Nanomaterials for Biomedical Application / by Mohd. Hayrie Mohd. Hatta, 1989-, editor 498358, Nik Ahmad Nizam Nik Malek, editor 614732, Mohd. Hayrie Mohd. Hatta, 1989-, contributor 498358, Nik Ahmad Nizam Nik Malek, contributor 614732, Abdulrahman Sani Aliero, contributor 655585, Abilasha Chandran, contributor 655586, Aishah Badruzzaman, contributor 444732, Farah Hidayah Kamisan, contributor 655587, Fatin Hasinah Marzoki, contributor 655588, Ho, Helen Hsin Yee, contributor 655595, Juan Matmin, contributor 387222, Khairunadwa Jemon, contributor 601214, Madhu Meetha Thiruchelvan, contributor 655596, Nazirah Amran, contributor 655589, Noor Alyanis Farhaida Mohd Zainon, 1993-, contributor 646213, Nur Shafeera Mohamad, 1992-, contributor 638062, Nur Syafiqa Syahida Sakrani, contributor 655590, Nurhidayah Aripin, 1987-, contributor 547607, Nurliyana Ahmad Zawawi, contributor 639915, Nurul Syuhadah Muhammad Tamrin, contributor 655591, Praseetha Prabhakaran, contributor 270598, Rukkumani Kumaran, contributor 655598, Sharel Raj, contributor 655599, Sharmala Devi Sivenyanam, contributor 655597, Siew Ling Lee, contributor 605851, Siti Hajar Mokri, contributor 655592, Wan Fatin Amira Wan Mohd. Zawawi, 1992-, contributor 639678, Wong, Ker Thi, contributor 655593, Wong, Sru Thi, contributor 655594

Roadmap on energy harvesting materials by Pecunia, Vincenzo, Silva, S Ravi P, Phillips, Jamie D., Artegiani, Elisa, Romeo, Alessandro, Shim, Hongjae, Park, Jongsung, Kim, Jin Hyeok, Yun, Jae Sung, Welch, Gregory C., Larson, Bryon W., Creran, Myles, Laventure, Audrey, Sasitharan, Kezia, Flores-Diaz, Natalie, Freitag, Marina, Xu, Jie, Brown, Thomas M., Li, Benxuan, Wang, Yiwen, Li, Zhe, Hou, Bo, Hamadani, Behrang H., Defay, Emmanuel, Kovacova, Veronika, Glinsek, Sebastjan, Kar-Narayan, Sohini, Bai, Yang, Kim, Da Bin, Cho, Yong Soo, Žukauskaitė, Agnė, Barth, Stephan, Fan, Feng Ru, Wu, Wenzhuo, Costa, Pedro, del Campo, Javier, Lanceros-Mendez, Senentxu, Khanbareh, Hamideh, Wang, Zhong Lin, Pu, Xiong, Pan, Caofeng, Zhang, Renyun, Xu, Jing, Zhao, Xun, Zhou, Yihao, Chen, Guorui, Tat, Trinny, Ock, Il Woo, Chen, Jun, Graham, Sontyana Adonijah, Yu, Jae Su, Huang, Ling-Zhi, Li, Dan-Dan, Ma, Ming-Guo, Luo, Jikui, Jiang, Feng, Lee, Pooi See, Dudem, Bhaskar, Vivekananthan, Venkateswaran, Kanatzidis, Mercouri G., Xie, Hongyao, Shi, Xiao-Lei, Chen, Zhi-Gang, Riss, Alexander, Parzer, Michael, Garmroudi, Fabian, Bauer, Ernst, Zavanelli, Duncan, Brod, Madison K., Malki, Muath Al, Snyder, G. Jeffrey, Kovnir, Kirill, Kauzlarich, Susan M., Uher, Ctirad, Lan, Jinle, Lin, Yuan-Hua, Fonseca, Luis, Morata, Alex, Martin-Gonzalez, Marisol, Pennelli, Giovanni, Berthebaud, David, Mori, Takao, Quinn, Robert J., Bos, Jan-Willem G., Candolfi, Christophe, Gougeon, Patrick, Gall, Philippe, Lenoir, Bertrand, Venkateshvaran, Deepak, Kaestner, Bernd, Zhao, Yunshan, Zhang, Gang, Nonoguchi, Yoshiyuki, Schroeder, Bob C., Bilotti, Emiliano, Menon, Akanksha K., Urban, Jeffrey J., Fenwick, Oliver, Asker, Ceyla, Talin, A. Alec, Anthopoulos, Thomas D., Losi, Tommaso, Viola, Fabrizio, Caironi, Mario, Georgiadou, Dimitra G., Ding, Li, Peng, Lian-Mao, Wang, Zhenxing, Wei, Muh-Dey, Negra, Renato, Lemme, Max C., Wagih, Mahmoud, Beeby, Steve, Ibn-Mohammed, Taofeeq, Mustapha, K. B., Joshi, A. P.

