectors through the measurement of oscillating length changes in the arm cavities. In this context, KAGRA has a unique feature due to differing compositions of its mirrors, enhancing the signal of vector DM in the length change in the auxiliary channels. Here we present the result of a search for $U(1)_{B-L}$ gauge boson DM using the KAGRA data from auxiliary length channels during the first joint observation run together with GEO600. By applying our search pipeline, which takes into account the stochastic nature of ultralight DM, upper bounds on the coupling strength between the $U(1)_{B-L}$ gauge boson and ordinary matter are obtained for a range of DM masses. While our constraints are less stringent than those derived from previous experiments, this study demonstrates the applicability of our method to the lower-mass vector DM search, which is made difficult in this measurement by the short observation time compared to the auto-correlation time scale of DM., Comment: 20 pages, 5 figures
Published: 2024

42. Retinal Dystrophies Associated With Peripherin-2: Genetic Spectrum and Novel Clinical Observations in 241 Patients.

Author: Heath Jeffery, Rachael, Thompson, Jennifer, Lo, Johnny, Chelva, Enid, Armstrong, Sean, Pulido, Jose, Procopio, Rebecca, Vincent, Andrea, Bianco, Lorenzo, Battaglia Parodi, Maurizio, Ziccardi, Lucia, Antonelli, Giulio, Barbano, Lucilla, Marques, João, Geada, Sara, Carvalho, Ana, Tang, Wei, Chan, Choi, Boon, Camiel, Hensman, Jonathan, Chen, Ta-Ching, Lin, Chien-Yu, Chen, Pei-Lung, Vincent, Ajoy, Tumber, Anupreet, Heon, Elise, Grigg, John, Jamieson, Robyn, Cornish, Elisa, Nash, Benjamin, Borooah, Shyamanga, Ayton, Lauren, Britten-Jones, Alexis, Edwards, Thomas, Ruddle, Jonathan, Sharma, Abhishek, Porter, Rowan, Lamey, Tina, McLaren, Terri, McLenachan, Samuel, Roshandel, Danial, and Chen, Fred
Subjects: Humans, Peripherins, Middle Aged, Adult, Male, Female, Adolescent, Retinal Dystrophies, Aged, Visual Acuity, Child, Young Adult, Electroretinography, Child, Preschool, Phenotype, Tomography, Optical Coherence, Mutation, Fluorescein Angiography, Genetic Association Studies, Retrospective Studies, DNA Mutational Analysis, DNA, Pedigree
Abstract: PURPOSE: To describe the clinical, electrophysiological and genetic spectrum of inherited retinal diseases associated with variants in the PRPH2 gene. METHODS: A total of 241 patients from 168 families across 15 sites in 9 countries with pathogenic or likely pathogenic variants in PRPH2 were included. Records were reviewed for age at symptom onset, visual acuity, full-field ERG, fundus colour photography, fundus autofluorescence (FAF), and SD-OCT. Images were graded into six phenotypes. Statistical analyses were performed to determine genotype-phenotype correlations. RESULTS: The median age at symptom onset was 40 years (range, 4-78 years). FAF phenotypes included normal (5%), butterfly pattern dystrophy, or vitelliform macular dystrophy (11%), central areolar choroidal dystrophy (28%), pseudo-Stargardt pattern dystrophy (41%), and retinitis pigmentosa (25%). Symptom onset was earlier in retinitis pigmentosa as compared with pseudo-Stargardt pattern dystrophy (34 vs 44 years; P = 0.004). The median visual acuity was 0.18 logMAR (interquartile range, 0-0.54 logMAR) and 0.18 logMAR (interquartile range 0-0.42 logMAR) in the right and left eyes, respectively. ERG showed a significantly reduced amplitude across all components (P < 0.001) and a peak time delay in the light-adapted 30-Hz flicker and single-flash b-wave (P < 0.001). Twenty-two variants were novel. The central areolar choroidal dystrophy phenotype was associated with 13 missense variants. The remaining variants showed marked phenotypic variability. CONCLUSIONS: We described six distinct FAF phenotypes associated with variants in the PRPH2 gene. One FAF phenotype may have multiple ERG phenotypes, demonstrating a discordance between structure and function. Given the vast spectrum of PRPH2 disease our findings are useful for future clinical trials.
Published: 2024

