Search results for: indigenous community services

Authors: Andreas Rudisch, Ralf Lampert, Andreas Kolbitsch

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It is a well-known fact among the engineering community that earthquakes with comparatively low magnitudes can cause serious damage to nonstructural components (NSCs) of buildings, even when the supporting structure performs relatively well. Past research works focused mainly on NSCs of nuclear power plants and industrial plants. Particular attention should also be given to architectural façade elements of old masonry buildings (e.g. ornamental figures, balustrades, vases), which are very vulnerable under seismic excitation. Large numbers of these historical nonstructural components (HiNSCs) can be found in highly frequented historical city centers and in the event of failure, they pose a significant danger to persons. In order to estimate the vulnerability of acceleration sensitive HiNSCs, the peak horizontal floor acceleration (PHFA) is used. The PHFA depends on the dynamic characteristics of the building, the ground excitation, and induced nonlinearities. Consequently, the PHFA can not be generalized as a simple function of height. In the present research work, an extensive case study was conducted to investigate the influence of induced nonlinearity on the PHFA for old masonry buildings. Probabilistic nonlinear FE time-history analyses considering three different hazard levels were performed. A set of eighteen synthetically generated ground motions was used as input to the structure models. An elastoplastic macro-model (multiPlas) for nonlinear homogenized continuum FE-calculation was calibrated to multiple scales and applied, taking specific failure mechanisms of masonry into account. The macro-model was calibrated according to the results of specific laboratory and cyclic in situ shear tests. The nonlinear macro-model is based on the concept of multi-surface rate-independent plasticity. Material damage or crack formation are detected by reducing the initial strength after failure due to shear or tensile stress. As a result, shear forces can only be transmitted to a limited extent by friction when the cracking begins. The tensile strength is reduced to zero. The first goal of the calibration was the consistency of the load-displacement curves between experiment and simulation. The calibrated macro-model matches well with regard to the initial stiffness and the maximum horizontal load. Another goal was the correct reproduction of the observed crack image and the plastic strain activities. Again the macro-model proved to work well in this case and shows very good correlation. The results of the case study show that there is significant scatter in the absolute distribution of the PHFA between the applied ground excitations. An absolute distribution along the normalized building height was determined in the framework of probability theory. It can be observed that the extent of nonlinear behavior varies for the three hazard levels. Due to the detailed scope of the present research work, a robust comparison with code-recommendations and simplified PHFA distributions are possible. The chosen methodology offers a chance to determine the distribution of PHFA along the building height of old masonry structures. This permits a proper hazard assessment of HiNSCs under seismic loads.

Keywords: nonlinear macro-model, nonstructural components, time-history analysis, unreinforced masonry

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Authors: Tom S. Owens, Tom A. Calverley, Benjamin S. Stacey, Christopher J. Marley, George Rose, Lewis Fall, Gareth L. Jones, Priscilla Williams, John P. R. Williams, Martin Steggall, Damian M. Bailey

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Introduction and aims: Sports-related concussion (SRC) represents a significant and growing public health concern in rugby union, yet remains one of the least understood injuries facing the health community today. Alongside increasing SRC incidence rates, there is concern that prior recurrent concussion may contribute to long-term neurologic sequelae in later-life. This may be due to an accelerated decline in cerebral perfusion, a major risk factor for neurocognitive decline and neurodegeneration, though the underlying mechanisms remain to be established. The present study hypothesised that recurrent concussion in current professional rugby union players would result in elevated systemic oxidative-nitrosative stress, reflected by a free radical-mediated reduction in nitric oxide (NO) bioavailability and impaired cerebrovascular and cognitive function. Methodology: A longitudinal study design was adopted across the 2017-2018 rugby union season. Ethical approval was obtained from the University of South Wales Ethics Committee. Data collection is ongoing, and therefore the current report documents result from the pre-season and first half of the in-season data collection. Participants were initially divided into two subgroups; 23 professional rugby union players (aged 26 ± 5 years) and 22 non-concussed controls (27 ± 8 years). Pre-season measurements were performed for cerebrovascular function (Doppler ultrasound of middle cerebral artery velocity (MCAv) in response to hypocapnia/normocapnia/hypercapnia), cephalic venous concentrations of the ascorbate radical (A•-, electron paramagnetic resonance spectroscopy), NO (ozone-based chemiluminescence) and cognition (neuropsychometric tests). Notational analysis was performed to assess contact in the rugby group throughout each competitive game. Results: 1001 tackles and 62 injuries, including three concussions were observed across the first half of the season. However, no associations were apparent between number of tackles and any injury type (P > 0.05). The rugby group expressed greater oxidative stress as indicated by increased A•- (P < 0.05 vs. control) and a subsequent decrease in NO bioavailability (P < 0.05 vs. control). The rugby group performed worse in the Ray Auditory Verbal Learning Test B (RAVLT-B, learning, and memory) and the Grooved Pegboard test using both the dominant and non-dominant hands (visuomotor coordination, P < 0.05 vs. control). There were no between-group differences in cerebral perfusion at baseline (MCAv: 54 ± 13 vs. 59 ± 12, P > 0.05). Likewise, no between-group differences in CVRCO2Hypo (2.58 ± 1.01 vs. 2.58 ± 0.75, P > 0.05) or CVRCO2Hyper (2.69 ± 1.07 vs. 3.35 ± 1.28, P > 0.05) were observed. Conclusion: The present study identified that the rugby union players are characterized by impaired cognitive function subsequent to elevated systemic-oxidative-nitrosative stress. However, this appears to be independent of any functional impairment in cerebrovascular function. Given the potential long-term trajectory towards accelerated cognitive decline in populations exposed to SRC, prophylaxis to increase NO bioavailability warrants consideration.

Keywords: cognition, concussion, mild traumatic brain injury, rugby

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Authors: Monique M. Keller, Roline Barnes, Corlia Brandt

