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Public commemorations and remembrance
No full textPublic commemorative artefacts (including public monuments) typically mark out some historical subject – typically, a person or an event – as important for a community to remember. This chapter surveys the budding literature on the historical character of public commemorative artefacts. First, it details three typical aims of public commemorative artefacts as they pertain to public remembrance. They declare the importance of some historical subject, impart ethical or political lessons, and foster community identity that is grounded in shared remembrance of the past. Next, it outlines two common problems with public commemorative artefacts. They can present incomplete or distorted accounts of history, and lead people to abdicate responsibility for the past. The chapter proposes an account of democratic public historiography that addresses the problems with public commemorative artefacts.Submitted/Accepted versio
Anti-intracellular MRSA activity of antibiotic-loaded lipid-polymer hybrid nanoparticles and their effectiveness in murine skin wound infection models
No full textMethicillin-resistant Staphylococcus aureus (MRSA) is a significant concern for skin and soft tissue infections. Apart from biofilm formation, these bacteria can reside intracellularly in phagocytic and nonphagocytic mammalian cells, complicating treatment with conventional antibiotics. Lipid-polymer hybrid nanoparticle (LPN) systems, combining the advantages of polymeric nanoparticles and liposomes, represent a new generation of nanocarriers with the potential to address these therapeutic challenges. In this study, gentamicin (Gen) and vancomycin (Van) were encapsulated in LPNs and evaluated for their ability to eliminate intracellular MRSA in phagocytic macrophage RAW-Blue cells and nonphagocytic epithelial HaCaT cells. Compared to free antibiotics at 100 μg/mL, LPN formulations significantly reduced intracellular bacterial loads in both cell lines. Specifically, LPN-Van resulted in approximately 0.7 Log CFU/well reduction in RAW-Blue cells and 0.3 Log CFU/well reduction in HaCaT cells. LPN-Gen showed a more pronounced reduction, with approximately 1.26 Log CFU/well reduction in RAW-Blue cells and 0.45 Log CFU/well reduction in HaCaT cells. In vivo, LPN-Van at 500 μg/mL significantly reduced MRSA biofilm viability compared to untreated controls (p < 0.001), achieving 98% eradication based on median values. In comparison, free vancomycin achieved a nonstatistically significant 79.2% reduction in biofilm viability compared to control. Prophylactically, LPN-Van at 500 μg/mL decreased MRSA levels to the limit of detection, resulting in a ∼3.5 Log reduction in the median CFU/wound compared to free vancomycin. No acute dermal toxicity was observed for LPN-Van based on histological analysis. These data indicate that LPNs show promise as a drug delivery platform technology to address intracellular infections.Ministry of Education (MOE)Singapore Food AgencySubmitted/Accepted versionThe authors would like to acknowledge the financial support from the Singapore Center for Environmental Life Sciences Engineering (SCELSE) (MOE/RCE: M4330019.C70), Ministry of Education AcRF-Tier 1 grant (RT08/19, RG79/22), the Singapore National Biofilm Consortium (SNBC/2021/SF2/P04), and the Singapore Food Agency (SFS_RND_SUFP_001_06)
Investigating precarity: experiences of low-income precarious young workers in Singapore
No full textPrecarity is a characteristic of modern-day work. The issue gained traction in academic western literature, which attributed precarious work to neoliberal globalisation as workers undertook more risks. This is especially so for lower-wage workers, whose life circumstances could take a turn for the worse should they lose their jobs or when an unexpected crisis hits. This thesis asserts that it is important to understand precarity not only through workers’ experiences but also through Singapore’s economic, historical and welfare contexts. Singapore’s labour history and economic transformation set the context for understanding individual experiences of precarity through the concept of labour regimes. Using in-depth interviews with young low-wage workers from the NUS study on In-Work Poverty and Challenges of Getting by Among the Young, this thesis documented the experiences of low-wage precarious workers. This was followed by an exploration of workers’ motivations for entering precarious work and the longer-term scarring effects of precarious work. The study’s fieldwork coincided with the COVID-19 pandemic, which affected low-wage workers who were both in precarious work and regular employment. The incident exposed the precarious nature of all work. Throughout the thesis, workers were seen as individuals with agency who were navigating the challenging structures of precarious work. The thesis ends with a emphasising the uniqueness of the Singapore case in understanding low wage precarious work and some implications of the study’s findings.Master's degre
Breaking the mold of the female: a case study of park chan-wook's decision to leave (2022)
No full textThe prominence of South Korean film in the global film market has surged in recent years, with a notable focus on feminist themes and gender equality. Films featuring rebellious female characters have captured international attention and acclaim. This study explores the portrayal of feminist themes through the character Seorae in the South Korean film Decision to Leave (2022). Seorae exemplifies the recent advancements in the Korean film industry and its aesthetic standards. Through various cinematic elements, such as casting, screenplay, and filming techniques, she has become a quintessential representation of a rebellious female character. Director Park Chan-Wook, a pioneer in South Korean film noir, collaborated with female scriptwriter Chung Seo- kyung to craft many chaotic, angry, humorous, violent, and vulnerable female characters for two decades from 2002, establishing a distinctive creative style.
