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2. More than a piece of cake: Noun classifier processing in primary progressive aphasia

Author

Tee, Boon Lead, Li‐Ying, Lorinda Kwan‐Chen, Chen, Ta‐Fu, Yan, Connie TY, Tsoh, Joshua, Chan, Andrew Lung‐Tat, Wong, Adrian, Lo, Raymond Y, Lu, Chien Jung, Sun, Yu, Wang, Pei‐Ning, Lee, YiChen, Chiu, Ming‐Jang, Allen, Isabel Elaine, Battistella, Giovanni, Bak, Thomas H, Chuang, Yu‐Chen, García, Adolfo M, and Gorno‐Tempini, Maria Luisa

Subjects
Biological Psychology, Cognitive and Computational Psychology, Psychology, Frontotemporal Dementia (FTD), Neurodegenerative, Brain Disorders, Dementia, Clinical Research, Aphasia, Aging, Acquired Cognitive Impairment, 2.1 Biological and endogenous factors, Aetiology, Humans, Aphasia, Primary Progressive, Language, Gray Matter, Cerebral Cortex, Chinese language, lemma, lexical syntactic attributes, noun classifier, primary progressive aphasia, Clinical Sciences, Neurosciences, Geriatrics, Clinical sciences, Biological psychology
Abstract

IntroductionClinical understanding of primary progressive aphasia (PPA) has been primarily derived from Indo-European languages. Generalizing certain linguistic findings across languages is unfitting due to contrasting linguistic structures. While PPA patients showed noun classes impairments, Chinese languages lack noun classes. Instead, Chinese languages are classifier language, and how PPA patients manipulate classifiers is unknown.MethodsWe included 74 native Chinese speakers (22 controls, 52 PPA). For classifier production task, participants were asked to produce the classifiers of high-frequency items. In a classifier recognition task, participants were asked to choose the correct classifier.ResultsBoth semantic variant (sv) PPA and logopenic variant (lv) PPA scored significantly lower in classifier production task. In classifier recognition task, lvPPA patients outperformed svPPA patients. The classifier production scores were correlated to cortical volume over left temporal and visual association cortices.DiscussionThis study highlights noun classifiers as linguistic markers to discriminate PPA syndromes in Chinese speakers.HighlightsNoun classifier processing varies in the different primary progressive aphasia (PPA) variants. Specifically, semantic variant PPA (svPPA) and logopenic variant PPA (lvPPA) patients showed significantly lower ability in producing specific classifiers. Compared to lvPPA, svPPA patients were less able to choose the accurate classifiers when presented with choices. In svPPA, classifier production score was positively correlated with gray matter volume over bilateral temporal and left visual association cortices in svPPA. Conversely, classifier production performance was correlated with volumetric changes over left ventral temporal and bilateral frontal regions in lvPPA. Comparable performance of mass and count classifier were noted in Chinese PPA patients, suggesting a common cognitive process between mass and count classifiers in Chinese languages.

Published
2024

3. Do Satisfied Visitors Intend to Revisit a Large Sports Event? A Case Study of a Large Sports Event In Indonesia

Author

Pahrudin Pahrudin, Wang Chia-Chun, Liu Li-Wei, Lu Chien, and Hak Muhamad Bai’ul

Subjects
intention to revisit, satisfaction, sports event, motogp, indonesia, Sports, GV557-1198.995
Abstract

Only a few studies on large sports tourism explore motorsport events such as the Moto Grand Prix. The present study addresses this gap by examining the factors influencing visitors’ satisfaction and intention to revisit related to the large sports event of MotoGP, Indonesia. The data were collected from visitors who had attended the MotoGP event in Indonesia using an online questionnaire with purposive sampling. The partial Least Square-Structural Equation Modeling (PLS-SEM) analysis was applied in this study to analyze the data. The findings indicate that hospitality, accessibility, and attraction significantly influenced visitor satisfaction at the MotoGP sports event in Mandalika, Indonesia. However, the factors of hospitality, infrastructure, accessibility, and attraction are insignificant where it concerns visitors’ intention to revisit. Moreover, satisfaction successfully influences visitors to revisit the MotoGP event in Indonesia. This study contributes to research on sports event management in large sports events by examining the factors that influence satisfaction and intention to revisit in the context of the MotoGP sports event, and contributes both theoretically and practically to research on sports events and tourism.