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Introduction Scientific evidence on the hand forces and the types of grasps measurement during daily tasks are lacking, leaving a gap in the field of hand rehabilitation and robotics. Measuring the grasp forces and types produced by the individual fingers during daily functional tasks is valuable to inform and grade rehabilitation practices for second to fifth metacarpal fractures with robust scientific evidence. Feix et al, 2016 identified the most extensive and complete grasp study that resulted in the GRASP taxonomy. Covid-19 virus changed data collection across the globe and safety precautions in research are essential to ensure the health of participants and researchers. Methodology A cross-sectional study investigated six healthy adults aged 20 to 59 years, pilot participants’ hand forces during 105 tasks. The tasks were categorized into five sections namely, personal care, transport and moving around, home environment and inside, gardening and outside, and office. The predominant grasp of each task was identified guided by the GRASP Taxonomy. Grasp forces were measured with 13mm force-sensing resistors glued onto a glove attached to each of the dominant and non-dominant hand’s individual fingers. Testing equipment included Flexiforce 13millimetres FSR .5" circle, calibrated prior to testing, 10k 1/4w resistors, Arduino pro mini 5.0v – compatible, Esp-01-kit, Arduino uno r3 – compatible board, USB ab cable - 1m, Ftdi ft232 mini USB to serial, Sil 40 inline connectors, ribbon cable combo male header pins, female to female, male to female, two gloves, glue to attach the FSR to glove, Arduino software programme downloaded on a laptop. Grip strength measurements with Jamar dynamometer prior to testing and after every 25 daily tasks were taken to will avoid fatigue and ensure reliability in testing. Covid-19 precautions included wearing face masks at all times, screening questionnaires, temperatures taken, wearing surgical gloves before putting on the testing gloves 1.5 metres long wires attaching the FSR to the Arduino to maintain social distance. Findings Predominant grasps observed during 105 tasks included, adducted thumb (17), lateral tripod (10), prismatic three fingers (12), small diameter (9), prismatic two fingers (9), medium wrap (7), fixed hook (5), sphere four fingers (4), palmar (4), parallel extension (4), index finger extension (3), distal (3), power sphere (2), tripod (2), quadpod (2), prismatic four fingers (2), lateral (2), large-diameter (2), ventral (2), precision sphere (1), palmar pinch (1), light tool (1), inferior pincher (1), and writing tripod (1). Range of forces applied per category, personal care (1-25N), transport and moving around (1-9 N), home environment and inside (1-41N), gardening and outside (1-26.5N), and office (1-20N). Conclusion Scientifically measurements of finger forces with careful consideration to types of grasps used in daily tasks should guide rehabilitation practices and robotic design to ensure a return to the full participation of the individual into the community.

Keywords: activities of daily living (ADL), Covid-19, force-sensing resistors, grasps, hand forces

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Authors: Hamda Ajmal, Karen Young, Ruth Melia, John Bogue, Mary O'Sullivan, Jim Duggan, Hannah Wood

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The Covid-19 pandemic led to a range of public health mitigation strategies in order to suppress the SARS-CoV-2 virus. The drastic changes in everyday life due to lockdowns had the potential for a significant negative impact on public mental health, and a key public health goal is to now assess the evidence from available Irish datasets to provide useful insights on this issue. Text-50808 is an online text-based mental health support service, established in Ireland in 2020, and can provide a measure of revealed distress and mental health concerns across the population. The aim of this study is to explore statistical associations between public mental health in Ireland and the Covid-19 pandemic. Uniquely, this study combines two measures of emotional wellbeing in Ireland: (1) weekly text volume at Text-50808, and (2) emotional wellbeing indicators reported by respondents of the Amárach public opinion survey, carried out on behalf of the Department of Health, Ireland. For this analysis, a multivariate graphical exploratory data analysis (EDA) was performed on the Text-50808 dataset dated from 15th June 2020 to 30th June 2021. This was followed by time-series analysis of key mental health indicators including: (1) the percentage of daily/weekly texts at Text-50808 that mention Covid-19 related issues; (2) the weekly percentage of people experiencing anxiety, boredom, enjoyment, happiness, worry, fear and stress in Amárach survey; and Covid-19 related factors: (3) daily new Covid-19 case numbers; (4) daily stringency index capturing the effect of government non-pharmaceutical interventions (NPIs) in Ireland. The cross-correlation function was applied to measure the relationship between the different time series. EDA of the Text-50808 dataset reveals significant peaks in the volume of texts on days prior to level 3 lockdown and level 5 lockdown in October 2020, and full level 5 lockdown in December 2020. A significantly high positive correlation was observed between the percentage of texts at Text-50808 that reported Covid-19 related issues and the percentage of respondents experiencing anxiety, worry and boredom (at a lag of 1 week) in Amárach survey data. There is a significant negative correlation between percentage of texts with Covid-19 related issues and percentage of respondents experiencing happiness in Amárach survey. Daily percentage of texts at Text-50808 that reported Covid-19 related issues to have a weak positive correlation with daily new Covid-19 cases in Ireland at a lag of 10 days and with daily stringency index of NPIs in Ireland at a lag of 2 days. The sudden peaks in text volume at Text-50808 immediately prior to new restrictions in Ireland indicate an association between a rise in mental health concerns following the announcement of new restrictions. There is also a high correlation between emotional wellbeing variables in the Amárach dataset and the number of weekly texts at Text-50808, and this confirms that Text-50808 reflects overall public sentiment. This analysis confirms the benefits of the texting service as a community surveillance tool for mental health in the population. This initial EDA will be extended to use multivariate modeling to predict the effect of additional Covid-19 related factors on public mental health in Ireland.

Keywords: COVID-19 pandemic, data analysis, digital health, mental health, public health, digital health

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Authors: Laura Norfolk, Georgina Zimbitas, Jan Sefcik, Sarah Staniland

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Magnetite nanoparticles (MNP) have been an area of increasing research interest due to their extensive applications in industry, such as in carbon capture, water purification, and crucially, the biomedical industry. The use of MNP in the biomedical industry is rising, with studies on their effect as Magnetic resonance imaging contrast agents, drug delivery systems, and as hyperthermic cancer treatments becoming prevalent in the nanomaterial research community. Particles used for biomedical purposes must meet stringent criteria; the particles must have consistent shape and size between particles. Variation between particle morphology can drastically alter the effective surface area of the material, making it difficult to correctly dose particles that are not homogeneous. Particles of defined shape such as octahedral and cubic have been shown to outperform irregular shaped particles in some applications, leading to the need to synthesize particles of defined shape. In nature, highly homogeneous MNP are found within magnetotactic bacteria, a unique bacteria capable of producing magnetite nanoparticles internally under ambient conditions. Biomineralisation proteins control the properties of the MNPs, enhancing their homogeneity. One of these proteins, Mms6, has been successfully isolated and used in vitro as an additive in room-temperature co-precipitation reactions (RTCP) to produce particles of defined mono-dispersed size & morphology. When considering future industrial scale-up it is crucial to consider the costs and feasibility of an additive, as an additive that is not readily available or easily synthesized at a competitive price will not be sustainable. As such, additives selected for this research are inspired by the functional groups of biomineralisation proteins, but cost-effective, environmentally friendly, and compatible with scale-up. Diethylenetriamine (DETA), triethylenetetramine (TETA), tetraethylenepentamine (TEPA), and pentaethylenehexamine (PEHA) have been successfully used in RTCP to modulate the properties of particles synthesized, leading to the formation of octahedral nanoparticles with no use of organic solvents, heating, or toxic precursors. By extending this principle to a fluidic system, ongoing research will reveal whether the amine additives can also exert morphological control in an environment which is suited toward higher particle yield. Two fluidic systems have been employed; a peristaltic turbulent flow mixing system suitable for the rapid production of MNP, and a macrofluidic system for the synthesis of tailored nanomaterials under a laminar flow regime. The presence of the amine additives in the turbulent flow system in initial results appears to offer similar morphological control as observed under RTCP conditions, with higher proportions of octahedral particles formed. This is a proof of concept which may pave the way to green synthesis of tailored MNP on an industrial scale. Mms6 and amine additives have been used in the macrofluidic system, with Mms6 allowing magnetite to be synthesized at unfavourable ferric ratios, but no longer influencing particle size. This suggests this synthetic technique while still benefiting from the addition of additives, may not allow additives to fully influence the particles formed due to the faster timescale of reaction. The amine additives have been tested at various concentrations, the results of which will be discussed in this paper.