By analyzing the female character Seorae, this research aims to research the construction of feminist themes in South Korean cinema. The study examines how Park Chan-wook's artistic choices, including the casting of the leading actress, color and art strategies, sound design, and camera shot language, contribute to the creation of Seorae's character. This research not only highlights the interplay between feminist theory and cinematic aesthetics but also provides practical insights for future filmmaking. The conclusions drawn from this study offer new perspectives on the portrayal of female characters and contribute to the ongoing discourse on gender equality in cinema.Master's degre
T3DNet: compressing point cloud models for lightweight 3-D recognition
No full textThe 3-D point cloud has been widely used in many mobile application scenarios, including autonomous driving and 3-D sensing on mobile devices. However, existing 3-D point cloud models tend to be large and cumbersome, making them hard to deploy on edged devices due to their high memory requirements and nonreal-time latency. There has been a lack of research on how to compress 3-D point cloud models into lightweight models. In this article, we propose a method called T3DNet (tiny 3-D network with augmentation and distillation) to address this issue. We find that the tiny model after network augmentation is much easier for a teacher to distill. Instead of gradually reducing the parameters through techniques, such as pruning or quantization, we predefine a tiny model and improve its performance through auxiliary supervision from augmented networks and the original model. We evaluate our method on several public datasets, including ModelNet40, ShapeNet, and ScanObjectNN. Our method can achieve high compression rates without significant accuracy sacrifice, achieving state-of-the-art performances on three datasets against existing methods. Amazingly, our T3DNet is 58× smaller and 54× faster than the original model yet with only 1.4% accuracy descent on the ModelNet40 dataset. Our code is available at https://github.com/Zhiyuan002/T3DNet.Nanyang Technological UniversityThis work was supported by a Start-Up Grant at Nanyang Technological University
Nanoindentation behavior in T-carbon thin films: a molecular dynamics study
No full textT-carbon is a new allotrope of carbon materials, and it displays high hardness and low density. Nevertheless, the hardening mechanisms of T-carbon thin films under nanoindentation remain elusive. This work utilizes molecular dynamics simulation to explore the hardening mechanisms of T-carbon thin films under nanoindentation with variations of loading velocities and temperatures. The results reveal that a loading velocity increase at a given temperature raises the nanoindentation force. The increase in nanoindentation force is due to graphitization, which is related to the fracture of tetrahedral structures in T-carbon thin films. However, increased graphitization caused by an increased temperature lowers the nanoindentation force at a given loading velocity. The increased graphitization is influenced by both the fractured tetrahedrons and the deformation of inter-tetrahedron bond angles. This is attributed to the loss of thermal stability and the lower density of T-carbon thin films as the temperature increases. These findings have significant implications for the design of nanodevices for specific application requirements
Semantic, syntactic and joint deep learning of event extraction
No full textMuch of human decision-making is based on a cognition of events. Events, ranging from simple occurrences to complex structures, form the essence of human communication, encapsulating rich information about actions, entities, and relationships. In the era of big data, empowering machines to recognize events in human language emerges as an important research problem for unlocking valuable insights from unstructured textual data. Event Extraction (EE), one of the main Information Extraction (IE) tasks in the field of Natural Language Processing (NLP), is immensely useful for real-world applications across different fields such as media, business, cybersecurity, and biomedical research.
Event extraction methods aims at automatically extracting event-related mentions from text documents written in natural language. However, traditional rule-based and statistical methods for event extraction often struggle to handle the inherent complexity and variability of natural language. This limitation has spurred significant interest in leveraging deep learning and neural network techniques to tackle the challenges of event extraction. Neural methods offer the promise of automatically learning intricate patterns and representations from data, enabling more effective and efficient event extraction systems.
Motivated by the growing importance of event extraction and the potential of neural approaches, this thesis aims to explore novel methods for enhancing event extraction from different aspects of deep learning. By delving into the nuances of event representation learning, semantic and syntactic understanding, and multi-task learning optimization, the thesis aims to push the boundaries of current event extraction systems and pave the way for more accurate and comprehensive event understanding.
In summary, the main contributions are: first, we propose the Contrastive Learning Framework via Semantic Type Prototype Representation Modeling for Event Detection (SemPRE), which utilizes pre-defined event type labels to capture event type semantics. On two benchmark datasets, namely ACE 2005 and MAVEN, SemPRE achieves state-of-the-art results and demonstrates excellent performance in situations with limited training data, sentences containing multiple events, and trigger word disambiguation, thus offering a robust solution for more accurate and efficient event detection systems.
Second, we propose Syntactic Reinforcement for Neural Event Extraction (SRE) model for sentence-level and document-level event extraction. Sentence-level SRE outperforms other models on ACE 2005, CASIE, and PHEE, while document-level SRE outperforms prior state-of-the-art on MUC-4. It also achieves absolute improvements of 1.10\%-11.81\% in recall over the existing models on MUC-4. This is the first work that explores the feasibility of intrinsic syntactic mechanisms for event extraction, pushing the boundaries of extraction performance in both fine-grained sentence-level tasks and broader document-level event extraction.