Published
2024
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6. Disparities in medical recommendations from AI-based chatbots across different countries/regions

Author

Gumilar, Khanisyah E., Indraprasta, Birama R., Hsu, Yu-Cheng, Yu, Zih-Ying, Chen, Hong, Irawan, Budi, Tambunan, Zulkarnain, Wibowo, Bagus M., Nugroho, Hari, Tjokroprawiro, Brahmana A., Dachlan, Erry G., Mulawardhana, Pungky, Rahestyningtyas, Eccita, Pramuditya, Herlangga, Putra, Very Great E., Waluyo, Setyo T., Tan, Nathan R., Folarin, Royhaan, Ibrahim, Ibrahim H., Lin, Cheng-Han, Hung, Tai-Yu, Lu, Ting-Fang, Chen, Yen-Fu, Shih, Yu-Hsiang, Wang, Shao-Jing, Huang, Jingshan, Yates, Clayton C., Lu, Chien-Hsing, Liao, Li-Na, and Tan, Ming

Published
2024
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8. Embraceable Virtual Paws: Player Experiences in Animal Shelter Simulator

Author

Lu, Chien, Hassan, Lobna, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Vale Costa, Liliana, editor, Zagalo, Nelson, editor, Veloso, Ana Isabel, editor, Clua, Esteban, editor, Arnab, Sylvester, editor, Vairinhos, Mário, editor, and Gomes, Diogo, editor

Published
2024
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14. Assessment of Large Language Models (LLMs) in decision-making support for gynecologic oncology

Author

Gumilar, Khanisyah Erza, Indraprasta, Birama R., Faridzi, Ach Salman, Wibowo, Bagus M., Herlambang, Aditya, Rahestyningtyas, Eccita, Irawan, Budi, Tambunan, Zulkarnain, Bustomi, Ahmad Fadhli, Brahmantara, Bagus Ngurah, Yu, Zih-Ying, Hsu, Yu-Cheng, Pramuditya, Herlangga, Putra, Very Great E., Nugroho, Hari, Mulawardhana, Pungky, Tjokroprawiro, Brahmana A., Hedianto, Tri, Ibrahim, Ibrahim H., Huang, Jingshan, Li, Dongqi, Lu, Chien-Hsing, Yang, Jer-Yen, Liao, Li-Na, and Tan, Ming

Published
2024
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22. Dysgraphia Phenotypes in Native Chinese Speakers With Primary Progressive Aphasia

Author

Tee, Boon Lead, Lorinda Kwan-Chen, Li Ying, Chen, Ta-Fu, Yan, Connie TY, Tsoh, Joshua, Lung-Tat Chan, Andrew, Wong, Adrian, Lo, Raymond Y, Lu, Chien Long, Wang, Pei-Ning, Lee, YiChen, Yang, Fanpei G, Battistella, Giovanni, Allen, Isabel Elaine, Dronkers, Nina F, Miller, Bruce L, and Gorno-Tempini, Maria Luisa

Subjects
Biomedical and Clinical Sciences, Neurosciences, Clinical Sciences, Rare Diseases, Dementia, Brain Disorders, Acquired Cognitive Impairment, Aging, Neurodegenerative, Aphasia, Frontotemporal Dementia (FTD), Agraphia, Aphasia, Primary Progressive, China, Humans, Language, Phenotype, Primary Progressive Nonfluent Aphasia, Cognitive Sciences, Neurology & Neurosurgery, Clinical sciences
Abstract