Keywords: bioinspired, green synthesis, fluidic, magnetite, morphological control, scale-up

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Authors: Mireille Elhajj, Washington Ochieng, Deeph Chana

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The challenges of the rapid growth in the demand for transport has traditionally been seen within the context of the problems of congestion, air quality, climate change, safety, and affordability. However, there are increasing threats including those related to crime such as cyber-attacks that threaten the security of the transport of people and goods. To the best of the authors’ knowledge, this paper presents for the first time, a comprehensive framework for the assessment of the current and future security issues of multi-modal transport systems. The approach or method proposed is based on a structured framework starting with a detailed specification of the transport asset map (transport system architecture), followed by the identification of vulnerabilities. The asset map and vulnerabilities are used to identify the various approaches for exploitation of the vulnerabilities, leading to the creation of a set of threat scenarios. The threat scenarios are then transformed into risks and their categories, and include insights for their mitigation. The consideration of the mitigation space is holistic and includes the formulation of appropriate policies and tactics and/or technical interventions. The quality of the framework is ensured through a structured and logical process that identifies the stakeholders, reviews the relevant documents including policies and identifies gaps, incorporates targeted surveys to augment the reviews, and uses subject matter experts for validation. The approach to categorising security risks is an extension of the current methods that are typically employed. Specifically, the partitioning of risks into either physical or cyber categories is too limited for developing mitigation policies and tactics/interventions for transport systems where an interplay between physical and cyber processes is very often the norm. This interplay is rapidly taking on increasing significance for security as the emergence of cyber-physical technologies, are shaping the future of all transport modes. Examples include: Connected Autonomous Vehicles (CAVs) in road transport; the European Rail Traffic Management System (ERTMS) in rail transport; Automatic Identification System (AIS) in maritime transport; advanced Communications, Navigation and Surveillance (CNS) technologies in air transport; and the Internet of Things (IoT). The framework adopts a risk categorisation scheme that considers risks as falling within the following threat→impact relationships: Physical→Physical, Cyber→Cyber, Cyber→Physical, and Physical→Cyber). Thus the framework enables a more complete risk picture to be developed for today’s transport systems and, more importantly, is readily extendable to account for emerging trends in the sector that will define future transport systems. The framework facilitates the audit and retro-fitting of mitigations in current transport operations and the analysis of security management options for the next generation of Transport enabling strategic aspirations such as systems with security-by-design and co-design of safety and security to be achieved. An initial application of the framework to transport systems has shown that intra-modal consideration of security measures is sub-optimal and that a holistic and multi-modal approach that also addresses the intersections/transition points of such networks is required as their vulnerability is high. This is in-line with traveler-centric transport service provision, widely accepted as the future of mobility services. In summary, a risk-based framework is proposed for use by the stakeholders to comprehensively and holistically assess the security of transport systems. It requires a detailed understanding of the transport architecture to enable a detailed vulnerabilities analysis to be undertaken, creates threat scenarios and transforms them into risks which form the basis for the formulation of interventions.

Keywords: mitigations, risk, transport, security, vulnerabilities

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Authors: Mozhdeh Khalili Kordabadi

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Textiles play a vital role in human life, particularly in the form of clothing. However, the alarming rate at which textiles end up in landfills presents a significant environmental risk. With approximately one garbage truck per second being filled with discarded textiles, urgent measures are required to mitigate this trend. Governments and responsible organizations are calling upon various stakeholders to shift from a linear economy to a circular economy model in the textile industry. This article highlights several key approaches that can be undertaken to address this pressing issue. These approaches include the creation of renewable raw material sources, rethinking production processes, maximizing the use and reuse of textile products, implementing reproduction and recycling strategies, exploring redistribution to new markets, and finding innovative means to extend the lifespan of textiles. By adopting these strategies, the textile industry can contribute to a more sustainable and environmentally friendly future. Introduction: Textiles, particularly clothing, are essential to human existence. However, the rapid accumulation of textiles in landfills poses a significant threat to the environment. This article explores the urgent need for the textile industry to transition from a linear economy model to a circular economy model. The linear model, characterized by the creation, use, and disposal of textiles, is unsustainable in the long term. By adopting a circular economy approach, the industry can minimize waste, reduce environmental impact, and promote sustainable practices. This article outlines key approaches that can be undertaken to drive this transition. Approaches to Address Environmental Challenges: Creation of Renewable Raw Materials Sources: Exploring and promoting the use of renewable and sustainable raw materials, such as organic cotton, hemp, and recycled fibers, can significantly reduce the environmental footprint of textile production. Rethinking Production Processes: Implementing cleaner production techniques, optimizing resource utilization, and minimizing waste generation are crucial steps in reducing the environmental impact of textile manufacturing. Maximizing Use and Reuse of Textile Products: Encouraging consumers to prolong the lifespan of textile products through proper care, maintenance, and repair services can reduce the frequency of disposal and promote a culture of sustainability. Reproduction and Recycling Strategies: Investing in innovative technologies and infrastructure to enable efficient reproduction and recycling of textiles can close the loop and minimize waste generation. Redistribution of Textiles to New Markets: Exploring opportunities to redistribute textiles to new and parallel markets, such as resale platforms, can extend their lifecycle and prevent premature disposal. Improvising Means to Extend Textile Lifespan: Encouraging design practices that prioritize durability, versatility, and timeless aesthetics can contribute to prolonging the lifespan of textiles. Conclusion: The textile industry must urgently transition from a linear economy to a circular economy model to mitigate the adverse environmental impact caused by textile waste. By implementing the outlined approaches, such as sourcing renewable raw materials, rethinking production processes, promoting reuse and recycling, exploring new markets, and extending the lifespan of textiles, stakeholders can work together to create a more sustainable and environmentally friendly textile industry. These measures require collective action and collaboration between governments, organizations, manufacturers, and consumers to drive positive change and safeguard the planet for future generations.

Keywords: textiles, circular economy, environmental challenges, renewable raw materials, production processes, reuse, recycling, redistribution, textile lifespan extension.

