Research Publications and Outputs

Restoration, Exploration and Transformation: How Youth Engage Character.AI Chatbots for Feels, Fun and Finding themselves

Wed, 25 Mar 2026 00:00:00 GMT

Restoration, Exploration and Transformation: How Youth Engage Character.AI Chatbots for Feels, Fun and Finding themselves Blake, Annabel; Carter, Marcus; Velloso, Eduardo Young people are among the fastest adopters of generative AI, yet research emphasises adult-designed tools and experiments rather than playful, self-directed youth use. We analysed discourse from 4,172 users in Character.AI’s official Discord, finding that the most engaged users were predominantly adolescents (50% aged 13–17), female or non-binary (61.9%), with most (59%) creating their own characters. We contribute (1) a descriptive account of how highly engaged youth on Character.AI’s Discord use AI for playful, emotional, and creative practices that push the platform limits; (2) a framework of three engagement intents — Restoration (emotional regulation), Exploration (creative experimentation), and Transformation (identity development); and (3) a taxonomy of seven youth created character archetypes. Together, these findings reveal how youth invent novel roles for AI, expose critical misalignments between youth use and current AI experiences, and provide frameworks for researchers and practitioners to design youth-centred AI futures.

Prototyping and testing of an active modulating radiative system

Sun, 01 Jan 2023 00:00:00 GMT

Prototyping and testing of an active modulating radiative system Kracic, Djordje; Haddad, Shamila; Khan, Hassan; Paolini, Riccardo; Santamouris, Mattheos; Ranzi, Gianluca Daytime radiative cooling (DRC) is a well-recognised passive cooling solution for future building envelopes to mitigate the intensity of urban overheating. Its superior cooling performance is based on two mechanisms that rely on a high reflection of incident light in the solar range to limit absorbance of solar heat and on a thermal emission of the absorbed heat in the atmospheric window to exploit the outer space as a heat sink. Unfortunately, this cooling technology has been recently shown in the literature to have the potential of compromising the outstanding cooling benefits exhibited in hot weather because of the undesired overcooling that it can produce under cold conditions and that may require additional heating in buildings. For this purpose, the ability for a building surface to switch between a DRC and a Solar Heater (SH) represents an attractive feature to mitigate, or even eliminate, the undesired overcooling while still aiming to minimise the cooling and heating demands of buildings. In this context, this paper presents the prototyping and testing of an active modulating radiative system that can operate as a DRC or SH depending on the weather conditions and building requirements. The system is based on a sandwich structure that encases a set of films with different optical properties. The active modulation between the two operational states of DCR and SR is performed through the actuation of temperature-controlled motors that modify the arrangements of the films to enable the desired performance to be deployed. The system is capable of accommodating different films because the design of the sandwich structure enables for an easy installation and replacement of the films. The sandwich structure provides the additional benefit of protecting the system from rain and wind. The paper also considers the performance of the proposed modulating system when compared to static cooling technologies. The proposed design is scalable and its programmable and responsive nature can support its applicability for a wide range of climatic conditions.

Minimizing and controlling hydrogen for highly efficient FAPbI3 perovskite

Sat, 01 Jan 2022 00:00:00 GMT

Minimizing and controlling hydrogen for highly efficient FAPbI3 perovskite Liang, Yuhang; Cui, Xiangyuan; Li, Feng; Stampfl, Catherine; Ringer, Simon Peter; Huang, Jun; Zheng, Rongkun Formamidinium lead triiodide (FAPbI3) currently holds the record conversion efficiency in the single-junction perovskite solar cell. Iodine management is known to be essential to suppress defect-induced nonradiative losses in FAPbI3 active layers. However, the origin of nonradiative losses and the underlying mechanism of suppressing such losses by iodine-concentration management remain unknown. Here, through first-principles simulation, we demonstrate that native point defects are not responsible for the nonradiative losses in FAPbI3. Instead, hydrogen ions, which can be abundant under both iodine-rich and iodine-poor conditions in FAPbI3, act as efficient nonradiative recombination centers and are proposed to be responsible for the suppressed power conversion efficiency. Moreover, iodine-moderate synthesis conditions can favor the formation of electrically inactive molecular hydrogen, which can dramatically suppress the detrimental hydrogen ions. This work identifies the dominant nonradiative recombination centers in the widely used FAPbI3 layers and rationalizes how the prevailing iodine management reduces the nonradiative losses. Minimizing the unintentional hydrogen incorporation in the perovskite is critical for achieving high device performance.

Atomic and molecular hydrogen in hybrid perovskite solar cells

Sat, 01 Jan 2022 00:00:00 GMT

Atomic and molecular hydrogen in hybrid perovskite solar cells Liang, Yuhang; Cui, Xiangyuan; Stampfl, Catherine; Ringer, Simon Peter; Zheng, Rongkun Hydrogen interstitials are expected to be important in organic–inorganic hybrid perovskites; however, the characteristics and behaviors of hydrogen in perovskites remain poorly understood. Here, on the basis of density functional theory calculations, we quantitatively reported that both atomic and molecular hydrogen interstitials can form in hybrid MAPbI3 and MASnI3 perovskites. Whereas molecular hydrogen interstitial, H2, is chemically inert, atomic hydrogen interstitial, Hi, serves as an electrically active negative-U defect. We identify high-density Hi+ as a significant origin of ionic conductivity in p-type MAPbI3 under the hydrogen-rich conditions, with the calculated activation energy being comparable to that measured in experiments. The highly diffusive Hi+ ions are expected to impact hysteresis, charge separation, device polarization, and photogenerated field-screening effect and consequently degrade the solar cell performance. We evaluated approaches for mitigating such detrimental effects and suggested that synthesizing the perovskites with slightly extra iodine addition or tin alloying can effectively suppress the concentration of Hi+. Our results are important to understand the fundamental aspects of hydrogen in perovskites in general and offer valuable insight for further improving the performance of perovskite solar cells and other optoelectronic devices via defect engineering.

Origin of enhanced nonradiative carrier recombination induced by oxygen in hybrid Sn perovskite

Sun, 01 Jan 2023 00:00:00 GMT

Origin of enhanced nonradiative carrier recombination induced by oxygen in hybrid Sn perovskite Liang, Yuhang; Cui, Xiangyuan; Li, Feng; Stampfl, Catherine; Ringer, Simon Peter; Yang, Xudong; Rongkun, Zheng Oxygen ingression has been shown to substantially decrease the carrier lifetime of Sn-based perovskites, behind which the mechanism remains yet unknown. Our first-principles calculations reveal that in prototypical MASnI3 (MA = CH3NH3), oxygen by itself is not a recombination center. Instead, it tends to form substitutional OI through combining with native I vacancies (VI) and remarkably increases the original recombination rate of VI by 2–3 orders of magnitude. This rationalizes the experimentally observed sharp decline of carrier lifetime in perovskites exposed to air. The significantly enhanced carrier recombination is due to a smaller electron capture barrier of OI, resulting from lattice strengthening and the suppressed structural relaxation upon electron capture. These insights offer a route to further improve device performance via anion engineering in broad Sn-based perovskite optoelectronics operating in ambient air. Moreover, our results highlight the important role of lattice relaxation for nonradiative carrier capture in materials in general.

Interstitial hydrogen anions: a cause of p-type conductivity in CsSnI3

Sat, 01 Jan 2022 00:00:00 GMT

Interstitial hydrogen anions: a cause of p-type conductivity in CsSnI3 Liang, Yuhang; Cui, Xiangyuan; Li, Feng; Stampfl, Catherine; Ringer, Simon Peter; Huang, Jun; Zheng, Rongkun The all-inorganic tin halide perovskite CsSnI3, currently under intensive investigation for photovoltaics and other optoelectronics, characteristically exhibits strong p-type conductivity and consequently poor power conversion efficiency regardless of growth and processing conditions. This has been traditionally attributed to the prevalence of native acceptor defects; however, such a mechanism falls short of explaining the observed high hole concentration under Sn-rich growth conditions in experiments. Here, by using first-principles calculations, we reveal that hydrogen impurities, existing as hydrogen anions, are an important cause for the high p-type character in CsSnI3. Hydrogen anions can be present with high densities and act as shallow acceptors, significantly enhancing the background hole concentrations, even under excess Sn treatment. Careful control and utilization of hydrogen anions are important for improving the performance of CsSnI3-based optoelectronic devices.

Trapped-Hydrogen-Induced Energy Loss in Tin-Based Hybrid Perovskite Solar Cells

Sat, 01 Jan 2022 00:00:00 GMT

Trapped-Hydrogen-Induced Energy Loss in Tin-Based Hybrid Perovskite Solar Cells Liang, Yuhang; Cui, Xiangyuan; Li, Feng; Stampfl, Catherine; Ringer, Simon Peter; Huang, Jun; Zheng, Rongkun The hitherto subdued power conversion efficiencies of Sn-based hybrid perovskite solar cells are generally attributed to severe nonradiative recombination; however, the responsible deep-level defects are still unclear. Here, we report an important nonradiative energy loss mechanism in the prototypical FASn⁢I3 [FA = HC⁢(NH2)2, formamidinium]. High-density tin vacancies (𝑉Sn) can effectively capture hydrogen to form 𝑉Sn −H2 complexes that act as highly detrimental nonradiative recombination centers. We quantitatively show that they can give rise to strong carrier recombination and thus energy loss due to a high nonradiative recombination rate constant. These key findings identify a hidden yet critical origin for the low performance of FASn⁢I3-based devices and highlight the significance of controlling the hydrogen environment in the development of broad high-efficiency nontoxic halide perovskite device applications.