Background and objectivesMost primary progressive aphasia (PPA) literature is based on English language users. Linguistic features that vary from English, such as logographic writing systems, are underinvestigated. The current study characterized the dysgraphia phenotypes of patients with PPA who write in Chinese and investigated their diagnostic utility in classifying PPA variants.MethodsThis study recruited 40 participants with PPA and 20 cognitively normal participants from San Francisco, Hong Kong, and Taiwan. We measured dictation accuracy using the Chinese Language Assessment for PPA (CLAP) 60-character orthographic dictation test and examined the occurrence of various writing errors across the study groups. We also performed voxel-based morphometry analysis to identify the gray matter regions correlated with dictation accuracy and prevalence of writing errors.ResultsAll PPA groups produced significantly less accurate writing responses than the control group and no significant differences in dictation accuracy were noted among the PPA variants. With a cut score of 36 out of 60 in the CLAP orthographic dictation task, the test achieved sensitivity and specificity of 90% and 95% in identifying Chinese participants with PPA vs controls. In addition to a character frequency effect, dictation accuracy was affected by homophone density and the number of strokes in semantic variant PPA and logopenic variant PPA groups. Dictation accuracy was correlated with volumetric changes over left ventral temporal cortices, regions known to be critical for orthographic long-term memory. Individuals with semantic variant PPA frequently presented with phonologically plausible errors at lexical level, patients with logopenic variant PPA showed higher preponderance towards visual and stroke errors, and patients with nonfluent/agrammatic variant PPA commonly exhibited compound word and radical errors. The prevalence of phonologically plausible, visual, and compound word errors was negatively correlated with cortical volume over the bilateral temporal regions, left temporo-occipital area, and bilateral orbitofrontal gyri, respectively.DiscussionThe findings demonstrate the potential role of the orthographic dictation task as a screening tool and PPA classification indicator in Chinese language users. Each PPA variant had specific Chinese dysgraphia phenotypes that vary from those previously reported in English-speaking patients with PPA, highlighting the importance of language diversity in PPA.