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Authors: Manon Frédout, Laëtitia Bucari, Mathias Aloui, Gaëtan Duhamel, Olivier Rovellotti, Javier Blanco

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Ecosystems must be resilient to ensure cleaner air, better water and soil quality, and thus healthier citizens. Technology can be an excellent tool to support urban ecosystem restoration projects, especially when based on Open Source and promoting Open Data. This is the goal of the ecoTeka application: one single digital tool for tree management which allows decision-makers to improve their urban forestry practices, enabling more responsible urban planning and climate change adaptation. EcoTeka provides city councils with three main functionalities tackling three of their challenges: easier biodiversity inventories, better green space management, and more efficient planning. To answer the cities’ need for reliable tree inventories, the application has been first built with open data coming from the websites OpenStreetMap and OpenTrees, but it will also include very soon the possibility of creating new data. To achieve this, a multi-source algorithm will be elaborated, based on existing artificial intelligence Deep Forest, integrating open-source satellite images, 3D representations from LiDAR, and street views from Mapillary. This data processing will permit identifying individual trees' position, height, crown diameter, and taxonomic genus. To support urban forestry management, ecoTeka offers a dashboard for monitoring the city’s tree inventory and trigger alerts to inform about upcoming due interventions. This tool was co-constructed with the green space departments of the French cities of Alès, Marseille, and Rouen. The third functionality of the application is a decision-making tool for urban planning, promoting biodiversity and landscape connectivity metrics to drive ecosystem restoration roadmap. Based on landscape graph theory, we are currently experimenting with new methodological approaches to scale down regional ecological connectivity principles to local biodiversity conservation and urban planning policies. This methodological framework will couple graph theoretic approach and biological data, mainly biodiversity occurrences (presence/absence) data available on both international (e.g., GBIF), national (e.g., Système d’Information Nature et Paysage) and local (e.g., Atlas de la Biodiversté Communale) biodiversity data sharing platforms in order to help reasoning new decisions for ecological networks conservation and restoration in urban areas. An experiment on this subject is currently ongoing with Montpellier Mediterranee Metropole. These projects and studies have shown that only 26% of tree inventory data is currently geo-localized in France - the rest is still being done on paper or Excel sheets. It seems that technology is not yet used enough to enrich the knowledge city councils have about biodiversity in their city and that existing biodiversity open data (e.g., occurrences, telemetry, or genetic data), species distribution models, landscape graph connectivity metrics are still underexploited to make rational decisions for landscape and urban planning projects. This is the goal of ecoTeka: to support easier inventories of urban biodiversity and better management of urban spaces through rational planning and decisions relying on open databases. Future studies and projects will focus on the development of tools for reducing the artificialization of soils, selecting plant species adapted to climate change, and highlighting the need for ecosystem and biodiversity services in cities.

Keywords: digital software, ecological design of urban landscapes, sustainable urban development, urban ecological corridor, urban forestry, urban planning

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Authors: Manuel I. Capel, Antonio Tomeu, Alberto Salguero

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Tumor growth from a transformed cancer-cell up to a clinically apparent mass spans through a range of spatial and temporal magnitudes. Through computer simulations, Cellular Automata (CA) can accurately describe the complexity of the development of tumors. Tumor development prognosis can now be made -without making patients undergo through annoying medical examinations or painful invasive procedures- if we develop appropriate CA-based software tools. In silico testing mainly refers to Computational Biology research studies of application to clinical actions in Medicine. To establish sound computer-based models of cellular behavior, certainly reduces costs and saves precious time with respect to carrying out experiments in vitro at labs or in vivo with living cells and organisms. These aim to produce scientifically relevant results compared to traditional in vitro testing, which is slow, expensive, and does not generally have acceptable reproducibility under the same conditions. For speeding up computer simulations of cellular models, specific literature shows recent proposals based on the CA approach that include advanced techniques, such the clever use of supporting efficient data structures when modeling with deterministic stochastic cellular automata. Multiparadigm and multiscale simulation of tumor dynamics is just beginning to be developed by the concerned research community. The use of stochastic cellular automata (SCA), whose parallel programming implementations are open to yield a high computational performance, are of much interest to be explored up to their computational limits. There have been some approaches based on optimizations to advance in multiparadigm models of tumor growth, which mainly pursuit to improve performance of these models through efficient memory accesses guarantee, or considering the dynamic evolution of the memory space (grids, trees,…) that holds crucial data in simulations. In our opinion, the different optimizations mentioned above are not decisive enough to achieve the high performance computing power that cell-behavior simulation programs actually need. The possibility of using multicore and GPU parallelism as a promising multiplatform and framework to develop new programming techniques to speed-up the computation time of simulations is just starting to be explored in the few last years. This paper presents a model that incorporates parallel processing, identifying the synchronization necessary for speeding up tumor growth simulations implemented in Java and C++ programming environments. The speed up improvement that specific parallel syntactic constructs, such as executors (thread pools) in Java, are studied. The new tumor growth parallel model is proved using implementations with Java and C++ languages on two different platforms: chipset Intel core i-X and a HPC cluster of processors at our university. The parallelization of Polesczuk and Enderling model (normally used by researchers in mathematical oncology) proposed here is analyzed with respect to performance gain. We intend to apply the model and overall parallelization technique presented here to solid tumors of specific affiliation such as prostate, breast, or colon. Our final objective is to set up a multiparadigm model capable of modelling angiogenesis, or the growth inhibition induced by chemotaxis, as well as the effect of therapies based on the presence of cytotoxic/cytostatic drugs.

Keywords: cellular automaton, tumor growth model, simulation, multicore and manycore programming, parallel programming, high performance computing, speed up

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Authors: Majid Alenezi, Abdelbare Algamode, Amy Hayes, Gavin Lawrence, Nichola Callow