Hydrogen-anion-induced carrier recombination in MAPbI3 perovskite solar cells

Fri, 01 Jan 2021 00:00:00 GMT

Hydrogen-anion-induced carrier recombination in MAPbI3 perovskite solar cells Liang, Yuhang; Cui, Xiangyuan; Li, Feng; Stampfl, Catherine; Huang, Jun; Ringer, Simon Peter; Zheng, Rongkun Identification and passivation of defect-induced electron-hole recombination centers are currently crucial for improving the efficiency of hybrid perovskite solar cells. Besides general intrinsic defects, experimental reports have indicated that hydrogen interstitials are also abundant in hybrid perovskite layers; however, few reports have evaluated the effect of such defects on the charged recombination and device efficiencies. Here, we reveal that under 𝐼-poor synthesis conditions, the negatively charged monoatomic hydrogen interstitial, H_i-, will form in the prototypical CH3NH3PbI3 perovskite layer, acting as a detrimental deep-level defect, which leads to efficient electron-hole recombination and lowers the cell performance. We further rationalize that Br doping can mitigate the large atomic displacement caused by the presence of H_i-, and hence suppress the formation of the deep localized state. The results advance the knowledge of the deep-level defects in hybrid perovskites and provide useful information for enhancing solar cell performance by defect engineering.

Twenty years of PMI’s Pulse of the Profession (2006–2025): A review

Fri, 26 Sep 2025 00:00:00 GMT

Twenty years of PMI’s Pulse of the Profession (2006–2025): A review Zhangguan, Waner This review examines two decades of the Project Management Institute’s Pulse of the Profession series (2006–2025), the flagship global survey of project, program, and portfolio management. Forty reports were analysed, comprising 14 annual global editions, 23 thematic studies, and three practitioner-focused outputs. The findings show that Pulse has served both as an industry barometer and as an advocacy instrument. While the central message across all editions is consistent, poor project management wastes resources, the framing of this message has shifted over time: from cost-and-control narratives to capability-driven emphases on agility, digital fluency, power skills, and business acumen. Using text mining (Voyant Tools) and qualitative coding (ATLAS.ti), the study identifies five clusters of project management approaches, governance, process, adaptive, people-centred, and purpose-driven, and traces how PMI’s discourse has repositioned project management as a strategic, human-centred discipline with societal impact. The analysis underscores the value of Pulse as a directional indicator of industry priorities, while also highlighting its limitations as empirical evidence due to shifting metrics, selective transparency, and advocacy framing. For scholarship, this review offers the first comprehensive synthesis of the Pulse series. For practice, it reinforces the importance of governance, agility, and people skills in sustaining performance. For doctoral research, it provides both a typology and a conceptual scaffold for examining how project management approaches contribute to the sustainability and scalability of public health programs.

Exploring the Intersection of Public Health and Project Management: Insights, Trends, Gaps, and Future Directions—A Narrative Review of Leading Project Management Journals

Mon, 14 Jul 2025 00:00:00 GMT

Exploring the Intersection of Public Health and Project Management: Insights, Trends, Gaps, and Future Directions—A Narrative Review of Leading Project Management Journals Zhangguan, Waner As public health initiatives increasingly adopt project-based structures to address complex societal challenges, there remains limited understanding of how project management practices are applied within this domain. This narrative literature review explores how public health has been represented and managed in the project management research field by analyzing 11 peer-reviewed studies from three leading project management journals: International Journal of Project Management, Project Management Journal, and International Journal of Managing Projects in Business. Drawing on SANRA guidelines to ensure methodological rigor, the review identifies key themes across selected studies, including stakeholder engagement, systems integration, and context-specific adaptation. Findings reveal that while project management approaches—such as change management, iterative planning, and action research—are increasingly used in health-related contexts, they often lack alignment with public health theory, long-term sustainability strategies, and sociopolitical considerations. The review highlights substantial gaps, including the minimal involvement of public health professionals, limited use of interdisciplinary frameworks, and insufficient evaluation of scalability and sustainability outcomes. By mapping current trends, exposing conceptual and methodological shortcomings, and outlining directions for future research, this review provides a foundation for strengthening the integration of project management practices in advancing sustainable and scalable public health interventions.

Thermal cycling resets the irreversible liquid-to-solid transition of peptide condensates during aging

Wed, 01 Jan 2025 00:00:00 GMT

Thermal cycling resets the irreversible liquid-to-solid transition of peptide condensates during aging Anwar, Abel; Li, Tianchen; Shen, Yi The ability of biomolecular condensates to reversibly dissolve and reform is crucial for maintaining cellular stability and functions. In the context of cell physiology and disease, they can serve as a metastable phase mediating the liquid-to-solid transition of disease proteins or rapidly assemble/disassemble as a mechanism for stress response. However, as metabolic rates decline with aging, the protein-rich condensates persist longer therefore increasing the propensity of undergoing irreversible liquid-to-solid transitions. Temperature, as a physical stimulus, plays a key role in controlling condensate formation, dissolution, and material properties. In this study, we explore how the reversibility of short peptide biomolecular condensates (z-FF) can be modulated by temperature change. Our findings reveal that aged condensates exhibit reduced responsiveness to external temperature stimuli. By using thermal cycling experiments to simulate repeated heat stress, we found that the time taken for irreversible fiber formation could be delayed up to 4.7-fold compared to condensates without thermal cycles. We also found the dissolution rate of condensates progressively slows as they age but remain more stable with thermal cycles. Importantly, our results indicate that continuous cycles of liquid-liquid phase separation and dissolution act as a reset mechanism, preserving the biomolecular condensates from further liquid-to-solid transition. These findings provide valuable insights into how aging impacts condensate behavior and highlight potential strategies to preserve cellular function through controlled phase transitions.

Visualizing active species in CO2 electroreduction

Mon, 01 Jan 2024 00:00:00 GMT

Visualizing active species in CO2 electroreduction Yang, Yu; Shi, Yaohui; Li, Fengwang Understanding the evolution of Cu-based catalysts during electrochemical CO2 reduction (ECR) remains challenging. The study by Lim et al. in Joule devises an operando scanning transmission X-ray microscopy to investigate the dynamic phase transformations of Cu catalysts and reveals that Cu2+ species play a crucial role in enhancing C–C coupling. The findings inform the authors of an approach to dynamically redirect the oxidation state of Cu, achieving, as a result, higher selectivity and efficiency for ECR catalysis.

Rapid Analysis: Character AI & Children

Tue, 29 Apr 2025 00:00:00 GMT

Rapid Analysis: Character AI & Children Blake, Annabel; Carter, Marcus; Velloso, Eduardo This rapid analysis examines Character AI, a multimodal chatbot platform that has rapidly grown to over 20 million monthly active users, many of whom are under 18. Unlike productivity-focused AI tools, Character AI frames itself as an "AI entertainment company," offering user-generated characters for a range of purposes: from creative assistants, to games, to emotional support characters, to fantasy role-playing and more. Our audit highlights the platform’s unique dynamics: weak age verification, evolving youth-driven use cases that are signals for innovation (i.e. roleplay and 'comfort bots'), and platform risks. While Character AI enables creative and expressive play, it also presents new regulatory challenges. We identify critical gaps in youth protections, explore opportunities for youth-centered co-design, and propose action starters for policymakers seeking to balance innovation with safety in this new digital landscape.

Supplementary data for "Vortices and antivortices in antiferroelectric PbZrO3"

Thu, 27 Mar 2025 00:00:00 GMT

Supplementary data for "Vortices and antivortices in antiferroelectric PbZrO3" Liu, Ying TEM data for "Vortices and antivortices in antiferroelectric PbZrO3"

How to Be a Uni Tutor

Thu, 06 Feb 2025 00:00:00 GMT

How to Be a Uni Tutor Elmasry, Jacob How to Be a Uni Tutor by Jacob Elmasry goes through over 20 ideas and considerations that Good University tutors think about when tutoring their subjects. These topics range from the motivations of why tutors teach, to the practicalities of preparing for tutorials and even to the question of how responsible a tutor is for the marks of their students! The book lays out some of the reasoning and practices behind the Author’s own tutoring approaches, but also invites the reader to think critically about what is being suggested and to make their own informed decisions on their personal teaching style. The author frequently draws on his own experience tutoring 25 different tutorial classes for 10 unique courses over a 4-year period to illustrate the points he makes throughout the book. The author has also been Highly Commended by the University of Sydney for Outstanding Tutoring during this time period, an achievement that he received due to his passionate teaching and his desire to share his learnings with others.

Data from: Differences in government support for private sector climate change adaptation in developing versus developed countries

Fri, 24 Jan 2025 00:00:00 GMT

Data from: Differences in government support for private sector climate change adaptation in developing versus developed countries Bartelet, Henry A. This data publications contains the dataset used in the journal manuscript tentatively titled as "Differences in government support for private sector climate change adaptation in developing versus developed countries".

Ecological networks among key target fish species in Kenya (2015-2022).

Fri, 24 Jan 2025 00:00:00 GMT

Ecological networks among key target fish species in Kenya (2015-2022). Barnes, Michele L.; Graham, Nicholas A. J.; McClanahan, Tim; Matous, Petr; Bartelet, Henry A. Trophic interactions (i.e., predator-prey relationships) among target fish species comprising the majority of catch by all fishing gears employed along the Kenyan coast.

Automatic left ventricular cavity segmentation via deep spatial sequential network in 4D computed tomography

Fri, 01 Jan 2021 00:00:00 GMT

Automatic left ventricular cavity segmentation via deep spatial sequential network in 4D computed tomography Guo, Yuyu; Bi, Lei; Zhu, Zhengbin; Feng, Dagan David; Zhang, Ruiyan; Wang, Qian; Kim, Jinman Automated segmentation of left ventricular cavity (LVC) in temporal cardiac image sequences (consisting of multiple time-points) is a fundamental requirement for quantitative analysis of cardiac structural and functional changes. Deep learning methods for segmentation are the state-of-the-art in performance; however, these methods are generally formulated to work on a single time-point, and thus disregard the complementary information available from the temporal image sequences that can aid in segmentation accuracy and consistency across the time-points. In particular, single time-point segmentation methods perform poorly in segmenting the end-systole (ES) phase image in the cardiac sequence, where the left ventricle deforms to the smallest irregular shape, and the boundary between the blood chamber and the myocardium becomes inconspicuous and ambiguous. To overcome these limitations in automatically segmenting temporal LVCs, we present a spatial sequential network (SS-Net) to learn the deformation and motion characteristics of the LVCs in an unsupervised manner; these characteristics are then integrated with sequential context information derived from bi-directional learning (BL) where both chronological and reverse-chronological directions of the image sequence are used. Our experimental results on a cardiac computed tomography (CT) dataset demonstrate that our spatial-sequential network with bi-directional learning (SS-BL-Net) outperforms existing methods for spatiotemporal LVC segmentation.