Published
2022

24. Comparing Low- or Standard-Dose Alteplase in Endovascular Thrombectomy: Insights From a Nationwide Registry

Author

Chen, Chih-Hao, Lee, Chung-Wei, Hsieh, Yi-Chen, Lin, Chun-Jen, Chen, Yu-Wei, Lin, Kuan-Hung, Sung, Pi-Shan, Tang, Chih-Wei, Chu, Hai-Jui, Tsai, Kun-Chang, Chou, Chao-Liang, Lin, Ching-Huang, Wei, Cheng-Yu, Yen, Shang-Yih, Chen, Po-Lin, Yeh, Hsu-Ling, Chan, Lung, Sung, Sheng-Feng, Lee, Meng, Liu, Hon-Man, Lin, Yen-Heng, Lee, I-Hui, Yeh, Shin-Joe, Lien, Li-Ming, Chiou, Hung-Yi, Lee, Jiunn-Tay, Tang, Sung-Chun, Jeng, Jiann-Shing, Tang, Sung-Chun, Jeng, Jiann-Shing, Lee, Chung-Wen, Chen, Chih-Hao, Lin, Yen-Heng, Yeh, Shin-Joe, Lee, Bo-Ching, Chung, Tai-Chun, Lin, Chun-Jen, Lee, I-Hui, Chi, Nai-Fang, Hsu, Li-Chi, Chung, Chih-Ping, Liu, Hung-Yu, Luo, Chao-Bao, Chang, Feng-Chi, Lin, Chung-Jung, Wu, Chia-Hung, Yu, Kai-Wei, Hwang, Hsuen-En, Lin, Te-Ming, Chen, Yu-Wei, Chen, Chi-Jen, Wang, Ching-Yi, Kuo, Yeh-Lin, Lu, Ping-Sheng, Chao, Yen-Tung, Su, Yi-Hsin, Lin, Pei-Ju, Chen, Yi-Chun, Fan, Li-Ling, Yang, Ju-Fang, Lin, Kuan-Hung, Lin, Chien-Jen, Yang, Sheng-Hsiang, Yang, Chun-Ming, Lin, Huey-Juan, Yeh, Poh-Shiow, Chang, Chia-Yu, Cheng, Tian-Junn, Lee, Wei-Jia, Ko, Ching-Chung, Tsui, Yu-Kun, Shih, Yun-Ju, Wu, Te-Chang, Sung, Pi-Shan, Chang Chun-Min Wang, Yu-Ming, Huang, Chih-Yuan, Chen, Chih-Hung, Hsieh, Meng-Tsang, Ou, Chang-Hsien, Lin, Wan-Ching, Chen, Li-Ching, Ann, Bi-Shin, Tang, Chih-Wei, Lai, Yen-Jun, Huang, Lih-Wen, Kuo, Ya-Ling, Peng, Szu-Hsiang, Pai Lin, Yi-Chun, Chu, Hai-Jui, Lin, Cheng-Huai, Sun, Yu, Lu, Chien-Jung, Lee, Chun-Yu, Liu, Chang-Hsiu, Tsai, Kun-Chang, Chen, Kuo-Wei, Tsai, Li-Kai, Hsiue, Yen-Chung, Cheng, Ya-Wen, Fu, Chuan-Hsiu, Chen, Wen-Yu, Chou, Chao-Liang, Po, Helen L., Lin, Ya-Ju, Hwang, Yung-Pin, Kuo, Shu-Fan, Huang, Chun-Chao, Jhou, Zong-Yi, Yu, Hui-Fen, Lin, Hsiao-Chu, Wei, Cheng-Yu, Chen, Chih-Lin, Wu, Pei-han, Tsai, Yi-Ching, Yen, Shang-Yih, Lee, Jiunn-tay, Chou, Chung-Hsing, Ko, Chien-An, Chen, Po-Lin, Tsuei, Yuang-Seng, Chen, Wen-Hsien, Liao, Nien-Chen, Liaw, Yeng-Fung, Yeh, Hsu-Ling, Lien, Li-Ming, Hsiao, Chen-Yu, Lin, Kuan-Yu, Yang, Tsui-Hua, Chan, Lung, Chen, Jia-Hung, Yu, Shun-Fan, Su, I-Chang, Lu, Yueh-Hsun, Sung, Sheng-Feng, Yang, Tzu-Hsien, Hsu, Yung-Chu, Su, Yu-Hsiang, Hung, Ling-Chien, Lin, Mao-Hsun, Su, Chien-Yu, Liu, Hon-Man, Huang, Yung-Chuan, Wan, Chih-Cheng, Lin, Ching-Huang, Yen, Cheng- Chang, Shih, Ching-Sen, Lin, Chun-Shien, Lee, Meng, Tsai, Yuan-Hsiung, Huang, Yen-Chu, Hung, Wei-Tse, and Lee, Jiann-Der

Published
2024
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26. CryptoKitties vs. Axie Infinity: Computational Analysis of NFT Game Reddit Discussions

Author

Lu, Chien, Lauritano, Giacomo, Peltonen, Jaakko, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin, Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, and Brooks, Anthony L., editor

Published
2023
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35. Knowledge Distillation with Feature Maps for Image Classification

Author

Chen, Wei-Chun, Chang, Chia-Che, Lu, Chien-Yu, and Lee, Che-Rung

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition
Abstract

The model reduction problem that eases the computation costs and latency of complex deep learning architectures has received an increasing number of investigations owing to its importance in model deployment. One promising method is knowledge distillation (KD), which creates a fast-to-execute student model to mimic a large teacher network. In this paper, we propose a method, called KDFM (Knowledge Distillation with Feature Maps), which improves the effectiveness of KD by learning the feature maps from the teacher network. Two major techniques used in KDFM are shared classifier and generative adversarial network. Experimental results show that KDFM can use a four layers CNN to mimic DenseNet-40 and use MobileNet to mimic DenseNet-100. Both student networks have less than 1\% accuracy loss comparing to their teacher models for CIFAR-100 datasets. The student networks are 2-6 times faster than their teacher models for inference, and the model size of MobileNet is less than half of DenseNet-100's., Comment: Knowledge Distillation, Model Compression, and Generative Adversarial Network, ACCV 2018

Published
2018

41. A non-comparative, randomized, phase II trial of atezolizumab or atezolizumab plus tiragolumab for programmed death-ligand 1-positive recurrent cervical cancer (SKYSCRAPER-04)

