Somatosensory and clinical profiles of patients with spine-related and clinical framework-based neck–arm pain by Kapitza, C, Ballenberger, N, Luedtke, K, Schmid, AB, Tampin, B

“…<p>Spine-related neck–arm pain is heterogeneous and may present on a spectrum between nociceptive and neuropathic pain. …”

Biosorption of silver ions. by Toh, Guanhong.

“…In this project, ECH-chitosan beads, BCD grafted chitosan beads and native chitosan hydrogel beads are tested for adsorption of silver ions. pH is varied across the range of 4 to 8. All three types of chitosan beads are able to adsorb silver ions. …”
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Investigating Interventions in Fine-grained Contexts for Habit Formation by Khan, Mina

“…Habits are automatic responses to specific contextual cues, and can help sustain behavior change. Fine-grained specific contexts are commonly used in habit formation, but interventions in automatically-detected fine-grained contexts have rarely been explored for habit formation. …”
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The fine line between jianli guanxi and la guanxi. by Loh, Wan Fong.

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Origin of a topotactic reduction effect for superconductivity in infinite-layer nickelates by Zeng, Shengwei, Tang, Chi Sin, Luo, Zhaoyang, Chow, Lin Er, Lim, Zhi Shiuh, Prakash, Saurav, Yang, Ping, Diao, Caozheng, Yu, Xiaojiang, Xing, Zhenxiang, Ji, Rong, Yin, Xinmao, Li, Changjian, Wang, Renshaw Xiao, He, Qian, Breese, Mark B. H., Ariando, A., Liu, Huajun

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Extracting structured data from organic synthesis procedures using a fine-tuned large language model by Ai, Qianxiang, Meng, Fanwang, Shi, Jiale, Pelkie, Brenden, Coley, Connor W

“…The fine-tuned model produces syntactically correct ORD records with an average accuracy of 91.25% for ORD “messages” (e.g., full compound, workups, or condition definitions) and 92.25% for individual data fields (e.g., compound identifiers, mass quantities), with the ability to recognize compound-referencing tokens and to infer reaction roles. …”
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FPGA implementation of spiking convolutional neural networks for voice keyword recognition by Ng, Wei Soon

“…The spiking convolutional neural network (SCNN) is a hybrid model of both the spiking neural network (SNN) and convolutional neural network (CNN). …”
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Fine-scale population structure and widespread conservation of genetic effect sizes between human groups across traits by Hu, S, Ferreira, LAF, Shi, S, Hellenthal, G, Marchini, J, Lawson, DJ, Myers, SR

“…We developed a statistical pipeline to infer fine-scale Ancestry Components and applied it to UK Biobank data. …”

Investigating Fine-Tuning of Language Models for Multiple-Choice Questions by Wang, Ivy A.

“…We specifically investigate training data properties related to positional bias in fine-tuned language model performance on correctly answering MCQs. …”
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Fabrication of fine features using digital light processing stereolithography by Chew, Ze Yong

“…Thus, this project was developed with the objectives to: 1. reduce production cost of Stereolithography by optimizing low end commercial Stereolithography system – ASIGA Freeform Pico 39 Plus such that it is able to print fine features 2. explore effective and convenient post processing step such that it is able to reduce material wastage and at the same time further shorten production lead time The parameter study conducted revealed that every layer thickness has a specific optimal exposure time such that the layers could be printed just fine, with minimal compromise of the internal features’ accuracy. …”
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Investigating fine-tuning of large language models for text summarisation by Khaliq, Usama, Patel, Preeti

“…The limited performance increase from the fine-tuned models was likely due to small datasets and medium-sized LLMs. …”
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Visual analytics for fine-grained text classification models and datasets by Battogtokh, M, Xing, Y, Davidescu, C, Abdul-Rahman, A, Luck, M, Borgo, R

“…In natural language processing (NLP), text classification tasks are increasingly fine-grained, as datasets are fragmented into a larger number of classes that are more difficult to differentiate from one another. …”

Preventing lithium-ion (li-ion) cell fire with an embedded extinguisher by Muhammad Azrie Bin Razale

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A review on substitution of natural sand with granite fines in sustainable concrete by Li, Ziyang, Lao, Junying, Wang, Lijie, Lim, Namyo Salim, Tan, Kang Hai, Qian, Shunzhi

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Ultra-fine bainite in medium-carbon high-silicon bainitic steel by Yu, Xinpan, Wang, Yong, Wu, Huibin, Gong, Na

“…%C ultra-fine bainitic steel is through austenitization at 1000 °C and austempering at 340 °C.…”
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Effects of lumbar support to reduce discomfort during prolonged riding among motocyclists by Mohd Shafiei, Umi Kalsom

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Bio-inspired categorization using event-driven feature extraction and spike-based learning by Zhao, Bo, Chen, Shoushun, Tang, Huajin

“…Bio-inspired, cortex-like, spikebased features are obtained through event-driven convolution and neural competition. The extracted spike feature patterns are then classified by a network of leaky integrate-and-fire (LIF) spiking neurons, in which the weights are trained using tempotron learning rule. …”
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Morphological learning in spiking neurons: a new hardware efficient maching learning method by Jahagirdar, Kavya

“…The latest developments in the research of spiking neural network models have shown that unlike the classic neural network models, these models communicate via precisely timed neuron spikes, thus making them a closer representation of the biological neurons. …”
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Design of a hybrid neural spike detection algorithm for implantable integrated brain circuits by Zeinolabedin, Seyed Mohammad Ali, Do, Anh Tuan, Yeo, Kiat Seng, Kim, Tony Tae-Hyoung

Subjects: “…Spike…”
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Fish Motion Trajectories Detection Algorithm Based on Spiking Neural Network (S/O: 12893) by Yusoff, Nooraini, Yusof, Yuhanis, Siraj, Fadzilah, Ahmad, Farzana Kabir

“…This study proposes sequence learning for the fish motion trajectory by using the Spike-Time dependent Plasticity (STDP) in the Spiking Neural Networks (SNNs). …”
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