USyd Cassowary Dataset

Fri, 30 Aug 2024 00:00:00 GMT

USyd Cassowary Dataset Shan, Mao; Li, Kunming; Worrall, Stewart This is a sample dataset collected in the Queensland Department of Transport and Main Roads (TMR) project "Development and Performance Testing of a LAARMA---Large Animal Activated Roadside Monitoring and Alert System" in 2024.

Access, the Built Environment, and Behavior

Mon, 01 Jan 2024 00:00:00 GMT

Access, the Built Environment, and Behavior Wu, Hao; Levinson, David Matthew Access is an essential component of the built environment that measures the ease of reaching desired destinations; the level of access is a combined result from both land use and transport infrastructure. Other facets of the built environment include density, street design, pedestrian and bike infrastructure, policy, etc. Individual travel behaviour is shaped in part by the built environment, which has implications for both the well-being of individuals, and the sustainability and vitality of a city. The built environment of a city is in a continuous state of change; developments in Information and Communications Technology (ICT), and work-from-home (WFH) have the potential to redefine the meaning of the built environment, and access. This chapter discusses the evolving interaction between access, the built environment, and travel and activity patterns, and what these changes would mean for the future of transport.

Promoting electrocatalytic CO2 methanation using a molecular modifier on Cu surfaces

Sat, 01 Jan 2022 00:00:00 GMT

Promoting electrocatalytic CO2 methanation using a molecular modifier on Cu surfaces Wang, Cheng; Kong, Xiangdong; Huang, Junming; Yang, Yu; Zheng, Han; Wang, Huijuan; Dai, Suiyang; Zhang, Shuzhen; Liang, Yongxiang; Geng, Zhigang; Li, Fengwang; Zeng, Jie The electroreduction of CO2 to methane using renewable energy is a promising approach to achieving carbon neutrality. At commercially relevant current densities (>200 mA cm−2), methane selectivity is however below 50%. Herein, we reported a benzenethiol-modified Cu nanoparticle catalyst that achieved a methane faradaic efficiency of 54.5% at a partial current density of 383 mA cm−2, 1.9-fold higher than that of Cu nanoparticle controls. In situ vibrational spectroscopy and density functional theory calculations showed that the benzenethiol modulated the electronic structure of the Cu surface to enable a lowered coverage of *CO, favouring the formation of *CHO, a key intermediate embarking on the CH4 pathway, over the competing carbon–carbon coupling, the pathway towards multicarbons.

In situ characterisation for nanoscale structure–performance studies in electrocatalysis

Sun, 01 Jan 2023 00:00:00 GMT

In situ characterisation for nanoscale structure–performance studies in electrocatalysis Xia, Tianlai; Yang, Yu; Song, Qiang; Luo, Mingchuan; Xue, Mianqi; Ostrikov, Kostya (Ken); Zhao, Yong; Li, Fengwang Recently, electrocatalytic reactions involving oxygen, nitrogen, water, and carbon dioxide have been developed to substitute conventional chemical processes, with the aim of producing clean energy, fuels and chemicals. A deepened understanding of catalyst structures, active sites and reaction mechanisms plays a critical role in improving the performance of these reactions. To this end, in situ/operando characterisations can be used to visualise the dynamic evolution of nanoscale materials and reaction intermediates under electrolysis conditions, thus enhancing our understanding of heterogeneous electrocatalytic reactions. In this review, we summarise the state-of-the-art in situ characterisation techniques used in electrocatalysis. We categorise them into three sections based on different working principles: microscopy, spectroscopy, and other characterisation techniques. The capacities and limits of the in situ characterisation techniques are discussed in each section to highlight the present-day horizons and guide further advances in the field, primarily aiming at the users of these techniques. Finally, we look at challenges and possible strategies for further development of in situ techniques.

Gas permeability through swelling porous media: Insights from coarse-grained pore-scale simulations

Thu, 21 Mar 2024 00:00:00 GMT

Gas permeability through swelling porous media: Insights from coarse-grained pore-scale simulations Wu, Jian; Gan, Yixiang; Huang, Pengyu; Shen, Luming Sorption-induced swelling can decrease porosity and permeability of the porous medium, affecting the long-term injectivity in rock matrix during CO2 geologic storage. This study employs an innovative coarse-grained model to integrate fluid flow with solid deformation at the pore-scale, exploring gas permeability within swelling nanoporous media. The nanoporous media are composed of spherical pores between 35.4 nm and 106.2 nm to represent pore networks embedded within organic matter. Gas transport is initiated by creating a pressure gradient between two gas reservoirs placed at the two sides of the nanoporous structure. The results indicate that solid swelling (~40%) can significantly decrease permeability (up to 100%). Gas permeability curves demonstrate a linear decline with the increasing gas-solid interaction energy in both swelling and non-swelling porous media, with solid swelling exerting a greater influence on permeability. Surprisingly, in the regime of weak gas-solid interactions, the porosity and permeability of flexible porous media increase, possibly caused by gas flow-induced pore throat opening. It is found that nanoporous media with lower initial porosity experience a greater permeability decline during swelling. The relationship between permeability and porosity changes shows a linear increase characterized by different slopes with varying initial porosities, whilst it is also impacted by pore size distributions. These findings provide valuable insights into the complex interactions among gas transport, solid deformation, and porosity changes in nanoporous media, with implications for understanding and optimizing gas production and storage in realistic geological environments.

Optimization of random silica-polymethylpentene (TPX) radiative coolers towards substantial cooling capacity

Sat, 01 Jan 2022 00:00:00 GMT

Optimization of random silica-polymethylpentene (TPX) radiative coolers towards substantial cooling capacity Feng, JIe; Gao, Kai; Jiang, Yue; Ulpiani, Giulia; Krajcic, Djordje; Paolini, Riccardo; Ranzi, Gianluca; Santamouris, Mattheos In the context of global warming, radiative coolers with high solar reflectance and strong emissivity in the atmospheric window can cool the substrate as well as the ambient air. Silica at its nano or micro-scale being randomly dispersed into a uniform transparent polymer can form scalable radiative coolers for large-scale application. Promising cooling performance has been reported for silica-polymers compared with conventional cooling materials, but their performance can be largely influenced by various fabrication parameters. So far, how fabrication parameters influence the emissivity and the cooling performance has not been experimentally demonstrated and the cooling capacity of silica-polymers reported was not substantial compared to other superior radiative coolers. In this work, random silica-polymer has been optimized experimentally. Lab measurement and experimental testing of six fabricated silica-polymers under subtropical and desert climates indicated that due to the complexity of the thermo-radiative balance, high emissivity and strong selectivity are both indispensable in the production of high cooling power. If combined with superior reflectors with higher solar reflectance and especially the emissivity in 8–13 μm enhancing the heat dissipation ability, substantial cooling capacity can be achieved: under the harsh desert climate with average peak solar radiation over 1100 Wm-2, the combination presented sub-ambient temperature of maximum 4.7 ◦C when air temperature reached its peak and the maximum daytime and night-time sub-ambient temperatures were 12.5 ◦C and 15.9 ◦C respectively.

Expanding the applicability of daytime radiative cooling: Technological developments and limitations

Fri, 01 Jan 2021 00:00:00 GMT

Expanding the applicability of daytime radiative cooling: Technological developments and limitations Ulpiani, Giulia; Ranzi, Gianluca; Feng, Jie; Santamouris, Mattheos Daytime radiative cooling is regarded as the gold promise of future sustainable building energy systems and a breakthrough in the fight against local climate change. Despite the fervid research interest, most literature reports exceptional theoretical performances under ideal, desert-like conditions, but overlooks the cooling impairment that occurs under low atmospheric transparency (cloudy, humid, polluted conditions) and reduced sky access (packed urban contexts). Power recovery and stabilization call for decoupling of incoming and outgoing radiation at equal wavelengths. Enhanced directionality and high-contrast, broadband asymmetric transmission have been recently proposed to expand the applicability of radiative coolers over a wider spectrum of climates, weathers and terrains. This review offers itself as a first, timely synthesis of the current technological arena. Physical principles, materials and designs, collected from a variety of applicative fields, are detailed and discussed in terms of performance and feasibility, to inspire the transition into sustainable building cooling, worldwide. Major grey areas and serious concerns on potential violations of the 2nd law of thermodynamics reinforce the need for experimental demonstrations in future research.

On the energy modulation of daytime radiative coolers: A review on infrared emissivity dynamic switch against overcooling

Wed, 01 Jan 2020 00:00:00 GMT

On the energy modulation of daytime radiative coolers: A review on infrared emissivity dynamic switch against overcooling Ulpiani, Giulia; Ranzi, Gianluca; Shah, Kwok Wei; Feng, Jie; Santamouris, Mattheos Passive daytime radiative cooling represents one of the boldest answers to tackle the future cooling needs of the built environment and to mitigate urban heat island effects. Recent developments in the field targeted subambience with several successful examples. On the other side, heating demands may get exacerbated unless effective countermeasures against overcooling are identified, especially in wintertime or heating-dominated climates. This review aims at collecting state-of-the-art technologies and techniques to dynamically control the heat transfer to and from the radiative emitter and ultimately modulate its cooling capacity. Potential solutions are selected from different applicative fields, including spacecraft thermal control, thermal camouflage and electronics. Environmentally-responsive solutions are analyzed in depth given their perfect match with radiative cooling design requirements. Among them, VO2-tuned Fabry-Perot resonators are given particular emphasis, owing to their proven applicability. Active solutions are presented for completeness, but in less detail. Underlying principles, structural composition and experimental/simulated results are detailed and discussed to identify prominent pathways towards technically and economically effective integration in the built environment.

