Representation learning in the artificial and biological neural networks underlying sensorimotor integration by Suhaimi, Ahmad, Lim, Amos W. H., Chia, Xin Wei, Li, Chunyue, Makino, Hiroshi

“…PPC neurons also exhibited representations of the internally defined subgoal, a feature of deep RL algorithms postulated to improve sample efficiency. …”
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Laboratory realization of relativistic pair-plasma beams by Arrowsmith, CD, Simon, P, Bilbao, PJ, Bott, AFA, Burger, S, Chen, H, Cruz, FD, Davenne, T, Efthymiopoulos, I, Froula, DH, Goillot, A, Gudmundsson, JT, Haberberger, D, Halliday, JWD, Hodge, T, Huffman, BT, Iaquinta, S, Miniati, F, Reville, B, Sarkar, S, Schekochihin, AA, Silva, LO, Simpson, R, Stergiou, V, Trines, RMGM, Charitonidis, N, Bingham, R, Gregori, G

“…We present the first experimental results confirming the generation of high-density, quasi-neutral, relativistic electron-positron pair beams using the 440 GeV/c beam at CERN’s Super Proton Synchrotron (SPS) accelerator. …”

Laboratory realization of relativistic pair-plasma beams by Arrowsmith, C, Simon, P, Bilbao, P, Bott, A, Burger, S, Chen, H, Cruz, F, Davenne, T, Efthymiopoulos, I, Froula, D, Goillot, AM, Gudmundsson, JT, Haberberger, D, Halliday, J, Hodge, T, Huffman, B, Iaquinta, S, Miniati, F, Reville, B, Sarkar, S, Schekochihin, A, Silva, L, Simpson, Stergiou, V, Trines, R, Vieu, T, Charitonidis, N, Bingham, R, Gregori, G

“…We present first experimental results confirming the generation of high-density, quasi-neutral, relativistic electron-positron pair beams using the 440 GeV/c beam at CERN's Super Proton Synchrotron (SPS) accelerator. …”

Advancing cyber incident timeline analysis through retrieval-augmented generation and large language models by Loumachi, Fatma Yasmine, Ghanem, Mohamed Chahine, Ferrag, Mohamed Amine

“…This paper introduces an innovative framework, GenDFIR, a context-specific approach powered via large language model (LLM) capabilities. …”
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Modeling entity and event relations in scientific documents for supporting knowledge discovery and organization by Wu, Yejun

“…Here what one entity did to another entity under what condition is defined as an event, which expresses the relationship between two entities under a condition. …”
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Study of organization structure and empowerment profile of construction companies in Singapore by Pham, Thanh Hai.

“…In the modern world where change is the only constant, Construction Industry must be able to adapt and even take advantage of change for highest benefit. …”
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Urban vulnerability assessment of sea level rise in Singapore through the World Avatar by Phua, Shin Zert, Lee, Kok Foong, Tsai, Yi-Kai, Ganguly, Srishti, Yan, Jingya, Mosbach, Sebastian, Ng, Trina, Moise, Aurel, Horton, Benjamin Peter, Kraft, Markus

“…We introduce OntoSeaLevel, an ontology to describe sea level rise scenarios, and its impact on broader elements defined in other ontologies such as buildings (OntoBuiltEnv ontology), road networks (OpenStreetMap ontology), and land plots (Ontoplot and Ontozoning ontology). …”
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Elucidating the genomic and transcriptomic profiles contributing to the overall survival of acute myeloid leukaemia patients with normal karyotype in Malaysia by Ambayya @ Ampiah, A Angeli

“…Hitherto, the genomic and transcriptomic profiles of AML-NK that contribute to OS remain veiled. Therefore, this study aimed to elucidate the genomic and transcriptomic profiles of AML—NK patients predisposed to their overall survival. …”
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Development and characterisation of novel silicon pixel detectors for tracking and timing by Gaži, M

“…</p> <p>This thesis presents the electrical characterisation of wafers from the first LGAD batch manufactured by Teledyne e2v, featuring samples with a range of gain layer implant energy and dose. Multiple 1×1 mm^2 LGAD devices were tested in a test beam at the CERN North Area. …”

Effective type label-based synergistic representation learning for biomedical event trigger detection by Hao, Anran, Yuan, Haohan, Hui, Siu Cheung, Su, Jian

“…Given its success in image classification, label representation learning is a promising approach to enhancing biomedical event trigger detection models by leveraging the rich semantics of pre-defined event type labels. Results: In this paper, we propose the Biomedical Label-based Synergistic representation Learning (BioLSL) model, which effectively utilizes event type labels by learning their correlation with trigger words and enriches the representation contextually. …”
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Distinctive antibody responses to Mycobacterium tuberculosis in pulmonary and brain infection by Spatola, M, Nziza, N, Irvine, EB, Cizmeci, D, Jung, W, Van, LH, Nhat, LTH, Ha, VTN, Phu, NH, Nghia, HDT, Thwaites, GE, Lauffenburger, DA, Fortune, S, Thuong, NTT, Alter, G

“…Machine learning methods were applied to characterize serum and CSF responses in TBM, identify prognostic factors associated with disease severity, and define the key antibody features that distinguish TBM from pulmonary TB. …”

Tracing RNA biography: in situ transcriptome profiling by novel spatial omics technologies by Ren, Jingyi (Rena)

“…Applying these technologies, I’ve profiled spatial, temporal and single-molecule information of RNA and single cells at the transcriptomic and translational levels in a range of biological systems, including iPSCs, primary skin cells and intact brain tissues. …”
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Magnetic nanochain enabled microarray and microfluidic bioassays by Xiong, Qirong

“…Importantly, PDA not only serves as the scaffold to lock the nanochain structure, but also allows for convenient surface functionalization by means of spontaneous Michael addition and/or Schiff base reaction with nucleophilic thiol and amine groups. …”
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