Third, we propose the Adaptive Weighting Method for Joint Information Extraction (AWIE), a novel gradient-based optimization method to balance task losses for joint information extraction dynamically. On three multi-task IE datasets, AWIE outperforms the existing state-of-the-art Uncertainty and MGDA-UB techniques over all the tasks in F1 scores. For event extraction, AWIE improves the static-weighting DYGIE++ baseline by 1.7\%-3.1\% in F1 scores for the event trigger extraction and argument classification subtasks. It offers an effective strategy that dynamically balances task losses during joint IE model training.
Finally, we propose a domain-specific model for biomedical event trigger extraction, Bio-SemSyntEE, which incorporates the semantic-based mechanism from our proposed SemPRE model and the syntax-based mechanism from our proposed SRE model. Bio-SemSyntEE outperforms both discriminative and generative state-of-the-art models across three benchmark datasets. The results demonstrate the generalisability and robustness of our proposed mechanisms for domain-specific applications.Doctor of Philosoph
Multimodal electrolyte architecting for static aqueous zinc-halogen batteries
No full textRechargeable static aqueous zinc-halogen batteries (AZHBs) thrive in energy storage applications due to their suitable redox potential, abundant reserves, and relatively high energy density. This non-flow battery relies on the collaboration of the reversible stripping/plating process of Zn metal and the halogen-participating zincation reactions. However, the corrosion of Zn metal and the shuttling of the halogen species result in serious capacity decay, posing challenges to their reversibility and lifespan. Moreover, the instability of high-valent halides hinders the implementation of multi-electron reactions in AZHBs. This Review elaborates the fundamentals, challenges, and recent progress in AZHBs, highlighting the significance of the electrolyte design aiming at synchronous optimization for both the halogen cathode and Zn anode in AZHBs. We discuss the design principles and protocols, along with concerns in effective test and evaluation of synchronous electrolytes. Possible approaches towards synchronous electrolytes are proposed, namely, biphasic electrolytes, gradient hydrogel electrolytes, and ionic liquid electrolytes. This Review may help guide the research in achieving AZHBs with high energy density and longevity for practical applications.Ministry of Education (MOE)National Research Foundation (NRF)Published versionThis work was supported by the Singapore Ministry of Education by Tier 2 (MOE-T2EP50121-0006) and the National Research Foundation, Singapore, under its Singapore-China Joint Flagship Project (Clean Energy)
Improvement in mechanical as well as magnetic properties of a (FeCoNi)90Ti10-xAlx complex concentrated alloy series by tuning the chemical order
No full textThere is considerable interest in magnetic materials which also possess good mechanical properties. Hence, the effect of Ti/Al ratio on the microstructure, mechanical and magnetic properties of (FeCoNi)90Ti10-xAlx complex concentrated alloys (CCA) was investigated. An increase in the Ti/Al ratio in these CCA enhanced chemical ordering and substantially improved selected mechanical and magnetic properties. As the Ti/Al ratio changed from 10 to 0, the ductility increased from 7.5 to close to 50 %, the saturation magnetization (Ms) increased from
115.2 to 136.7 emu/g, and the coercivity (Hc) decreased from 17.9 to 4.2 Oe. The Fe30Co30Ni30Ti5Al5 alloy exhibit higher UTS×EL value than available soft magnetic materials and has relatively higher Ms and lower Hc compared with other CCA. These results provide a methodology to modulate the chemical order in the Fe-Co-Ni system by Al and Ti additions and synergistically tune the mechanical and magnetic properties for high performance rotating electrical machine applications.Agency for Science, Technology and Research (A*STAR)This work is supported by AME Programmatic Fund by the Agency for Science, Technology and Research, Singapore under Grant No A1898b0043
Surface modification of Sr2Fe1.5Mo0.5O6-δ perovskite electrode with Ru nanoparticles via plasma-enhanced atomic layer deposition for solid oxide fuel cells
No full textThis study demonstrates the use of plasma-enhanced atomic layer deposition (PEALD) to deposit uniformly distributed Ru nanoparticles on a Sr2Fe1.5Mo0.5O6-δ (SFMO) perovskite cathode as a surface modification strategy to improve electrode performance. The PEALD Ru nanoparticles covered the SFMO surface with superior uniformity and high density, significantly enhancing the surface reaction steps of oxygen reduction reactions (ORR). SOFCs with Ru-coated SFMO cathode showed a peak power density of 983 mW/cm2 at 700 °C, a 47 % increase over the SOFCs using bare SFMO cathode. In addition, the presence of high-density Ru nanoparticles also suppressed the Sr surface segregation, which is a chronic issue that deteriorates the long-term stability of Sr-containing perovskite electrodes. The cell performance was maintained for more than 20 h without significant degradation compared to cells using a bare SFMO cathode.Ministry of Education (MOE)This paper was supported by AcRF Tier 1 Grant No. RG73/22 from Singapore Ministry of Education