ORCID Profile
0000-0002-9664-3830
Current Organisations
UNSW Sydney
,
Aarhus University
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Publisher: Wiley
Date: 28-11-2018
Abstract: Nanozymes, nanoparticles that mimic the natural activity of enzymes, are intriguing academically and are important in the context of the Origin of Life. However, current nanozymes offer mimicry of a narrow range of mammalian enzymes, near-exclusively performing redox reactions. We present an unexpected discovery of non-proteinaceous enzymes based on metals, metal oxides, 1D/2D-materials, and non-metallic nanomaterials. The specific novelty of these findings lies in the identification of nanozymes with apparent mimicry of erse mammalian enzymes, including unique pan-glycosidases. Further novelty lies in the identification of the substrate scope for the lead candidates, specifically in the context of bioconversion of glucuronides, that is, human metabolites and privileged prodrugs in the field of enzyme-prodrug therapies. Lastly, nanozymes are employed for conversion of glucuronide prodrugs into marketed anti-inflammatory and antibacterial agents, as well as "nanozyme prodrug therapy" to mediate antibacterial measures.
Publisher: Wiley
Date: 11-01-2021
DOI: 10.1002/ROB.22015
Abstract: Visual navigation is a commonly researched alternative to the use of global navigation satellite systems in challenging environments where satellite signals are not available. However, the vast majority of visual navigation techniques studied to date require scene illumination of some form. In this study, we use a low‐resolution long‐wave infrared (LWIR) image sensor sensitive to thermal emissivity within an optical flow processing engine to extend a low complexity track‐based navigation scheme for fixed wing aircraft to operate at night. A mixture of closed and open loop flight experiments conducted on a small UAV integrated with the new sensor demonstrate: accurate track‐based navigation in visual darkness that the LWIR sensor performs equivalently to the benchmark optical flow sensor during daylight and continues to operate in low light and that the LWIR sensor is able to detect suitable textures for operation at night across a wide span of altitudes. These results demonstrate utility of optical flow algorithms with low‐resolution thermal scenes as a novel aircraft navigation sensor for day and night operation.
Publisher: MDPI AG
Date: 05-02-2021
Abstract: The World Health Organization (WHO) has declared COVID-19 a pandemic. We review and reduce the clinical literature on diagnosis of COVID-19 through symptoms that might be remotely detected as of early May 2020. Vital signs associated with respiratory distress and fever, coughing, and visible infections have been reported. Fever screening by temperature monitoring is currently popular. However, improved noncontact detection is sought. Vital signs including heart rate and respiratory rate are affected by the condition. Cough, fatigue, and visible infections are also reported as common symptoms. There are non-contact methods for measuring vital signs remotely that have been shown to have acceptable accuracy, reliability, and practicality in some settings. Each has its pros and cons and may perform well in some challenges but be inadequate in others. Our review shows that visible spectrum and thermal spectrum cameras offer the best options for truly noncontact sensing of those studied to date, thermal cameras due to their potential to measure all likely symptoms on a single camera, especially temperature, and video cameras due to their availability, cost, adaptability, and compatibility. Substantial supply chain disruptions during the pandemic and the widespread nature of the problem means that cost-effectiveness and availability are important considerations.
Publisher: MDPI AG
Date: 19-10-2021
Abstract: Limited navigation capabilities of many current robots and UAVs restricts their applications in GPS denied areas. Large aircraft with complex navigation systems rely on a variety of sensors including radio frequency aids and high performance inertial systems rendering them somewhat resistant to GPS denial. The rapid development of computer vision has seen cameras incorporated into small drones. Vision-based systems, consisting of one or more cameras, could arguably satisfy both size and weight constraints faced by UAVs. A new generation of thermal sensors is available that are lighter, smaller and widely available. Thermal sensors are a solution to enable navigation in difficult environments, including in low-light, dust or smoke. The purpose of this paper is to present a comprehensive literature review of thermal sensors integrated into navigation systems. Furthermore, the physics and characteristics of thermal sensors will also be presented to provide insight into challenges when integrating thermal sensors in place of conventional visual spectrum sensors.
Publisher: American Chemical Society (ACS)
Date: 15-06-2016
DOI: 10.1021/ACS.MOLPHARMACEUT.6B00156
Abstract: In this article a library of polymeric therapeutic agents against the human immunodeficiency virus (HIV) is presented. The library of statistical copolymers of varied molar mass was synthesized by reversible addition-fragmentation chain transfer (RAFT) polymerization. The synthesized polymers comprise pendent hydroxyl and sulfonated side chains as well as the reverse transcriptase prodrug lamivudine (3TC) attached via a disulfide self-immolative linker. The glutathione mediated release of 3TC is demonstrated as well as the antiviral efficacy against HIV entry and polymerase activity. Although a high degree of polymer sulfonation is required for effective HIV entry inhibition, polymers with approximately ∼50% sulfonated monomer demonstrated potent kinase independent reverse transcriptase inhibition. In addition, the sulfonated polymers demonstrate activity against DNA-DNA polymerase, which suggests that these polymers may exhibit activity against a broad spectrum of viruses. In summary, the polymers described provide a triple-active arsenal against HIV with extracellular activity via entry inhibition and intracellular activity by kinase-dependent lamivudine-based and kinase-independent sulfonated polymer based inhibition. Since these sulfonated copolymers are easily formulated into gels, we envision them to be particularly suited for topical application to prevent the mucosal transmission of viruses, particularly HIV.