A Web-Based Medical Multimedia Visualisation Interface for Personal Health Records

Tue, 01 Jan 2013 00:00:00 GMT

A Web-Based Medical Multimedia Visualisation Interface for Personal Health Records de Ridder, Michael; Constantinescu, Liviu; Bi, Lei; Jung, Youn Hyun; Kumar, Ashnil; Kim, Jinman; Feng, David Dagan; Fulham, Michael The healthcare industry has begun to utilise web-based systems and cloud computing infrastructure to develop an increasing array of online personal health record (PHR) systems. Although these systems provide the technical capacity to store and retrieve medical data in various multimedia formats, including images, videos, voice, and text, individual patient use remains limited by the lack of intuitive data representation and visualisation techniques. As such, further research is necessary to better visualise and present these records, in ways that make the complex medical data more intuitive. In this study, we present a web-based PHR visualisation system, called the 3D medical graphical avatar (MGA), which was designed to explore web based delivery of a wide array of medical data types including multi-dimensional medical images; medical videos; text-based data; and spatial annotations. Mapping information was extracted from each of the data types and was used to embed spatial and textual annotations, such as regions of interest (ROIs) and time-based video annotations. Our MGA itself is built from clinical patient imaging studies, when available. We have taken advantage of the emerging web technologies of HTML5 and WebGL to make our application available to a wider base of users and devices. We analysed the performance of our proof-of concept prototype system on mobile and desktop consumer devices. Our initial experiments indicate that our system can render the medical data in a fashion that enables interactive navigation of the MGA.

Visibility-driven PET-CT Visualisation with Region of Interest (ROI) Segmentation

Tue, 01 Jan 2013 00:00:00 GMT

Visibility-driven PET-CT Visualisation with Region of Interest (ROI) Segmentation Jung, Younhyun; Kim, Jinman; Eberl, Stefan; Fulham, Michael; Feng, David Dagan Multi-modality positron emission tomography – computed tomography (PET-CT) visualises biological and physiological functions (from PET) as region of interests (ROIs) within a higher resolution anatomical reference frame (from CT). The need to efficiently assess and assimilate the information from these co-aligned volumes simultaneously has stimulated new visualisation techniques that combine 3D volume rendering with interactive transfer functions to enable efficient manipulation of these volumes. However, in typical multi-modality volume rendering visualisation, the transfer functions for the volumes are manipulated in isolation with the resulting volumes being fused, thus failing to exploit the spatial correlation that exists between the aligned volumes. Such lack of feedback makes multi-modality transfer function manipulation to be complex and time-consuming. Further, transfer function alone is often insufficient to select the ROIs when it comprises of similar voxel properties to those of non-relevant regions. In this study, we propose a new ROI-based multi-modality visibility-driven transfer function (m2-vtf) for PET-CT visualisation. We present a novel ‘visibility’ metrics, a fundamental optical property that represents how much of the ROIs are visible to the users, and use it to measure the visibility of the ROIs in PET in relation to how it is affected by transfer function manipulations to its counterpart CT. To overcome the difficulty in ROI selection, we provide an intuitive ROIs selection tool based on automated PET segmentation. We further present a multi-modality transfer function automation where the visibility metrics from the PET ROIs are used to automate its CT’s transfer function. Our GPU implementation achieved an interactive visualisation of multi-modality PET-CT with efficient and intuitive transfer function manipulations.

A systematic review on incentive-driven mHealth technology: As used in diabetes management

Fri, 01 Jan 2016 00:00:00 GMT

A systematic review on incentive-driven mHealth technology: As used in diabetes management de Ridder, Michael; Kim, Jinman; Jing, Yan; Khadra, Mohamed; Nanan, Ralph Introduction Mobile Health (mHealth) technologies have been shown to improve self-management of chronic diseases, such as diabetes. However, mHealth tools, such as Apps, often have low rates of retention, eroding their potential benefits. Using incentives is a common mechanism for engaging and retaining patients that is applied by mHealth tools. We conducted a systematic review aiming to categorise the different types of incentive mechanisms employed in mHealth tools for diabetes management, which we defined as Incentive-driven Technologies (IDTs). As an auxiliary aim, we also analysed barriers to adoption of IDT technologies. Methods Literature published in English between January 2008 and August 2014 was identified through searching leading publishers and indexing databases: IEEE, Springer, Science Direct, NCBI, ACM, Wiley and Google Scholar. Results A total of 42 articles were selected. Of these, 34 presented mHealth tools with IDT mechanisms. Many of these contained more than one IDT, with Education the most common (n=21), followed by Reminder (n=11), Feedback (n=10), Social (n=8), Alert (n=5), Gamification (n=3), and Financial (n=2). The remaining 8 articles were review papers and a qualitative study of focus groups and interviews with patients with diabetes, where no new technologies were proposed, from which we defined barriers for adoption. Discussion We identified that while mHealth technologies have advanced over the last 5 years, the core IDT mechanisms have remained consistent. Instead, IDT mechanisms have evolved with the upgrades in technology, such as moving from manual to automatic content delivery and personalisation of content.

Topology-guided deformable registration with local importance preservation for biomedical images

Mon, 01 Jan 2018 00:00:00 GMT

Topology-guided deformable registration with local importance preservation for biomedical images Zheng, Chaojie; Wang, Xiuying; Zeng, Shan; Zhou, Jianlong; Yin, Yong; Feng, Dagan; Fulham, Michael The demons registration (DR) model is well recognized for its deformation capability. However, it might lead to misregistration due to erroneous diffusion direction when there are no overlaps between corresponding regions. We propose a novel registration energy function, introducing topology energy, and incorporating a local energy function into the DR in a progressive registration scheme, to address these shortcomings. The topology energy that is derived from the topological information of the images serves as a direction inference to guide diffusion transformation to retain the merits of DR. The local energy constrains the deformation disparity of neighbouring pixels to maintain important local texture and density features. The energy function is minimized in a progressive scheme steered by a topology tree graph and we refer to it as topology-guided deformable registration (TDR). We validated our TDR on 20 pairs of synthetic images with Gaussian noise, 20 phantom PET images with artificial deformations and 12 pairs of clinical PET-CT studies. We compared it to three methods: (1) free-form deformation registration method, (2) energy-based DR and (3) multi-resolution DR. The experimental results show that our TDR outperformed the other three methods in regard to structural correspondence and preservation of the local important information including texture and density, while retaining global correspondence.

A New Aggregation of DNN Sparse and Dense Labeling for Saliency Detection

Fri, 01 Jan 2021 00:00:00 GMT

A New Aggregation of DNN Sparse and Dense Labeling for Saliency Detection Yan, Ke; Wang, Xiuying; Kim, Jinman; Feng, Dagan As a fundamental requirement to many computer vision systems, saliency detection has experienced substantial progress in recent years based on deep neural networks (DNNs). Most DNN-based methods rely on either sparse or dense label- ing, and thus they are subject to the inherent limitations of the chosen labeling schemes. DNN dense labeling captures salient objects mainly from global features, which are often hampered by other visually distinctive regions. On the other hand, DNN sparse labeling is usually impeded by inaccurate presegmentation of the images that it depends on. To address these limitations, we propose a new framework consisting of two pathways and an Aggregator to progressively integrate the DNN sparse and DNN dense labeling schemes to derive the final saliency map. In our “zipper” type aggregation, we propose a multiscale ker- nels approach to extract optimal criteria for saliency detection where we suppress nonsalient regions in the sparse labeling while guiding the dense labeling to recognize more complete extent of the saliency. We demonstrate that our method outperforms in saliency detection compared to other 11 state-of-the-art methods across six well-recognized benchmarking datasets.

Short-Term Lesion Change Detection for Melanoma Screening With Novel Siamese Neural Network

Fri, 01 Jan 2021 00:00:00 GMT

Short-Term Lesion Change Detection for Melanoma Screening With Novel Siamese Neural Network Zhang, Boyan; Wang, Zhiyong; Gao, Junbin; Rutjes, Chantal; Nufer, Kaitlin; Tao, Dacheng; Feng, David Dagan; Menzies, Scott Short-term monitoring of lesion changes has been a widely accepted clinical guideline for melanoma screening. When there is a significant change of a melanocytic lesion at three months, the lesion will be excised to exclude melanoma. However, the decision on change or no-change heavily depends on the experience and bias of individual clinicians, which is subjective. For the first time, a novel deep learning based method is developed in this paper for automatically detecting short-term lesion changes in melanoma screening. The lesion change detection is formulated as a task measuring the similarity between two dermoscopy images taken for a lesion in a short time-frame, and a novel Siamese structure based deep network is proposed to produce the decision: changed (i.e. not similar) or unchanged (i.e. similar enough). Under the Siamese framework, a novel structure, namely Tensorial Regression Process, is proposed to extract the global features of lesion images, in addition to deep convolutional features. In order to mimic the decision-making process of clinicians who often focus more on regions with specific patterns when comparing a pair of lesion images, a segmentation loss (SegLoss) is further devised and incorporated into the proposed network as a regularization term. To evaluate the proposed method, an in-house dataset with 1,000 pairs of lesion images taken in a short time-frame at a clinical melanoma centre was established. Experimental results on this first-of-a-kind large dataset indicate that the proposed model is promising in detecting the short-term lesion change for objective melanoma screening.