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The purpose of this study was to translate and culturally adapt the Vividness of Movement Imagery Questionnaire-2 (VMIQ-2) from English to produce a new Arabic version (VMIQ-2A), and to evaluate the reliability and validity of the translated questionnaire. The questionnaire assesses how vividly and clearly individuals are able to imagine themselves performing everyday actions. Its purpose is to measure individuals’ ability to conduct movement imagery, which can be defined as “the cognitive rehearsal of a task in the absence of overt physical movement.” Movement imagery has been introduced in physiotherapy as a promising intervention technique, especially when physical exercise is not possible (e.g. pain, immobilisation.) Considerable evidence indicates movement imagery interventions improve physical function, but to maximize efficacy it is important to know the imagery abilities of the individuals being treated. Given the increase in the global sharing of knowledge it is desirable to use standard measures of imagery ability across language and cultures, thus motivating this project. The translation procedure followed guidelines from the Translation and Cultural Adaptation group of the International Society for Pharmacoeconomics and Outcomes Research and involved the following phases: Preparation; the original VMIQ-2 was adapted slightly to provide additional information and simplified grammar. Forward translation; three native speakers resident in Saudi Arabia translated the original VMIQ-2 from English to Arabic, following instruction to preserve meaning (not literal translation), and cultural relevance. Reconciliation; the project manager (first author), the primary translator and a physiotherapist reviewed the three independent translations to produce a reconciled first Arabic draft of VMIQ-2A. Backward translation; a fourth translator (native Arabic speaker fluent in English) translated literally the reconciled first Arabic draft to English. The project manager and two study authors compared the English back translation to the original VMIQ-2 and produced the second Arabic draft. Cognitive debriefing; to assess participants’ understanding of the second Arabic draft, 7 native Arabic speakers resident in the UK completed the questionnaire, and rated the clearness of the questions, specified difficult words or passages, and wrote in their own words their understanding of key terms. Following review of this feedback, a final Arabic version was created. 142 native Arabic speakers completed the questionnaire in community meeting places or at home; a subset of 44 participants completed the questionnaire a second time 1 week later. Results showed the translated questionnaire to be valid and reliable. Correlation coefficients indicated good test-retest reliability. Cronbach’s a indicated high internal consistency. Construct validity was tested in two ways. Imagery ability scores have been found to be invariant across gender; this result was replicated within the current study, assessed by independent-samples t-test. Additionally, experienced sports participants have higher imagery ability than those less experienced; this result was also replicated within the current study, assessed by analysis of variance, supporting construct validity. Results provide preliminary evidence that the VMIQ-2A is reliable and valid to be used with a general population who are native Arabic speakers. Future research will include validation of the VMIQ-2A in a larger sample, and testing validity in specific patient populations.

Keywords: motor imagery, physiotherapy, translation and validation, imagery ability

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Authors: Subhash Nerella, Ziyuan Guan, Azra Bihorac, Parisa Rashidi

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Intensive care units (ICUs) provide care to critically ill patients in severe and life-threatening conditions. However, patient monitoring in the ICU is limited by the time and resource constraints imposed on healthcare providers. Many critical care indices such as mobility are still manually assessed, which can be subjective, prone to human errors, and lack granularity. Other important aspects, such as environmental factors, are not monitored at all. For example, critically ill patients often experience circadian disruptions due to the absence of effective environmental “timekeepers” such as the light/dark cycle and the systemic effect of acute illness on chronobiologic markers. Although the occurrence of delirium is associated with circadian disruption risk factors, these factors are not routinely monitored in the ICU. Hence, there is a critical unmet need to develop systems for precise and real-time assessment through novel enabling technologies. We have developed the mobility and circadian disruption quantification system (Mobi-DiQ) by augmenting biomarker and clinical data with pervasive sensing data to generate mobility and circadian cues related to mobility, nightly disruptions, and light and noise exposure. We hypothesize that Mobi-DiQ can provide accurate mobility and circadian cues that correlate with bedside clinical mobility assessments and circadian biomarkers, ultimately important for delirium risk assessment and prevention. The collected multimodal dataset consists of depth images, Electromyography (EMG) data, patient extremity movement captured by accelerometers, ambient light levels, Sound Pressure Level (SPL), and indoor air quality measured by volatile organic compounds, and the equivalent CO₂ concentration. For delirium risk assessment, the system recognizes mobility cues (axial body movement features and body key points) and circadian cues, including nightly disruptions, ambient SPL, and light intensity, as well as other environmental factors such as indoor air quality. The Mobi-DiQ system consists of three major components: the pervasive sensing system, a data storage and analysis server, and a data annotation system. For data collection, six local pervasive sensing systems were deployed, including a local computer and sensors. A video recording tool with graphical user interface (GUI) developed in python was used to capture depth image frames for analyzing patient mobility. All sensor data is encrypted, then automatically uploaded to the Mobi-DiQ server through a secured VPN connection. Several data pipelines are developed to automate the data transfer, curation, and data preparation for annotation and model training. The data curation and post-processing are performed on the server. A custom secure annotation tool with GUI was developed to annotate depth activity data. The annotation tool is linked to the MongoDB database to record the data annotation and to provide summarization. Docker containers are also utilized to manage services and pipelines running on the server in an isolated manner. The processed clinical data and annotations are used to train and develop real-time pervasive sensing systems to augment clinical decision-making and promote targeted interventions. In the future, we intend to evaluate our system as a clinical implementation trial, as well as to refine and validate it by using other data sources, including neurological data obtained through continuous electroencephalography (EEG).

Keywords: deep learning, delirium, healthcare, pervasive sensing

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Authors: Delsy Salinas, Andreia Garcês, Augusto Silva, Paula Brilhante Simões

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Urinary tract infection (UTI) is a common disease affecting dogs and cats in both community and hospital environment. Bacteria is the most frequent agent isolated, fewer than 1% of infections are due to parasitic, fungal, or viral agents. Common symptoms and laboratory abnormalities includeabdominal pain, pyrexia, renomegaly, and neutrophilia with left shift. A rapid and precise identification of the bacterial agent is still a challenge in veterinarian laboratories. Therefore, this cross-sectional study aims to describe bacterial colony patterns of urine samples by using chromID™ CPS® EliteAgar (BioMérieux, France) from canine and feline specimens submitted to a veterinary laboratory in Portugal (INNO Veterinary Laboratory, Braga)from January to March2022. All urine samples were cultivated in CPS Elite Agar with calibrated 1 µL inoculating loop and incubated at 37ºC for 18-24h. Color,size, and shape (regular or irregular outline)were recorded for all samples. All colonies were classified as Gram-negative or Gram-positive bacteriausing Gram stain (PREVI® Color BioMérieux, France) and determined if they were pure colonies. Identification of bacteria species was performed using GP and GN cards inVitek 2® Compact(BioMérieux, France). A total of 256/1003 submitted urine samples presented bacterial growth, from which 172 isolates were included in this study. The sample’s population included 111 dogs (n=45 males and n=66 females) and 61 cats (n=35 males and n=26 females). The most frequent isolated bacteria wasEscherichia coli (44,7%), followed by Proteus mirabilis (13,4%). All Escherichia coli isolates presented red to burgundy colonies, a colony diameter between 2 to 6 mm, and regular or irregular outlines. Similarly, 100% of Proteus mirabilis isolates were dark yellow colonies with a diffuse pigment and the same size and shape as Escherichia coli. White and pink pale colonies where Staphylococcus species exclusively and S. pseudintermedius was the most frequent (8,2 %). Cian to blue colonies were mostly Enterococcusspp. (8,2%) and Streptococcus spp. (4,6%). Beige to brown colonies were Pseudomonas aeruginosa (2,9%) and Citrobacter spp. (1,2%).Klebsiella spp.,Serratia spp. and Enterobacter spp were green colonies. All Gram-positive isolates were 1 to 2 mm diameter long and had a regular outline, meanwhile, Gram-negative rods presented variable patterns. This results showed that theprevalence of E coli and P. mirabilis as uropathogenic agents follows the same trends in Europe as previously described in other studies. Both agents presented a particular color pattern in CPS Elite Agar to identify them without needing complementary tests. No other bacteria genus could be correlated strongly to a specific color pattern, and similar results have been observed instudies using human’s samples. Chromogenic media shows a great advantage for common urine bacteria isolation than traditional COS, McConkey, and CLEDAgar mediums in a routine context, especially when mixed fermentative Gram-negative agents grow simultaneously. In addition, CPS Elite Agar is versatile for Artificial Intelligent Reading Plates Systems. Routine veterinarian laboratories could use CPS Elite Agar for a rapid screening for bacteria identification,mainlyE coli and P.mirabilis, saving 6h to 10h of automatized identification.