Author

Salani, Ritu, primary, McCormack, Mary, additional, Kim, Yong-Man, additional, Ghamande, Sharad, additional, Hall, Shaundra L, additional, Lorusso, Domenica, additional, Barraclough, Lisa, additional, Gilbert, Lucy, additional, Guzman Ramirez, Adrian, additional, Lu, Chien-Hsing, additional, Sabatier, Renaud, additional, Colombo, Nicoletta, additional, Hu, Youyou, additional, Krishnan, Venkatesh, additional, Molinero, Luciana, additional, Feng, Yuning, additional, Kim, Nicole, additional, Castro, Marcela, additional, Lin, Yvonne G, additional, and Monk, Bradley J, additional

Published
2024
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43. Play as You Like: Timbre-enhanced Multi-modal Music Style Transfer

Author

Lu, Chien-Yu, Xue, Min-Xin, Chang, Chia-Che, Lee, Che-Rung, and Su, Li

Subjects
Computer Science - Sound, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

Style transfer of polyphonic music recordings is a challenging task when considering the modeling of diverse, imaginative, and reasonable music pieces in the style different from their original one. To achieve this, learning stable multi-modal representations for both domain-variant (i.e., style) and domain-invariant (i.e., content) information of music in an unsupervised manner is critical. In this paper, we propose an unsupervised music style transfer method without the need for parallel data. Besides, to characterize the multi-modal distribution of music pieces, we employ the Multi-modal Unsupervised Image-to-Image Translation (MUNIT) framework in the proposed system. This allows one to generate diverse outputs from the learned latent distributions representing contents and styles. Moreover, to better capture the granularity of sound, such as the perceptual dimensions of timbre and the nuance in instrument-specific performance, cognitively plausible features including mel-frequency cepstral coefficients (MFCC), spectral difference, and spectral envelope, are combined with the widely-used mel-spectrogram into a timber-enhanced multi-channel input representation. The Relativistic average Generative Adversarial Networks (RaGAN) is also utilized to achieve fast convergence and high stability. We conduct experiments on bilateral style transfer tasks among three different genres, namely piano solo, guitar solo, and string quartet. Results demonstrate the advantages of the proposed method in music style transfer with improved sound quality and in allowing users to manipulate the output.

Published
2018

44. Mutations in the PKM2 exon-10 region are associated with reduced allostery and increased nuclear translocation

Author

Chen, Tsan-Jan, Wang, Hung-Jung, Liu, Jai-Shin, Cheng, Hsin-Hung, Hsu, Sheng-Chieh, Wu, Meng-Chen, Lu, Chien-Hung, Wu, Yu-Fang, Wu, Jing-Wen, Liu, Ying-Yuan, Kung, Hsing-Jien, and Wang, Wen-Ching

Subjects
Cancer, Genetics, Aetiology, 2.1 Biological and endogenous factors, Active Transport, Cell Nucleus, Allosteric Regulation, Carrier Proteins, Exons, Histone Demethylases, Humans, Immunohistochemistry, Membrane Proteins, Models, Molecular, Mutation, Neoplasms, Protein Conformation, Thyroid Hormones
Abstract

PKM2 is a key metabolic enzyme central to glucose metabolism and energy expenditure. Multiple stimuli regulate PKM2's activity through allosteric modulation and post-translational modifications. Furthermore, PKM2 can partner with KDM8, an oncogenic demethylase and enter the nucleus to serve as a HIF1α co-activator. Yet, the mechanistic basis of the exon-10 region in allosteric regulation and nuclear translocation remains unclear. Here, we determined the crystal structures and kinetic coupling constants of exon-10 tumor-related mutants (H391Y and R399E), showing altered structural plasticity and reduced allostery. Immunoprecipitation analysis revealed increased interaction with KDM8 for H391Y, R399E, and G415R. We also found a higher degree of HIF1α-mediated transactivation activity, particularly in the presence of KDM8. Furthermore, overexpression of PKM2 mutants significantly elevated cell growth and migration. Together, PKM2 exon-10 mutations lead to structure-allostery alterations and increased nuclear functions mediated by KDM8 in breast cancer cells. Targeting the PKM2-KDM8 complex may provide a potential therapeutic intervention.

Published
2019

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