Automated Analysis of Chest Radiographs for Cystic Fibrosis Scoring

Mon, 01 Jan 2018 00:00:00 GMT

Automated Analysis of Chest Radiographs for Cystic Fibrosis Scoring Huang, Zhaowei; Ding, Chen; Zhang, Lei; Lee, Min-Zhao; Song, Yang; Selvadural, Hiran; Feng, Dagan; Zhang, Yanning; Cai, Weidong We present a framework to analyze chest radiographs for cystic fibro-sis using machine learning methods. We compare the representational power of deep learning features with traditional texture features. Specifically, we respec-tively employ VGG-16 based deep learning features, Tamura and Gabor filter based textural features to represent the cystic fibrosis images. We demonstrate that VGG-16 features perform best, with a maximum agreement of 82%. In ad-dition, due to limited dimensionality, Tamura features for unsegmented images achieve no more than 50% agreement; however, after segmentation, the accuracy of Tamura can reach 78%. In combination with using the deep learning features, we also compare back propagation neural network and sparse coding classifiers to the typical SVM classifier with polynomial kernel function. The result shows that neural network and sparse coding classifiers outperform SVM in most cases. Only with insufficient training samples does SVM demonstrate higher accuracy.

Nuclei instance segmentation with dual contour-enhanced adversarial network

Mon, 01 Jan 2018 00:00:00 GMT

Nuclei instance segmentation with dual contour-enhanced adversarial network Zhang, Donghao; Song, Yang; Liu, Siqi; Feng, Dagan; Wang, Yue; Cai, Weidong The morphology of cancer cells is widely used by pathologists to grade stages of cancers. Accurate cancer cell segmentation is significant to obtain quantitative diagnosis. We proposed a dual contour-enhanced adversarial network to solve this challenge. The dual contour-enhanced masks and adversarial network are incorporated to improve individual cell segmentation capability. By evaluating quantitative individual cell segmentation results on 2017 MICCAI Digital Pathology Challenge, our method achieved best balance between precision and recall rate of individual cell segmentation compared to state-of-the-art cell segmentation methods.

Cross-cohort dementia identification using transfer learning with FDG-PET imaging

Mon, 01 Jan 2018 00:00:00 GMT

Cross-cohort dementia identification using transfer learning with FDG-PET imaging Lu, Shen; Xia, Yong; Cai, Weidong; Feng, Dagan; Fulham, Michael Machine learning techniques have been extensively adapted to dementia identification with PET imaging in the last decade. Despite the promising results reported by these studies, the accurately labeled PET brain scans used to train machine learning models are generally difficult to obtain in real clinic environments. To tackle this challenge, we proposed a dementia classification method inspired by transfer learning. The main idea is to train a machine learning model using an accurately labeled source image cohort and an unlabeled target image cohort jointly, and then use this model to label the unlabeled target cohort. We demonstrated the effectiveness of the knowledge transfer in dementia classification tasks by comparing the proposed method to several other methods on public and private image cohorts.

Automated Multi-Stage Segmentation of White Blood Cells Via Optimizing Color Processing

Sun, 01 Jan 2017 00:00:00 GMT

Automated Multi-Stage Segmentation of White Blood Cells Via Optimizing Color Processing Tareef, Afaf; Song, Yang; Feng, Dagan; Chen, Mei; Cai, Weidong Segmentation of white blood cells (i.e. leukocytes) is a crucial step toward the development of haematological images analysis of peripheral blood smears due to the complex nature of the different types of white blood cells and their large variations in shape, texture, color, and density. This study addresses this issue and presents a single fully automatic segmentation framework for both nuclei and cytoplasm of the five classes of leukocytes in a microscope blood smears. The proposed framework integrates a priori information of enhanced nuclei color with Gram-Schmidt orthogonalization, and multi-scale morphological enhancement to localize the nuclei, whereas clustering-based seed extraction and watershed are utilized to segment the cytoplasm. The experimental results on two different datasets show that the proposed method works successfully for both nuclei and cytoplasm segmentation, and achieves more accurate segmentation results compared to the other methods in the literature.

Dataset for "Growth and metabolism of Chromera velia under hypercapnia": Chromeria velia under 10% CO2

Tue, 16 Aug 2022 00:00:00 GMT

Dataset for "Growth and metabolism of Chromera velia under hypercapnia": Chromeria velia under 10% CO2 Rahem, Shymma Chromera velia, also known as Chromerid, is a spherical golden-brown alga discovered a decade ago by coincidence while examining coral symbionts in Australia, Sydney , the Great Barrier Reef, Australia. Chromera velia has a unique evolutionary position between two different species of dinoflagellates and apicomplexans. Being relatively newly discovered, C. velia is still not fully studied, with previous work focusing on understanding its physical and ecological structures, phylogenetic analysis, and the missing linkage of C. velia and other related species. This thesis extends previous knowledge by exploring environmental factors and responses to increases in CO2 concentration (hypercapnia) (10% and 20%) and light intensities (50, 220, 2,850 lx) on C. velia’s growth in incubated flasks; the light intensity (36, 54, 72 klx) effect on the growth of C. velia in aerated bioreactors was also examined. Atmospheric CO2 concentration was the reference CO2 condition for the effect of hypercapnia, and darkness was the reference condition for the effect of light intensity. These cultures were used to determine the optimal conditions for growth in incubated flasks culture by modelling. The harvested C. velia were analysed to identify bioactive metabolites (carotenoids and fatty acids) because of their influence on human health. The effect of environmental conditions on the carotenoids and fatty acids (FAs) was studied to find the conditions for maximum production. Another aim of this work was to analyse the motility state of C. velia in darkness and hypercapnia (5%, 10%, 20% CO2) under light and time-lapse confocal microscopies, to investigate the initiation time and proportion of flagellation. New morphological features of C. velia were also highlighted. The results of the environmental factors study showed that hypercapnia has a negative effect on the growth of C. velia, yet this alga can still thrive at 10% CO2. Increasing the light intensity elevated the growth rate. Combining the high light intensity with hypercapnia has a significant positive impact on slowing down the decrease in growth rate under hypercapnia. The saturating light is found at the maximum tested light intensities of 2,850 lx in incubated flask culture and 36 klx in aerated bioreactor culture. Under light intensity 2,565 lx and 7% CO2, the near-optimal growth rate was determined to be 0.0415 day-1 with a model validation error of 10%. These findings show that combining hypercapnia with light irradiance helps C. velia adapt to high CO2 levels. This could make C. velia applicable to CO2 absorption from industrial flue gas streams (e.g., power plant emissions) via the incorporation of bioremediation-mitigation algal ponds, therefore contributing to directed efforts to combat global warming. For carotenoids, when investigating the effect of different hypercapnia levels and light intensities on the xanthophyll cycle, both factors were found to have a positive correlation with zeaxanthin but a negative impact on violaxanthin concentration. The maximum zeaxanthin production was identified in incubated flasks to be 1.8×106 ng/ml at 2,850 lx and 20% CO2 and in aerated bioreactor cultures to be 6.7×105 ng/ml in the light intensity range of 36 54 klx. The fatty acid (FA) analysis revealed that the fatty acid profile of C. velia has mostly C18 and C20 components, of which polyunsaturated fatty acids (PUFA) were the most prevalent. Eicosapentaenoic acid (EPA) is found to be the major fatty acid in PUFA. Increasing hypercapnia to 10% has a favourable effect on FAs, as does increasing light intensity. Hypercapnia and light have an interacting effect on C. velia, as evidenced by the FA uneven patterns. Despite the difficulties in understanding the behaviour of FAs in microalgae in general, which has been documented in the literature, a clear image of the ideal C. velia culture conditions for maximum accumulation of each FA component in both incubated flasks and aerated bioreactors could still be seen. Based on the results in this study at lab scale, C. velia was found to be a suitable candidate for commercial scale-up of zeaxanthin and FA synthesis, as well as a solution for industrial gaseous CO2 emissions. An important finding is that zeaxanthin has a direct influence on fatty acid desaturation under elevated hypercapnia. As a result of zeaxanthin increasing the fluidity of the cell beyond its capability, the alga produces SFA to enhance the rigidity of the membrane as a protective mechanism. Chromera velia produced a substantial amount of EPA, suggesting that it may be exploited for commercial EPA production on land. Finally, even though research on C. velia is still in its early stages, the findings of the metabolites analysis reveal a strong link between the increase in zeaxanthin and the degree of FA desaturation in C. velia. According to literature, increasing zeaxanthin increases membrane fluidity in the ordered phase while lowering fluidity in the liquid crystalline phase of phosphatidylcholine during hypercapnia. Algal mechanisms for resolving the osmotic imbalance caused by variations in the saturated fatty acids (SFA) and polyunsaturated fatty acids (PUFA) ratio (SFA/PUFA) include reduced membrane fluidity and rigidification of the wall structure. In the motility investigation, hypercapnia accelerated the onset of flagellation and increased the proportion of flagellating alga. Flagellation at a proportion of 90% occurred on day 4 at a CO2 concentration of 20%, which is significantly greater than the reference CO2 condition. The metabolic response hypothesis states that when C. velia is exposed to hypercapnia, it increases the amount of lipid or starch in its cells, which are the main sources of energy for flagellate algae in the dark. The observation of C. velia reveals new insights into the ecology and biodiversity of this alga. Investigating C. velia under the microscope revealed several metabolic characteristics similar to green algae and vascular plants, including red-eye, two types of flagellated cells representing two sexual mating cells (eggplant and round shape), and a double cell wall. These are important findings that show the effect of hypercapnia stress on flagellated algae, and the relationship between this alga and other higher plants on the one hand, and flagellated green algae on the other. Aside from that, C. velia's remarkable survival rate under high CO2 settings highlights the alga's enormous potential to lower the CO2 impact of human activities in aquatic environments. As a result, more research is needed to completely comprehend flagellation in the presence of high CO2 concentrations. The current thesis steers future investigations towards application of C. velia in CO2 emission mitigation (algae carbon capture), the production of bioactive valuable components, and wastewater bioremediation. In C. velia at higher CO2 concentration, a greater proportion of the energy required for photosynthesis is dedicated to producing more fatty acids. Increasing the fatty acids in C. velia provides the required energy to flagellate in complete darkness. Chromera velia is proved to be a potential source for the land-based commercial production of zeaxanthin and PUFA, especially EPA. Interestingly, C. velia was found to share several traits with flagellated green algae, namely their metabolic features and the biosynthetic routes to produce zeaxanthin. This work highlights a new morphological finding that could help in further understanding the missing origin path of apicomplexan parasites from their algal ancestors.