Keywords: cats, CPS elite agar, dogs, urine pathogens

Procedia PDF Downloads 72

Authors: Georgina Cherry, Taranpreet Rai, Luke Boyden, Sitira Williams, Andrea Wright, Richard Brown, Viva Chu, Alasdair Cook, Kevin Wells

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Estimating population-level burden, abilities of pet-parents to identify disease and demand for veterinary services worldwide is challenging. The purpose of this study is to compare a feline pruritus survey with social media listening (SML) data discussing this condition. Surveys are expensive and labour intensive to analyse, but SML data is freeform and requires careful filtering for relevancy. This study considers data from a survey of owner-observed symptoms of 156 pruritic cats conducted using Pet Parade® and SML posts collected through web-scraping to gain insights into the characterisation and management of feline pruritus. SML posts meeting a feline body area, behaviour and symptom were captured and reviewed for relevance representing 1299 public posts collected from 2021 to 2023. The survey involved 1067 pet-parents who reported on pruritic symptoms in their cats. Among the observed cats, approximately 18.37% (n=196) exhibited at least one symptom. The most frequently reported symptoms were hair loss (9.2%), bald spots (7.3%) and infection, crusting, scaling, redness, scabbing, scaling, or bumpy skin (8.2%). Notably, bald spots were the primary symptom reported for short-haired cats, while other symptoms were more prevalent in medium and long-haired cats. Affected body areas, according to pet-parents, were primarily the head, face, chin, neck (27%), and the top of the body, along the spine (22%). 35% of all cats displayed excessive behaviours consistent with pruritic skin disease. Interestingly, 27% of these cats were perceived as non-symptomatic by their owners, suggesting an under-identification of itch-related signs. Furthermore, a significant proportion of symptomatic cats did not receive any skin disease medication, whether prescribed or over the counter (n=41). These findings indicate a higher incidence of pruritic skin disease in cats than recognized by pet owners, potentially leading to a lack of medical intervention for clinically symptomatic cases. The comparison between the survey and social media listening data revealed bald spots were reported in similar proportions in both datasets (25% in the survey and 28% in SML). Infection, crusting, scaling, redness, scabbing, scaling, or bumpy skin accounted for 31% of symptoms in the survey, whereas it represented 53% of relevant SML posts (excluding bumpy skin). Abnormal licking or chewing behaviours were mentioned by pet-parents in 40% of SML posts compared to 38% in the survey. The consistency in the findings of these two disparate data sources, including a complete overlap in affected body areas for the top 80% of social media listening posts, indicates minimal biases in each method, as significant biases would likely yield divergent results. Therefore, the strong agreement across pruritic symptoms, affected body areas, and reported behaviours enhances our confidence in the reliability of the findings. Moreover, the small differences identified between the datasets underscore the valuable insights that arise from utilising multiple data sources. These variations provide additional depth in characterising and managing feline pruritus, allowing for more comprehensive understanding of the condition. By combining survey data and social media listening, researchers can obtain a nuanced perspective and capture a wider range of experiences and perspectives, supporting informed decision-making in veterinary practice.

Keywords: social media listening, feline pruritus, surveys, felines, cats, pet owners

Procedia PDF Downloads 99

Authors: Dongping Fang, Lian Duan, Xiaojing Yuan, Mike Xu, Allyn Klunder, Kevin Tan, Suiting Cao, Yeqing Ji

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Accurate prediction of a medical condition with straight clinical evidence is a long-sought topic in the medical management and health insurance field. Although great progress has been made with machine learning algorithms, the medical community is still, to a certain degree, suspicious about the model's accuracy and interpretability. This paper presents an innovative hierarchical attention deep learning model to achieve good prediction and clear interpretability that can be easily understood by medical professionals. This deep learning model uses a hierarchical attention structure that matches naturally with the medical history data structure and reflects the member’s encounter (date of service) sequence. The model attention structure consists of 3 levels: (1) attention on the medical code types (diagnosis codes, procedure codes, lab test results, and prescription drugs), (2) attention on the sequential medical encounters within a type, (3) attention on the medical codes within an encounter and type. This model is applied to predict the occurrence of stage 3 chronic kidney disease (CKD3), using three years’ medical history of Medicare Advantage (MA) members from a top health insurance company. The model takes members’ medical events, both claims and electronic medical record (EMR) data, as input, makes a prediction of CKD3 and calculates the contribution from individual events to the predicted outcome. The model outcome can be easily explained with the clinical evidence identified by the model algorithm. Here are examples: Member A had 36 medical encounters in the past three years: multiple office visits, lab tests and medications. The model predicts member A has a high risk of CKD3 with the following well-contributed clinical events - multiple high ‘Creatinine in Serum or Plasma’ tests and multiple low kidneys functioning ‘Glomerular filtration rate’ tests. Among the abnormal lab tests, more recent results contributed more to the prediction. The model also indicates regular office visits, no abnormal findings of medical examinations, and taking proper medications decreased the CKD3 risk. Member B had 104 medical encounters in the past 3 years and was predicted to have a low risk of CKD3, because the model didn’t identify diagnoses, procedures, or medications related to kidney disease, and many lab test results, including ‘Glomerular filtration rate’ were within the normal range. The model accurately predicts members A and B and provides interpretable clinical evidence that is validated by clinicians. Without extra effort, the interpretation is generated directly from the model and presented together with the occurrence date. Our model uses the medical data in its most raw format without any further data aggregation, transformation, or mapping. This greatly simplifies the data preparation process, mitigates the chance for error and eliminates post-modeling work needed for traditional model explanation. To our knowledge, this is the first paper on an interpretable deep-learning model using a 3-level attention structure, sourcing both EMR and claim data, including all 4 types of medical data, on the entire Medicare population of a big insurance company, and more importantly, directly generating model interpretation to support user decision. In the future, we plan to enrich the model input by adding patients’ demographics and information from free-texted physician notes.

