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  • Publication
    Nanoparticles as a Tool for Broadening Antifungal Activities.
    Renzi, Daniele Fernanda; de Almeida Campos, Laís; Miranda, Eduardo Hösel; Mainardes, Rubiana Mara; Abraham, Wolf-Rainer; Grigoletto, Diana Fortkamp; Khalil, Najeh Maissar
    Fungal infections are diseases that are considered neglected although their infection rates have increased worldwide in the last decades. Thus, since the antifungal arsenal is restricted and many strains have shown resistance, new therapeutic alternatives are necessary. Nanoparticles are considered important alternatives to promote drug delivery. In this sense, the objective of the present study was to evaluate the contributions of newly developed nanoparticles to the treatment of fungal infections. Studies have shown that nanoparticles generally improve the biopharmaceutical and pharmacokinetic characteristics of antifungals, which is reflected in a greater pharmacodynamic potential and lower toxicity, as well as the possibility of prolonged action. It also offers the proposition of new routes of administration. Nanotechnology is known to contribute to a new drug delivery system, not only for the control of infectious diseases but for various other diseases as well. In recent years, several studies have emphasized its application in infectious diseases, presenting better alternatives for the treatment of fungal infections.
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  • Publication
    Dielectric Response Spectroscopy as Means to Investigate Interfacial Effects for Ultra-Thin Film Polymer-Based High NA EUV Lithography.
    (2020-12-12T00:00:00Z) Severi, Joren; De Simone, Danilo; De Gendt, Stefan
    Extreme ultra-violet lithography (EUVL) is the leading-edge technology to produce advanced nanoelectronics. The further development of EUVL is heavily based on implementing the so-called high numerical aperture (NA) EUVL, which will enable even smaller pitches up to 8 nm half pitch (HP). In anticipation of this high NA technology, it is crucial to assess the readiness of the current resist materials for the high NA regime to comply with the demanding requirements of resolution, line-edge roughness, and sensitivity (RLS). The achievable tighter pitches require lower film thicknesses for both resist and underlying transfer layers. A concern that is tied to the thinning down is the potential change in resist properties and behavior due to the interaction with the underlayer. To increase the fundamental understanding of ultra-thin films for high NA EUVL, a method to investigate the interplay of reduced film thickness and different patterning-relevant underlayers is developed by looking at the glass transition temperature (T) of polymer-based resists. To minimize the ambiguity of the results due to resist additives (i.e., photoacid generator (PAG) and quencher), it was opted to move forward with polymer-only samples, the main component of the resist, at this stage of the investigation. By using dielectric response spectroscopy, the results obtained show that changing the protection group of the polymer, as well as altering the polymer film thickness impacts the dynamics of the polymer mobility, which can be assessed through the T of the system. Unexpectedly, changing the underlayer did not result in a clear change in the polymer mobility at the tested film thicknesses.
  • Publication
    RobBERT: a Dutch RoBERTa-based Language Model
    (2020-01-17T13:25:44Z)
    Pre-trained language models have been dominating the field of natural language processing in recent years, and have led to significant performance gains for various complex natural language tasks. One of the most prominent pre-trained language models is BERT, which was released as an English as well as a multilingual version. Although multilingual BERT performs well on many tasks, recent studies show that BERT models trained on a single language significantly outperform the multilingual version. Training a Dutch BERT model thus has a lot of potential for a wide range of Dutch NLP tasks. While previous approaches have used earlier implementations of BERT to train a Dutch version of BERT, we used RoBERTa, a robustly optimized BERT approach, to train a Dutch language model called RobBERT. We measured its performance on various tasks as well as the importance of the fine-tuning dataset size. We also evaluated the importance of language-specific tokenizers and the model's fairness. We found that RobBERT improves state-of-the-art results for various tasks, and especially significantly outperforms other models when dealing with smaller datasets. These results indicate that it is a powerful pre-trained model for a large variety of Dutch language tasks. The pre-trained and fine-tuned models are publicly available to support further downstream Dutch NLP applications.
  • Publication
    From Visual Semantic Parameterization to Graphic Visualization
    (IEEE, 2013-06-28) Zeng, Xin
    Visualizing natural language description is a difficult and complex task. When dealing with the process of generating images from natural language descriptions, we firstly should consider the real world and find out what key visual information can be extracted from the sentences which represents the most fundament concepts in both virtual and real environments. In this paper, we present the result of a prototype system called 3DSV (3D Story Visualiser) that generates a virtual scene by using simplified story-based descriptions. In particular, we describe the methodology used to parameterize the visual and describable words into XML formatted data structure. Then we discuss how to interpret the parameterized data and create an interactive real-time 3D virtual environment.

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