Dataset for "Growth and metabolism of Chromera velia under hypercapnia": Chromera velia under hypercapnia 5% CO2

Tue, 16 Aug 2022 00:00:00 GMT

Dataset for "Growth and metabolism of Chromera velia under hypercapnia": Chromera velia under hypercapnia 5% CO2 Rahem, Shymma Chromera velia, also known as Chromerid, is a spherical golden-brown alga discovered a decade ago by coincidence while examining coral symbionts in Australia, Sydney , the Great Barrier Reef, Australia. Chromera velia has a unique evolutionary position between two different species of dinoflagellates and apicomplexans. Being relatively newly discovered, C. velia is still not fully studied, with previous work focusing on understanding its physical and ecological structures, phylogenetic analysis, and the missing linkage of C. velia and other related species. This thesis extends previous knowledge by exploring environmental factors and responses to increases in CO2 concentration (hypercapnia) (10% and 20%) and light intensities (50, 220, 2,850 lx) on C. velia’s growth in incubated flasks; the light intensity (36, 54, 72 klx) effect on the growth of C. velia in aerated bioreactors was also examined. Atmospheric CO2 concentration was the reference CO2 condition for the effect of hypercapnia, and darkness was the reference condition for the effect of light intensity. These cultures were used to determine the optimal conditions for growth in incubated flasks culture by modelling. The harvested C. velia were analysed to identify bioactive metabolites (carotenoids and fatty acids) because of their influence on human health. The effect of environmental conditions on the carotenoids and fatty acids (FAs) was studied to find the conditions for maximum production. Another aim of this work was to analyse the motility state of C. velia in darkness and hypercapnia (5%, 10%, 20% CO2) under light and time-lapse confocal microscopies, to investigate the initiation time and proportion of flagellation. New morphological features of C. velia were also highlighted. The results of the environmental factors study showed that hypercapnia has a negative effect on the growth of C. velia, yet this alga can still thrive at 10% CO2. Increasing the light intensity elevated the growth rate. Combining the high light intensity with hypercapnia has a significant positive impact on slowing down the decrease in growth rate under hypercapnia. The saturating light is found at the maximum tested light intensities of 2,850 lx in incubated flask culture and 36 klx in aerated bioreactor culture. Under light intensity 2,565 lx and 7% CO2, the near-optimal growth rate was determined to be 0.0415 day-1 with a model validation error of 10%. These findings show that combining hypercapnia with light irradiance helps C. velia adapt to high CO2 levels. This could make C. velia applicable to CO2 absorption from industrial flue gas streams (e.g., power plant emissions) via the incorporation of bioremediation-mitigation algal ponds, therefore contributing to directed efforts to combat global warming. For carotenoids, when investigating the effect of different hypercapnia levels and light intensities on the xanthophyll cycle, both factors were found to have a positive correlation with zeaxanthin but a negative impact on violaxanthin concentration. The maximum zeaxanthin production was identified in incubated flasks to be 1.8×106 ng/ml at 2,850 lx and 20% CO2 and in aerated bioreactor cultures to be 6.7×105 ng/ml in the light intensity range of 36 54 klx. The fatty acid (FA) analysis revealed that the fatty acid profile of C. velia has mostly C18 and C20 components, of which polyunsaturated fatty acids (PUFA) were the most prevalent. Eicosapentaenoic acid (EPA) is found to be the major fatty acid in PUFA. Increasing hypercapnia to 10% has a favourable effect on FAs, as does increasing light intensity. Hypercapnia and light have an interacting effect on C. velia, as evidenced by the FA uneven patterns. Despite the difficulties in understanding the behaviour of FAs in microalgae in general, which has been documented in the literature, a clear image of the ideal C. velia culture conditions for maximum accumulation of each FA component in both incubated flasks and aerated bioreactors could still be seen. Based on the results in this study at lab scale, C. velia was found to be a suitable candidate for commercial scale-up of zeaxanthin and FA synthesis, as well as a solution for industrial gaseous CO2 emissions. An important finding is that zeaxanthin has a direct influence on fatty acid desaturation under elevated hypercapnia. As a result of zeaxanthin increasing the fluidity of the cell beyond its capability, the alga produces SFA to enhance the rigidity of the membrane as a protective mechanism. Chromera velia produced a substantial amount of EPA, suggesting that it may be exploited for commercial EPA production on land. Finally, even though research on C. velia is still in its early stages, the findings of the metabolites analysis reveal a strong link between the increase in zeaxanthin and the degree of FA desaturation in C. velia. According to literature, increasing zeaxanthin increases membrane fluidity in the ordered phase while lowering fluidity in the liquid crystalline phase of phosphatidylcholine during hypercapnia. Algal mechanisms for resolving the osmotic imbalance caused by variations in the saturated fatty acids (SFA) and polyunsaturated fatty acids (PUFA) ratio (SFA/PUFA) include reduced membrane fluidity and rigidification of the wall structure. In the motility investigation, hypercapnia accelerated the onset of flagellation and increased the proportion of flagellating alga. Flagellation at a proportion of 90% occurred on day 4 at a CO2 concentration of 20%, which is significantly greater than the reference CO2 condition. The metabolic response hypothesis states that when C. velia is exposed to hypercapnia, it increases the amount of lipid or starch in its cells, which are the main sources of energy for flagellate algae in the dark. The observation of C. velia reveals new insights into the ecology and biodiversity of this alga. Investigating C. velia under the microscope revealed several metabolic characteristics similar to green algae and vascular plants, including red-eye, two types of flagellated cells representing two sexual mating cells (eggplant and round shape), and a double cell wall. These are important findings that show the effect of hypercapnia stress on flagellated algae, and the relationship between this alga and other higher plants on the one hand, and flagellated green algae on the other. Aside from that, C. velia's remarkable survival rate under high CO2 settings highlights the alga's enormous potential to lower the CO2 impact of human activities in aquatic environments. As a result, more research is needed to completely comprehend flagellation in the presence of high CO2 concentrations. The current thesis steers future investigations towards application of C. velia in CO2 emission mitigation (algae carbon capture), the production of bioactive valuable components, and wastewater bioremediation. In C. velia at higher CO2 concentration, a greater proportion of the energy required for photosynthesis is dedicated to producing more fatty acids. Increasing the fatty acids in C. velia provides the required energy to flagellate in complete darkness. Chromera velia is proved to be a potential source for the land-based commercial production of zeaxanthin and PUFA, especially EPA. Interestingly, C. velia was found to share several traits with flagellated green algae, namely their metabolic features and the biosynthetic routes to produce zeaxanthin. This work highlights a new morphological finding that could help in further understanding the missing origin path of apicomplexan parasites from their algal ancestors.

Dataset for "Growth and metabolism of Chromera velia under hypercapnia": Chromera velia alga videos were taken under reference conditions