Keywords: deep learning, interpretability, attention, big data, medical conditions

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Authors: Sarah Niklas, Lynne Chester, Mark Diesendorf

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Geopolitical tensions, climate change and recent movements favouring a transformative shift in institutional power structures have influenced the economics of conventional energy supply for decades. This study takes a multi-dimensional approach to illustrate the potential of renewable energy (RE) technology to provide a pathway to a low-carbon economy driven by ecologically sustainable, independent and socially just energy. This comparative analysis identifies economic, political and social drivers that shaped the adoption of RE policy in two significantly different economies, Germany and Australia, with strong and weak commitments to RE respectively. Two complementary political-economy theories frame the document-based analysis. Régulation Theory, inspired by Marxist ideas and strongly influenced by contemporary economic problems, provides the background to explore the social relationships contributing the adoption of RE within the macro-economy. Varieties of Capitalism theory, a more recently developed micro-economic approach, examines the nature of state-firm relationships. Together these approaches provide a comprehensive lens of analysis. Germany’s energy policy transformed substantially over the second half of the last century. The development is characterised by the coordination of societal, environmental and industrial demands throughout the advancement of capitalist regimes. In the Fordist regime, mass production based on coal drove Germany’s astounding economic recovery during the post-war period. Economic depression and the instability of institutional arrangements necessitated the impulsive seeking of national security and energy independence. During the postwar Flexi-Fordist period, quality-based production, innovation and technology-based competition schemes, particularly with regard to political power structures in and across Europe, favoured the adoption of RE. Innovation, knowledge and education were institutionalized, leading to the legislation of environmental concerns. Lastly the establishment of government-industry-based coordinative programs supported the phase out of nuclear power and the increased adoption of RE during the last decade. Australia’s energy policy is shaped by the country’s richness in mineral resources. Energy policy largely served coal mining, historically and currently one of the most capital-intense industry. Assisted by the macro-economic dimensions of institutional arrangements, social and financial capital is orientated towards the export-led and strongly demand-oriented economy. Here energy policy serves the maintenance of capital accumulation in the mining sector and the emerging Asian economies. The adoption of supportive renewable energy policy would challenge the distinct role of the mining industry within the (neo)-liberal market economy. The state’s protective role of the mining sector has resulted in weak commitment to RE policy and investment uncertainty in the energy sector. Recent developments, driven by strong public support for RE, emphasize the sense of community in urban and rural areas and the emergence of a bottom-up approach to adopt renewables. Thus, political economy frameworks on both the macro-economic (Regulation Theory) and micro-economic (Varieties of Capitalism theory) scales can together explain the strong commitment to RE in Germany vis-à-vis the weak commitment in Australia.

Keywords: political economy, regulation theory, renewable energy, social relationships, energy transitions

Procedia PDF Downloads 361

Authors: Justin Woulfe

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Siloed logistics and supply chain management systems throughout the Department of Defense (DOD) has led to disparate approaches to modeling and simulation (M&S), a lack of understanding of how one system impacts the whole, and issues with “optimal” solutions that are good for one organization but have dramatic negative impacts on another. Many different systems have evolved to try to understand and account for uncertainty and try to reduce the consequences of the unknown. As the DoD undertakes expansive digital transformation initiatives, there is an opportunity to fuse and leverage traditionally disparate data into a centrally hosted source of truth. With a streamlined process incorporating machine learning (ML) and artificial intelligence (AI), advanced M&S will enable informed decisions guiding program success via optimized operational readiness and improved mission success. One of the current challenges is to leverage the terabytes of data generated by monitored systems to provide actionable information for all levels of users. The implementation of a cloud-based application analyzing data transactions, learning and predicting future states from current and past states in real-time, and communicating those anticipated states is an appropriate solution for the purposes of reduced latency and improved confidence in decisions. Decisions made from an ML and AI application combined with advanced optimization algorithms will improve the mission success and performance of systems, which will improve the overall cost and effectiveness of any program. The Systecon team constructs and employs model-based simulations, cutting across traditional silos of data, aggregating maintenance, and supply data, incorporating sensor information, and applying optimization and simulation methods to an as-maintained digital twin with the ability to aggregate results across a system’s lifecycle and across logical and operational groupings of systems. This coupling of data throughout the enterprise enables tactical, operational, and strategic decision support, detachable and deployable logistics services, and configuration-based automated distribution of digital technical and product data to enhance supply and logistics operations. As a complete solution, this approach significantly reduces program risk by allowing flexible configuration of data, data relationships, business process workflows, and early test and evaluation, especially budget trade-off analyses. A true capability to tie resources (dollars) to weapon system readiness in alignment with the real-world scenarios a warfighter may experience has been an objective yet to be realized to date. By developing and solidifying an organic capability to directly relate dollars to readiness and to inform the digital twin, the decision-maker is now empowered through valuable insight and traceability. This type of educated decision-making provides an advantage over the adversaries who struggle with maintaining system readiness at an affordable cost. The M&S capability developed allows program managers to independently evaluate system design and support decisions by quantifying their impact on operational availability and operations and support cost resulting in the ability to simultaneously optimize readiness and cost. This will allow the stakeholders to make data-driven decisions when trading cost and readiness throughout the life of the program. Finally, sponsors are available to validate product deliverables with efficiency and much higher accuracy than in previous years.

Keywords: artificial intelligence, digital transformation, machine learning, predictive analytics

Procedia PDF Downloads 136

Authors: Robert E. Kenney, Efrain Antunez, Samuel Nodal, Ameer Malik, Richard B. Aguilar

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Physician burnout has gained much attention during the COVID pandemic. After-hours workload, HCC coding, HEDIS metrics, and clinical documentation negatively impact career satisfaction. These and other influences have increased the rate of physicians leaving the workforce. In addition, roughly 1% of the entire physician workforce will be retiring earlier than expected based on pre-pandemic trends. The two Medical Specialties with the highest rates of burnout are Family Medicine and Primary Care. With a predicted shortage of primary care physicians looming, the need to address physician burnout is crucial. Commonly reported issues leading to clinician burnout are clerical documentation requirements, increased time working on Electronic Health Records (EHR) after hours, and a decrease in work-life balance. Clinicians experiencing burnout with physical and emotional exhaustion are at an increased likelihood of providing lower quality and less efficient patient care. This may include a lack of suitable clinical documentation, medication reconciliation, clinical assessment, and treatment plans. While the annual baseline turnover rates of physicians hover around 6-7%, the COVID pandemic profoundly disrupted the delivery of healthcare. A report found that 43% of physicians switched jobs during the initial two years of the COVID pandemic (2020 and 2021), tripling the expected average annual rate to 21.5 %/yr. During this same time, an average of 4% and 1.5% of physicians retired or left the workforce for a non-clinical career, respectively. The report notes that 35.2% made career changes for a better work-life balance and another 35% reported the reason as being unhappy with their administration’s response to the pandemic. A physician-led primary care-focused health organization, Cano Health (CH), based out of Florida, sought to preemptively address this problem by implementing several supportive measures. Working with >120 clinics and >280 PCPs from Miami to Tampa and Orlando, managing nearly 120,000 Medicare Advantage lives, CH implemented a number of changes to assist with the clinician’s workload. Supportive services such as after hour and home visits by APRNs, in-clinic care managers, and patient educators were implemented. In 2021, assistive Artificial Intelligence Software (AIS) was integrated into the EHR platform. This AIS converts free text within PDF files into a usable (copy-paste) format facilitating documentation. The software also systematically and chronologically organizes clinical data, including labs, medical records, consultations, diagnostic images, medications, etc., into an easy-to-use organ system or chronic disease state format. This reduced the excess time and documentation burden required to meet payor and CMS guidelines. A clinician Documentation Support team was employed to improve the billing/coding performance. The effects of these newly designed workflow interventions were measured via analysis of clinician turnover from CH’s hiring and termination reporting software. CH’s annualized average clinician turnover rate in 2020 and 2021 were 17.7% and 12.6%, respectively. This represents a 30% relative reduction in turnover rate compared to the reported national average of 21.5%. Retirement rates during both years were 0.1%, demonstrating a relative reduction of >95% compared to the national average (4%). This model successfully promoted the retention of clinicians in a Value-Based Care setting.