Publisher: MDPI AG
Date: 16-04-2022
Abstract: It is necessary to establish the relative performance of established optical flow approaches in airborne scenarios with thermal cameras. This study investigated the performance of a dense optical flow algorithm on 14 bit radiometric images of the ground. While sparse techniques that rely on feature matching techniques perform very well with airborne thermal data in high-contrast thermal conditions, these techniques suffer in low-contrast scenes, where there are fewer detectable and distinct features in the image. On the other hand, some dense optical flow algorithms are highly amenable to parallel processing approaches compared to those that rely on tracking and feature detection. A Long-Wave Infrared (LWIR) micro-sensor and a PX4Flow optical sensor were mounted looking downwards on a drone. We compared the optical flow signals of a representative dense optical flow technique, the Image Interpolation Algorithm (I2A), to the Lucas–Kanade (LK) algorithm in OpenCV and the visible light optical flow results from the PX4Flow in both X and Y displacements. The I2A to LK was found to be generally comparable in performance and better in cold-soaked environments while suffering from the aperture problem in some scenes.
Publisher: American Chemical Society (ACS)
Date: 30-04-2018
Publisher: Wiley
Date: 06-02-2022
DOI: 10.1002/ROB.22065
Abstract: This study explores the utility of optical flow calculated from thermal imaging cameras, “thermal flow,” mounted on an aircraft for localization in day and night conditions. Our sensor implementation utilizes a long wave infrared (LWIR) micro sensor to capture sequences of thermal images and an on‐board computer to compute an optical flow estimate. We compared the performance of optical flow from the LWIR camera with the output of visible spectrum optical flow sensor. Flights were conducted spanning a 24 h window to explore how thermal flow performs relative to optical flow as the ground heats and cools. Agreement between optical and thermal flow was found during daylight when both sensors were functional. Additionally, thermal flow results were reliable in the middle of the day through to late evening, gradually degrading until shortly after sunrise.
Publisher: Elsevier BV
Date: 2019
DOI: 10.1016/J.JCONREL.2018.12.016
Abstract: Albumin is a highly successful tool of drug delivery providing drastically extended body and blood residence time for the associated cargo, but it only traffics single drug copies at a time. In turn, macromolecular prodrugs (MP) are advantaged in carrying a high drug payload but offering only a modest extension of residence time to the conjugated drugs. In this work, we engineer MP to contain terminal groups that bind to albumin via non-covalent association and reveal that this facile measure affords a significant protraction for the associated polymers. This methodology is applied to MP of acyclovir, a successful drug against herpes simplex virus infection but with poor pharmacokinetics. Resulting albumin-affine MP were efficacious agents against herpes simplex virus type 2 (HSV-2) both in vitro and in vivo. In the latter case, sub-cutaneous administration of MP resulted in local (vaginal) antiviral effects and a systemic protection. Presented benefits of non-covalent association with albumin are readily transferrable to a wide variety of MP in development for drug delivery as anticancer, anti-inflammatory, and anti-viral measures.
Publisher: MDPI AG
Date: 12-10-2022
Abstract: This study is inspired by the widely used algorithm for real-time optical flow, the sparse Lucas–Kanade, by applying a feature extractor to decrease the computational requirement of optical flow based neural networks from real-world thermal aerial imagery. Although deep-learning-based algorithms have achieved state-of-the-art accuracy and have outperformed most traditional techniques, most of them cannot be implemented on a small multi-rotor UAV due to size and weight constraints on the platform. This challenge comes from the high computational cost of these techniques, with implementations requiring an integrated graphics processing unit with a powerful on-board computer to run in real time, resulting in a larger payload and consequently shorter flight time. For navigation applications that only require a 2D optical flow vector, a dense flow field computed from a deep learning neural network contains redundant information. A feature extractor based on the Shi–Tomasi technique was used to extract only appropriate features from thermal images to compute optical flow. The state-of-the-art RAFT-s model was trained with a full image and with our proposed alternative input, showing a substantial increase in speed while maintain its accuracy in the presence of high thermal contrast where features could be detected.
Publisher: Wiley
Date: 12-06-2023
DOI: 10.1002/ROB.22219
Abstract: The study explores the feasibility of optical flow‐based neural network from real‐world thermal aerial imagery. While traditional optical flow techniques have shown adequate performance, sparse techniques do not work well during cold‐soaked low‐contrast conditions, and dense algorithms are more accurate in low‐contrast conditions but suffer from the aperture problem in some scenes. On the other hand, optical flow from convolutional neural networks has demonstrated good performance with strong generalization from several synthetic public data set benchmarks. Ground truth was generated from real‐world thermal data estimated with traditional dense optical flow techniques. The state‐of‐the‐art Recurrent All‐Pairs Field Transform for the Optical Flow model was trained with both color synthetic data and the captured real‐world thermal data across various thermal contrast conditions. The results showed strong performance of the deep‐learning network against established sparse and dense optical flow techniques in various environments and weather conditions, at the cost of higher computational demand.
No related grants have been discovered for Camilla Kaas Frich.