Fri, 22 Jul 2022 00:00:00 GMT

Dataset for "Growth and metabolism of Chromera velia under hypercapnia": Chromera velia alga videos were taken under reference conditions Rahem, Shymma Abstract Chromera velia, also known as Chromerid, is a spherical golden-brown alga discovered a decade ago by coincidence while examining coral symbionts in Australia, Sydney , the Great Barrier Reef, Australia. Chromera velia has a unique evolutionary position between two different species of dinoflagellates and apicomplexans. Being relatively newly discovered, C. velia is still not fully studied, with previous work focusing on understanding its physical and ecological structures, phylogenetic analysis, and the missing linkage of C. velia and other related species. This thesis extends previous knowledge by exploring environmental factors and responses to increases in CO2 concentration (hypercapnia) (10% and 20%) and light intensities (50, 220, 2,850 lx) on C. velia’s growth in incubated flasks; the light intensity (36, 54, 72 klx) effect on the growth of C. velia in aerated bioreactors was also examined. Atmospheric CO2 concentration was the reference CO2 condition for the effect of hypercapnia, and darkness was the reference condition for the effect of light intensity. These cultures were used to determine the optimal conditions for growth in incubated flasks culture by modelling. The harvested C. velia were analysed to identify bioactive metabolites (carotenoids and fatty acids) because of their influence on human health. The effect of environmental conditions on the carotenoids and fatty acids (FAs) was studied to find the conditions for maximum production. Another aim of this work was to analyse the motility state of C. velia in darkness and hypercapnia (5%, 10%, 20% CO2) under light and time-lapse confocal microscopies, to investigate the initiation time and proportion of flagellation. New morphological features of C. velia were also highlighted. The results of the environmental factors study showed that hypercapnia has a negative effect on the growth of C. velia, yet this alga can still thrive at 10% CO2. Increasing the light intensity elevated the growth rate. Combining the high light intensity with hypercapnia has a significant positive impact on slowing down the decrease in growth rate under hypercapnia. The saturating light is found at the maximum tested light intensities of 2,850 lx in incubated flask culture and 36 klx in aerated bioreactor culture. Under light intensity 2,565 lx and 7% CO2, the near-optimal growth rate was determined to be 0.0415 day-1 with a model validation error of 10%. These findings show that combining hypercapnia with light irradiance helps C. velia adapt to high CO2 levels. This could make C. velia applicable to CO2 absorption from industrial flue gas streams (e.g., power plant emissions) via the incorporation of bioremediation-mitigation algal ponds, therefore contributing to directed efforts to combat global warming. For carotenoids, when investigating the effect of different hypercapnia levels and light intensities on the xanthophyll cycle, both factors were found to have a positive correlation with zeaxanthin but a negative impact on violaxanthin concentration. The maximum zeaxanthin production was identified in incubated flasks to be 1.8×106 ng/ml at 2,850 lx and 20% CO2 and in aerated bioreactor cultures to be 6.7×105 ng/ml in the light intensity range of 36 54 klx. The fatty acid (FA) analysis revealed that the fatty acid profile of C. velia has mostly C18 and C20 components, of which polyunsaturated fatty acids (PUFA) were the most prevalent. Eicosapentaenoic acid (EPA) is found to be the major fatty acid in PUFA. Increasing hypercapnia to 10% has a favourable effect on FAs, as does increasing light intensity. Hypercapnia and light have an interacting effect on C. velia, as evidenced by the FA uneven patterns. Despite the difficulties in understanding the behaviour of FAs in microalgae in general, which has been documented in the literature, a clear image of the ideal C. velia culture conditions for maximum accumulation of each FA component in both incubated flasks and aerated bioreactors could still be seen. Based on the results in this study at lab scale, C. velia was found to be a suitable candidate for commercial scale-up of zeaxanthin and FA synthesis, as well as a solution for industrial gaseous CO2 emissions. An important finding is that zeaxanthin has a direct influence on fatty acid desaturation under elevated hypercapnia. As a result of zeaxanthin increasing the fluidity of the cell beyond its capability, the alga produces SFA to enhance the rigidity of the membrane as a protective mechanism. Chromera velia produced a substantial amount of EPA, suggesting that it may be exploited for commercial EPA production on land. Finally, even though research on C. velia is still in its early stages, the findings of the metabolites analysis reveal a strong link between the increase in zeaxanthin and the degree of FA desaturation in C. velia. According to literature, increasing zeaxanthin increases membrane fluidity in the ordered phase while lowering fluidity in the liquid crystalline phase of phosphatidylcholine during hypercapnia. Algal mechanisms for resolving the osmotic imbalance caused by variations in the saturated fatty acids (SFA) and polyunsaturated fatty acids (PUFA) ratio (SFA/PUFA) include reduced membrane fluidity and rigidification of the wall structure. In the motility investigation, hypercapnia accelerated the onset of flagellation and increased the proportion of flagellating alga. Flagellation at a proportion of 90% occurred on day 4 at a CO2 concentration of 20%, which is significantly greater than the reference CO2 condition. The metabolic response hypothesis states that when C. velia is exposed to hypercapnia, it increases the amount of lipid or starch in its cells, which are the main sources of energy for flagellate algae in the dark. The observation of C. velia reveals new insights into the ecology and biodiversity of this alga. Investigating C. velia under the microscope revealed several metabolic characteristics similar to green algae and vascular plants, including red-eye, two types of flagellated cells representing two sexual mating cells (eggplant and round shape), and a double cell wall. These are important findings that show the effect of hypercapnia stress on flagellated algae, and the relationship between this alga and other higher plants on the one hand, and flagellated green algae on the other. Aside from that, C. velia's remarkable survival rate under high CO2 settings highlights the alga's enormous potential to lower the CO2 impact of human activities in aquatic environments. As a result, more research is needed to completely comprehend flagellation in the presence of high CO2 concentrations. The current thesis steers future investigations towards application of C. velia in CO2 emission mitigation (algae carbon capture), the production of bioactive valuable components, and wastewater bioremediation. In C. velia at higher CO2 concentration, a greater proportion of the energy required for photosynthesis is dedicated to producing more fatty acids. Increasing the fatty acids in C. velia provides the required energy to flagellate in complete darkness. Chromera velia is proved to be a potential source for the land-based commercial production of zeaxanthin and PUFA, especially EPA. Interestingly, C. velia was found to share several traits with flagellated green algae, namely their metabolic features and the biosynthetic routes to produce zeaxanthin. This work highlights a new morphological finding that could help in further understanding the missing origin path of apicomplexan parasites from their algal ancestors.

Virtual screening and in vitro validation of natural compound inhibitors against SARS-CoV-2 spike protein

Sat, 01 Jan 2022 00:00:00 GMT

Virtual screening and in vitro validation of natural compound inhibitors against SARS-CoV-2 spike protein Power, H.; Wu, J.; Turville, S.; Aggarwal, A.; Valtchev, P.; Schindeler, A.; Dehghani, F. The COVID-19 pandemic caused by the SARS-CoV-2 virus has led to a major public health burden and has resulted in millions of deaths worldwide. As effective treatments are limited, there is a significant requirement for high-throughput, low resource methods for the discovery of novel antivirals. The SARS-CoV-2 spike protein plays a key role in viral entry and has been identified as a therapeutic target. Using the available spike crystal structure, we performed a virtual screen with a library of 527 209 natural compounds against the receptor binding domain of this protein. Top hits from this screen were subjected to a second, more comprehensive molecular docking experiment and filtered for favourable ADMET properties. The in vitro activity of 10 highly ranked compounds was assessed using a virus neutralisation assay designed to facilitate viral entry in a physiologically relevant manner via the plasma membrane route. Subsequently, four compounds ZINC02111387, ZINC02122196, SN00074072 and ZINC04090608 were identified to possess antiviral activity in the µM range. These findings validate the virtual screening method as a tool for identifying novel antivirals and provide a basis for future drug development against SARS-CoV-2.

Assessing the Impacts of Human Activities on Air Quality during the COVID-19 Pandemic through Case Analysis

Sat, 01 Jan 2022 00:00:00 GMT

Assessing the Impacts of Human Activities on Air Quality during the COVID-19 Pandemic through Case Analysis Chi, X.; Hua, J.; Hua, S.; Ren, X.; Yang, S. COVID-19 is the latest of many pandemic affecting the world in the past few decades, and it has had a significant impact on the global environment. Some research has analysed the effects of the pandemic on air quality; however, very few studies have employed relationship analytics. In order to analyse the potential relationship between pandemic-related information and air quality data from a more holistic and detailed point of view, we propose a methodology based on pure data analysis. Three types of data were collected, namely air quality index, pandemic-related events, and number of COVID cases. Data were collected from five cities-Wuhan, New York, Seoul, Melbourne, and Singapore-to further analyse the response of air quality index to COVID events, thus revealing how human activity influences air quality from a pandemic perspective. The results show that a potential connection does exist in most cases and provide more evidence showing that air pollution declined during the pandemic. However, the strength of this relationship may also be related to other factors, such as geography, politics, population density, and measures imposed by local authorities, etc. This study provides another perspective to assist stakeholders in improving environmental decision making.

Online examinations in a large Australian CS1 course

Sat, 01 Jan 2022 00:00:00 GMT

Online examinations in a large Australian CS1 course Jeffries, B.; Baldwin, T.; Zalk, M. Due to the Covid-19 pandemic, universities were required to shift teaching online in 2020, including exams. This rapid move required many changes and compromises to be made in order for students to take their exams remotely. We report on the experiences of running online exams for a large CS1 course at an Australian university, describing the changes made to the online learning platform to support this task, as well as the authoring of the exam and the support provided to students. Several clear instances of academic misconduct are presented to illustrate some of the issues endemic to online exams. Broadly, this approach to examination was a success that we plan to continue in future years, and we reflect on how the approach can be improved.

COVID-MTL: Multitask learning with Shift3D and random-weighted loss for COVID-19 diagnosis and severity assessment

Sat, 01 Jan 2022 00:00:00 GMT

COVID-MTL: Multitask learning with Shift3D and random-weighted loss for COVID-19 diagnosis and severity assessment Bao, G.; Chen, H.; Liu, T.; Gong, G.; Yin, Y.; Wang, L.; Wang, X. There is an urgent need for automated methods to assist accurate and effective assessment of COVID-19. Radiology and nucleic acid test (NAT) are complementary COVID-19 diagnosis methods. In this paper, we present an end-to-end multitask learning (MTL) framework (COVID-MTL) that is capable of automated and simultaneous detection (against both radiology and NAT) and severity assessment of COVID-19. COVID-MTL learns different COVID-19 tasks in parallel through our novel random-weighted loss function, which assigns learning weights under Dirichlet distribution to prevent task dominance; our new 3D real-time augmentation algorithm (Shift3D) introduces space variances for 3D CNN components by shifting low-level feature representations of volumetric inputs in three dimensions; thereby, the MTL framework is able to accelerate convergence and improve joint learning performance compared to single-task models. By only using chest CT scans, COVID-MTL was trained on 930 CT scans and tested on separate 399 cases. COVID-MTL achieved AUCs of 0.939 and 0.846, and accuracies of 90.23% and 79.20% for detection of COVID-19 against radiology and NAT, respectively, which outperformed the state-of-the-art models. Meanwhile, COVID-MTL yielded AUC of 0.800 ± 0.020 and 0.813 ± 0.021 (with transfer learning) for classifying control/suspected, mild/regular, and severe/critically-ill cases. To decipher the recognition mechanism, we also identified high-throughput lung features that were significantly related (P < 0.001) to the positivity and severity of COVID-19.

Why Controlling the Asymptomatic Infection Is Important: A Modelling Study with Stability and Sensitivity Analysis

Sat, 01 Jan 2022 00:00:00 GMT

Why Controlling the Asymptomatic Infection Is Important: A Modelling Study with Stability and Sensitivity Analysis Pan, J.; Chen, Z.; He, Y.; Liu, T.; Cheng, X.; Xiao, J.; Feng, H. The large proportion of asymptomatic patients is the major cause leading to the COVID-19 pandemic which is still a significant threat to the whole world. A six-dimensional ODE system (SEIAQR epidemical model) is established to study the dynamics of COVID-19 spreading considering infection by exposed, infected, and asymptomatic cases. The basic reproduction number derived from the model is more comprehensive including the contribution from the exposed, infected, and asymptomatic patients. For this more complex six-dimensional ODE system, we investigate the global and local stability of disease-free equilibrium, as well as the endemic equilibrium, whereas most studies overlooked asymptomatic infection or some other virus transmission features. In the sensitivity analysis, the parameters related to the asymptomatic play a significant role not only in the basic reproduction number R0. It is also found that the asymptomatic infection greatly affected the endemic equilibrium. Either in completely eradicating the disease or achieving a more realistic goal to reduce the COVID-19 cases in an endemic equilibrium, the importance of controlling the asymptomatic infection should be emphasized. The three-dimensional phase diagrams demonstrate the convergence point of the COVID-19 spreading under different initial conditions. In particular, massive infections will occur as shown in the phase diagram quantitatively in the case R0 > 1. Moreover, two four-dimensional contour maps of Rt are given varying with different parameters, which can offer better intuitive instructions on the control of the pandemic by adjusting policy-related parameters.