43. 2D photonic-crystal-type surface relief grating for light with an azimuth angle

Author: Hsiao, Fu-Li, Lin, Chien-Teng, Yang, Yen-Tung, Huang, Yi-Chia, Yu, Li-Chuan, and Tsai, Ying-Pin
Published: 2024
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44. Risk, Predictive, and Preventive Factors for Noninfectious Ventriculitis and External Ventricular Drain Infection

Author: Huang, Tzu-Fen, Su, Yu-Kai, Su, I-Chang, Yeh, Yun-Kai, Liu, Heng-Wei, Kan, I-Hung, Lu, Yu-Chun, Chang, Yu-Pei, Lin, Chien-Min, Tu, Yong-Kwang, and Tseng, Chien-Hua
Published: 2024
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45. Effects of Stair-Climbing Exercise on Health-Related Physical Fitness Measures in Children with Developmental Disabilities

Author: Wen-Li, Lin, Lin, Chien-Lin, and Lin, Chin-Kai
Published: 2024
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46. Estrogen-related receptor alpha promotes thyroid tumor cell survival via a tumor subtype-specific regulation of target gene networks

Author: Chen, Wenjing, Song, Young Shin, Lee, Han Sai, Lin, Chien-Wei, Lee, Junguee, Kang, Yea Eun, Kim, Seon-Kyu, Kim, Seon-Young, Park, Young Joo, and Park, Jong-In
Published: 2024
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47. Dynamic response of bidirectional functionally graded beams with elastic supports and foundations under moving harmonic loads

Author: Chen, Wei-Ren and Lin, Chien-Hung
Published: 2024
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48. Early Therapeutic Drug Monitoring Optimizes Teicoplanin Use in Febrile Neutropenic Patients with Hematological Malignancies

Author: Wang, Yu-Wen, Hou, Hsin-An, Lin, Chien-Chin, Lin, Hsing-Yu, Chen, Pin-Zi, Kuo, Ching-Hua, Chiu, Huai-Hsuan, Chuang, Chia-Chi, Chen, Yi-Jing, and Lin, Shu-Wen
Published: 2024
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49. CROCuS, a Phase II Study Evaluating the Antiviral Activity, Clinical Outcomes, and Safety of Rilematovir in Children Aged ≥ 28 Days and ≤ 3 Years with Acute Respiratory Tract Infection Due to Respiratory Syncytial Virus

Author: Ferrero, Fernando, Lin, Chien-Yu, Liese, Johannes, Luz, Kleber, Stoeva, Tatyana, Nemeth, Agnes, Gijón, Manuel, Calvo, Cristina, Natalini, Silvina, Toh, Teck-Hock, Deleu, Sofie, Chen, Bohang, Rusch, Sarah, Sánchez, Beatriz López, Leipoldt, Illse, Vijgen, Leen, Huntjens, Dymphy, Baguet, Tristan, Bertzos, Kristi, Gamil, Mohamed, and Stevens, Marita
Published: 2024
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50. FastSR-NeRF: Improving NeRF Efficiency on Consumer Devices with A Simple Super-Resolution Pipeline

Author: Lin, Chien-Yu, Fu, Qichen, Merth, Thomas, Yang, Karren, and Ranjan, Anurag
Subjects: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Graphics
Abstract: Super-resolution (SR) techniques have recently been proposed to upscale the outputs of neural radiance fields (NeRF) and generate high-quality images with enhanced inference speeds. However, existing NeRF+SR methods increase training overhead by using extra input features, loss functions, and/or expensive training procedures such as knowledge distillation. In this paper, we aim to leverage SR for efficiency gains without costly training or architectural changes. Specifically, we build a simple NeRF+SR pipeline that directly combines existing modules, and we propose a lightweight augmentation technique, random patch sampling, for training. Compared to existing NeRF+SR methods, our pipeline mitigates the SR computing overhead and can be trained up to 23x faster, making it feasible to run on consumer devices such as the Apple MacBook. Experiments show our pipeline can upscale NeRF outputs by 2-4x while maintaining high quality, increasing inference speeds by up to 18x on an NVIDIA V100 GPU and 12.8x on an M1 Pro chip. We conclude that SR can be a simple but effective technique for improving the efficiency of NeRF models for consumer devices., Comment: WACV 2024 (Oral)
Published: 2023

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