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Dated by Ho, Jia Fen

“…Dated is a 2D hand drawn animation film done by Tan Ping Hao, Melissa Sing, Wang Jia Ying and myself. …”
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Modeling distance-dependent individual head-related transfer functions in the horizontal plane using frontal projection headphones by Sunder, Kaushik, Gan, Woon-Seng, Tan, Ee-Leng

“…Soc. 61, 989–1000] project the sound directly onto the pinnae from the front, and thus inherently create listener's idiosyncratic pinna cues at the eardrum. …”
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Use of large language models as artificial intelligence tools in academic research and publishing among global clinical researchers by Mishra, T, Sutanto, E, Rossanti, R, Pant, N, Ashraf, A, Raut, A, Uwabareze, G, Oluwatomiwa, A, Zeeshan, B

“…Majority (57.5%) of these participants practiced in an academic setting with a median of 7 (2,18) PubMed Indexed published articles. 198 respondents (87.6%) were aware of LLMs and those who were aware had higher number of publications (p < 0.001). 18.7% of the respondents who were aware (n = 37) had previously used LLMs in publications especially for grammatical errors and formatting (64.9%); however, most (40.5%) did not acknowledge its use in their papers. 50.8% of aware respondents (n = 95) predicted an overall positive future impact of LLMs while 32.6% were unsure of its scope. 52% of aware respondents (n = 102) believed that LLMs would have a major impact in areas such as grammatical errors and formatting (66.3%), revision and editing (57.2%), writing (57.2%) and literature review (54.2%). 58.1% of aware respondents were opined that journals should allow for use of AI in research and 78.3% believed that regulations should be put in place to avoid its abuse. …”

Survey on inadequate and omitted citations in manuscripts: a precursory study in identification of tasks for a literature review and manuscript writing assistive system by Sesagiri Raamkumar, Aravind, Foo, Schubert, Pang, Natalie

“…Reviewer and author groups opined that manuscript authors fail to cite seminal and topically-similar papers, while the reviewer group indicated that authors include too few papers and cite irrelevant papers. …”
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Effect of hydrophobic soils on infiltration by Tong, Wan Yi

“…The fine sand layer was then replaced by hydrophobic fine sand to study the effect of hydrophobicity on the infiltration. …”
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Rapid construction of green nanopesticide delivery systems using sophorolipids as surfactants by flash nanoprecipitation by Ma, Enguang, Chen, Kai, Sun, Liang, Fu, Zhinan, Guo, Jiangtao, Liu, Jichang, Zhao, Jigang, Liu, Zhiyong, Lei, Zhigang, Li, Li, Hu, Xiao, Guo, Xuhong

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Perceptual distortion analysis for images by Dong, Li

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Soil-water characteristic curves of hydrophobic sand by Tan, Nicole Shi Qi

“…In this project, the effect of hydrophobicity is investigated using fine and coarse sands. Fine sand was made hydrophobic and mixed with either fine or coarse sand such that sand mixtures of hydrophobicity 20%, 50% and 80% by mass were obtained. …”
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Human machine interface/brain control for electric vehicles application by Tang, Tao

“…Secondly, the same design methodology is extended to a 16-channel TDM/CS AFE with tunable DC-servo loop and fine-trimming input impedance boosting loop. A 4-bit calibrated impedance boosting loop contributed to the input impedance of 560 MΩ as well as CMRR for input interface. …”
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Investigation of the contribution of bioaerosol loading to indoor PM pollution on university campus in Singapore by Lee, Brandon Jia Hao

“…Fine particles could be mitigated safely for occupants with an electrostatic precipitator and future work could expound on elevated fungi concentrations in an indoor environment and fine particle mitigation strategies.…”
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Interpreting learned feedback patterns in large language models by Marks, L, Abdullah, A, Neo, C, Arike, R, Krueger, D, Torr, P, Barez, F

“…To test this, we train probes to estimate the feedback signal implicit in the activations of a fine-tuned LLM. We then compare these estimates to the true feedback, measuring how accurate the LFPs are to the fine-tuning feedback. …”

Genetic algorithm based deep learning model adaptation for improvising the motor imagery classification by R, Vishnupriya, Robinson, Neethu, M, Ramasubba Reddy

“…Transfer learning methods such as adaptation or fine-tuning can be used on the pre-trained model to improve the performance. …”
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SimSC: a simple framework for semantic correspondence with temperature learning by Li, X, Han, K, Wan, X, Prisacariu, VA

“…We discover that when fine-tuning ImageNet pre-trained backbone on the semantic matching task, L2 normalization of the feature map, a standard procedure in feature matching, produces an overly smooth matching distribution and significantly hinders the fine-tuning process. …”

Field instrumentation for performance assessment of Geobarrier System by Rahardjo, Harianto, Qian, Zhai, Satyanaga, Alfrendo, Leong, Eng Choon, Wang, Chien Looi, Wong, Johnny Liang Heng

“…The saturated hydraulic conductivity of a coarse-grained material is normally higher than that of a fine-grained material. However, the unsaturated hydraulic conductivity of the coarse-grained material decreases much faster than that of the fine-grained material with increasing matric suction and consequently the coarse-grained material can be less permeable than the fine-grained material in unsaturated condition. …”
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Red Alarm for Pre-trained Models: Universal Vulnerability to Neuron-level Backdoor Attacks by Zhang, Zhengyan, Xiao, Guangxuan, Li, Yongwei, Lv, Tian, Qi, Fanchao, Liu, Zhiyuan, Wang, Yasheng, Jiang, Xin, Sun, Maosong

“…The pre-training-then-fine-tuning paradigm has been widely used in deep learning. …”
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Build a Large Language Model (From Scratch) / by Raschka, Sebastian, author 656094

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Technological transmission of knowledge in Neolithic northwestern China: mineralogical and chemical analyses of Yangshao and Majiayao painted ware by Spataro, M, Hein, A

“…The analyses were carried out to detect differences or similarities in the chaînes opératoires of ceramic production at the three sites, in particular, to examine the clay types selected to make the three main categories of wares for which Yangshao and Majiayao are known, namely painted fine wares, burnished fine wares, and unpainted coarse wares. …”

WiFi and vision multimodal self-supervised learning for human activity recognition by Tang, Shijie

“…In this context, we propose a novel Multimodal Pretrain fine-tune (MPF) network architecture for device-free human activity recognition using commercial WiFi-enabled IoT devices and cameras. …”
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