Exhaled Jet and Viral-Laden Aerosol Transport from Nasal Sneezing

Sat, 01 Jan 2022 00:00:00 GMT

Exhaled Jet and Viral-Laden Aerosol Transport from Nasal Sneezing Salati, H.; Fletcher, D.F.; Khamooshi, M.; Dong, J.; Ito, K.; Vahaji, S.; Inthavong, K. The recognition that the spread of COVID-19 is primarily through airborne transmission has brought renewed urgency to understand the spread of aerosols generated from patients. Viral-laden aerosols generated from oral coughs have been well studied; however, aerosols generated from nasal sneezing has been overlooked. This scenario arises from patients who suffer allergenic rhinosinusitis, or the nasal cavity is irritated, particularly during naso-endoscopy. Nasal sneezing is characterised by an explosive blast of air exiting the nostrils, which can be considered as dual jets, resulting in the spread of viral-laden aerosols remaining suspended in the air. This study used computational fluid dynamics consisting of a hybrid RANS-LES turbulence method to model the airflow and the discrete phase model to track aerosol dispersion during nasal sneezing. The results demonstrated that the exhaled airflow jets during nasal sneezing resemble the flow characteristics of two parallel jets in co-flow. These two jets interfere with each other in the merging zone, and after they merge, the sneeze plume expands radially. The nasal sneeze forms a V-shaped plume with smaller particles in the core region. At the end of the sneeze, when the exhaled jets have lost their initial momentum, the large particle dispersion is dominated by gravity. We detected the presence of a 'sneeze puff' that transport droplets away from the body, similar to the buoyant puff observed in recent COVID-19 studies of oral coughs.

Energy justice issues in renewable energy megaprojects: implications for a socioeconomic evaluation of megaprojects

Sat, 01 Jan 2022 00:00:00 GMT

Energy justice issues in renewable energy megaprojects: implications for a socioeconomic evaluation of megaprojects Sankaran, S.; Clegg, S.; M�ller, R.; Drouin, N. Purpose: The purpose of this paper is to investigate and discuss stakeholder issues faced by renewable energy megaprojects and in particular solar and wind power projects and their relevance to socioeconomic evaluation of megaprojects. Design/methodology/approach: The paper uses secondary data collected from the recent literature published on stakeholder issues face by mega solar and wind power energy generation projects around the world. The issues are then analysed across specific challenges in five continents where these projects are being developed. The paper then focuses on the literature on energy justice to elaborate the type of issues being faced by renewable energy megaprojects contributing to the achievement of UN Sustainable Goal 7 and their impact on vulnerable communities where these projects are situated. Findings: Renewable energy megaprojects are rarely discussed in the project management literature on megaprojects despite their size and importance in delivering sustainable development goals. While these projects provide social benefits they also create issues of justice due to their impact of vulnerable populations living is locations where these projects are situated. The justice issues faced include procedural justice, distributive justice, recognition inequalities. The type of justice issues was found to vary intensity in the developed, emerging and developing economies. It was found that nonprofit organisations are embarking on strategies to alleviate energy justice issues in innovative ways. It was also found that, in some instances, smaller local projects developed with community participation could actually contribute more equitable to the UN sustainable development goals avoiding the justice issues posed by mega renewable energy projects. Research limitations/implications: The research uses secondary data due to which it is difficult to present a more comprehensive picture of stakeholder issues involving renewable energy megaprojects. The justice issues revealed through thesis paper with renewable energy megaprojects are also present in conventional megaprojects which have not been discussed in the project management literature. Post-COVID-19 these justice issues are likely to become mor prevalent due to the pandemic's impact on vulnerable population exacerbating the issues and increasing their severity on these populations. Therefore it is becoming even more critical to take these into account while developing renewable energy megaprojects. Practical implications: Proper identification and response to energy justice issues can help in alleviating stakeholder issues in renewable energy megaprojects. Social implications: Contributes to the equitable achievement of the United Nations Sustainable Development Goal 7. Originality/value: This paper addresses a gap in the project management literature on the exploration of stakeholder issues on renewable energy megaprojects. It also brings out the importance of justice issues which can assist in expanding stakeholders issues faced by megaprojects as these issues have not received sufficient attention in the past in the project management literature.

How do economic and public finance statuses affect policy responses during a pandemic? - learning from the COVID-19 first wave

Sat, 01 Jan 2022 00:00:00 GMT

How do economic and public finance statuses affect policy responses during a pandemic? - learning from the COVID-19 first wave Imam, T.; Uddin, S. Background: In the time of a pandemic, it is typical for public health bodies to collaborate with epidemiologists to design health policies both at national and international levels for controlling the spread. A point largely overlooked in literature is the extent economic capability and public finance status can influence the policy responses of countries during a pandemic situation. This article fills this gap by considering 12 public health and 7 economic measures (i.e., policies) in 200 countries during the COVID-19 first wave, with countries grouped across income categories. Methods: We apply statistical analysis, inclusive of regression models, to assess the impact of economic capability and public finance status on policy responses. Multiple open-access datasets are used in this research, and information from the hybrid sources are cumulated as samples. In our analysis, we consider variables including population characteristics (population size, density) and economic and public finance status (GDR, current account balance, government surplus/deficit) further to policy responses across public health and economic measures. Additionally, we consider infection rates across countries and the institution of the measures relative to infection rate. Results: Results suggest that countries from all income groups have favoured public health measures like school closures and travel bans, and economic measures like influencing interest rates. However, strong economy countries have more adopted technological monitoring than low-income countries. Contrarily, low-income countries have preferred traditional measures like curfew and obligatory mask-wearing. GDP per capita was a statistically significant factor influencing the institution of both public health and economic measures. Government finance statuses like current account balance and surplus/deficit were also significant factors influencing economic measures. Conclusions: Overall, the research reveals that, further to biological characteristics, policymakers and epidemiologists can consider the economic and public finance contexts when suggesting health responses to a pandemic. This, in turn, calls for more international cooperation on economic terms further to public health terms.

Shielding Surfaces from Viruses and Bacteria with a Multiscale Coating

Sat, 01 Jan 2022 00:00:00 GMT

Shielding Surfaces from Viruses and Bacteria with a Multiscale Coating Ashok, Deepu; Taheri, Mahdiar; Garg, Puneet; Webb, Daryl; Parajuli, Pawan; Wang, Yi; Funnell, Bronte; Taylor, Bradley; Tscharke, David C.; Tsuzuki, Takuya; Verma, Naresh K.; Tricoli, Antonio; Nisbet, David R. The spread of viral and bacterial pathogens mediated by contact with surfaces is a leading cause of infection worldwide. COVID-19 and the continuous rise of deaths associated with antibiotic-resistant bacteria highlight the need to impede surface-mediated transmission. A sprayable coating with an intrinsic ability to resist the uptake of bacteria and viruses from surfaces and droplets, such as those generated by sneezing or coughing, is reported. The coating also provides an effective microbicidal functionality against bacteria, providing a dual barrier against pathogen uptake and transmission. This antimicrobial functionality is fully preserved following scratching and other induced damage to its surface or 9 days of submersion in a highly concentrated suspension of bacteria. The coatings also register an 11-fold decrease in viral contamination compared to the noncoated surfaces.

Fast COVID-19 versus H1N1 screening using Optimized Parallel Inception

Sat, 01 Jan 2022 00:00:00 GMT

Fast COVID-19 versus H1N1 screening using Optimized Parallel Inception Tavakolian, Alireza; Hajati, Farshid; Rezaee, Alireza; Fasakhodi, Amirhossein Oliaei; Uddin, Shahadat COVID-19 and swine-origin influenza A (H1N1) are both pandemics that sparked significant concern worldwide. Since these two diseases have common symptoms, a fast COVID-19 versus H1N1 screening helps better manage patients at healthcare facilities. We present a novel deep model, called Optimized Parallel Inception, for fast screening of COVID-19 and H1N1 patients. We also present a Semi-supervised Generative Adversarial Network (SGAN) to address the problem related to the smaller size of the COVID-19 and H1N1 research data. To evaluate the proposed models, we have merged two separate COVID-19 and H1N1 data from different sources to build a new dataset. The created dataset includes 4,383 positive COVID-19 cases, 989 positive H1N1 cases, and 1,059 negative cases. We applied SGAN on this dataset to remove issues related to unequal class densities. The experimental results show that the proposed model's screening accuracy is 99.2% and 99.6% for COVID-19 and H1N1, respectively. According to our analysis, the most significant symptoms and underlying chronic diseases for COVID-19 versus H1N1 screening are dry cough, breathing problems, diabetes, and gastrointestinal.

Functional lock-in and the problem of design transformation

Sun, 01 Jan 2017 00:00:00 GMT

Functional lock-in and the problem of design transformation Dong, Andy The act of introducing an innovation into an existing product by substituting or inserting new technologies is thought to be challenging due to the problem of integrating new components and sub-system architectures into existing ones. This article aims to challenge the foundation of this problem and develop new insights into the choice of functional architecture. The article will propose that the choice of functional architecture to achieve an intended purpose locks-in a design by influencing the cost of transformation. This paper studies functional lock-in based on the transformation cost of the functional architectures of products. The transformation cost for a set of biological and biologically inspired products is compared to that of engineered products. The results show that the biological and biologically inspired products have a statistically significant lower transformation cost than the engineered products. The results indicate that the structure of functions and flows in a product will constrain its transformation. More broadly, the paper proposes minimum transformation cost as an essential property of an optimal design.