Keywords: clinician burnout, COVID-19, value-based care, burnout, clinician retirement

Procedia PDF Downloads 62

Authors: Jennifer Wheeldon, Nick de Viggiani, Nikki Cotterill

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Background: Urinary and fecal incontinence affect a significant proportion of older adults aged 65 and over who permanently reside in residential and nursing home facilities. Incontinence symptoms have been linked to comorbidities, an increased risk of infection and reduced quality of life and mental wellbeing of residents. However, continence care provision can often be poor, further compromising the health and wellbeing of this vulnerable population. Objectives: To identify experiences and perceptions of continence care provision in older adult residential care settings and to identify factors that help or hinder good continence care provision. Settings included both residential care homes and nursing homes for older adults. Methods: A qualitative evidence synthesis using systematic review methodology established the current evidence-base. Data from 20 qualitative and mixed-method studies was appraised and synthesized. Following the review process, 10* qualitative interviews with staff working in older adult residential care settings were conducted across six* sites, which included registered managers, registered nurses and nursing/care assistants/aides. Purposive sampling recruited individuals from across England. Both evidence synthesis and interview data was analyzed thematically, both manually and with NVivo software. Results: The evidence synthesis revealed complex barriers and facilitators for continence care provision at three influencing levels: macro (structural and societal external influences), meso (organizational and institutional influences) and micro (day-to-day actions of individuals impacting service delivery). Macro-level barriers included negative stigmas relating to incontinence, aging and working in the older adult social care sector, restriction of continence care resources such as containment products (i.e. pads), short staffing in care facilities, shortfalls in the professional education and training of care home staff and the complex health and social care needs of older adult residents. Meso-level barriers included task-centered organizational cultures, ageist institutional perspectives regarding old age and incontinence symptoms, inadequate care home management and poor communication and teamwork among care staff. Micro-level barriers included poor knowledge and negative attitudes of care home staff and residents regarding incontinence symptoms and symptom management and treatment. Facilitators at the micro-level included proactive and inclusive leadership skills of individuals in management roles. Conclusions: The findings of the evidence synthesis study help to outline the complexities of continence care provision in older adult care homes facilities. Macro, meso and micro level influences demonstrate problematic and interrelated barriers across international contexts, indicating that improving continence care in this setting is extremely challenging due to the multiple levels at which care provision and services are impacted. Both international and national older adult social care policy-makers, researchers and service providers must recognize this complexity, and any intervention seeking to improve continence care in older adult care home settings must be planned accordingly and appreciatively of the complex and interrelated influences. It is anticipated that the findings of the qualitative interviews will shed further light on the national context of continence care provision specific to England; data collection is ongoing*. * Sample size is envisaged to be between 20-30 participants from multiple sites by Spring 2023.

Keywords: continence care, residential and nursing homes, evidence synthesis, qualitative

Procedia PDF Downloads 60

Authors: Isabelle Barrett

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Natural watercourses provide a range of vital ecosystem services, notably freshwater provision. They also offer highly heterogeneous habitat which supports an extreme diversity of aquatic life. Exploitation of rivers, changing land use and flood prevention measures have led to habitat degradation and subsequent biodiversity loss; indeed, freshwater species currently face a disproportionate rate of extinction compared to their terrestrial and marine counterparts. Large woody debris (LWD) encompasses the trees, large branches and logs which fall into watercourses, and is responsible for important habitat characteristics. Historically, natural LWD has been removed from streams under the assumption that it is not aesthetically pleasing and is thus ecologically unfavourable, despite extensive evidence contradicting this. Restoration efforts aim to replace lost LWD in order to reinstate habitat heterogeneity. This paper aims to assess the current state of such restoration schemes for improving fluvial ecological health in the UK. A detailed review of the scientific literature was conducted alongside a meta-analysis of 25 UK-based projects involving LWD restoration. Projects were chosen for which sufficient information was attainable for analysis, covering a broad range of budgets and scales. The most effective strategies for river restoration encompass ecological success, stakeholder engagement and scientific advancement, however few projects surveyed showed sensitivity to all three; for example, only 32% of projects stated biological aims. Focus tended to be on stakeholder engagement and public approval, since this is often a key funding driver. Consequently, there is a tendency to focus on the aesthetic outcomes of a project, however physical habitat restoration does not necessarily lead to direct biodiversity increases. This highlights the significance of rivers as highly heterogeneous environments with multiple interlinked processes, and emphasises a need for a stronger scientific presence in project planning. Poor scientific rigour means monitoring is often lacking, with varying, if any, definitions of success which are rarely pre-determined. A tendency to overlook negative or neutral results was apparent, with unjustified focus often put on qualitative results. The temporal scale of monitoring is typically inadequate to facilitate scientific conclusions, with only 20% of projects surveyed reporting any pre-restoration monitoring. Furthermore, monitoring is often limited to a few variables, with biotic monitoring often fish-focussed. Due to their longer life cycles and dispersal capability, fish are usually poor indicators of environmental change, making it difficult to attribute any changes in ecological health to restoration efforts. Although the potential impact of LWD restoration may be positive, this method of restoration could simply be making short-term, small-scale improvements; without addressing the underlying symptoms of degradation, for example water quality, the issue cannot be fully resolved. Promotion of standardised monitoring for LWD projects could help establish a deeper understanding of the ecology surrounding the practice, supporting movement towards adaptive management in which scientific evidence feeds back to practitioners, enabling the design of more efficient projects with greater ecological success. By highlighting LWD, this study hopes to address the difficulties faced within river management, and emphasise the need for a more holistic international and inter-institutional approach to tackling problems associated with degradation.

Keywords: biological monitoring, ecological health, large woody debris, river management, river restoration

Procedia PDF Downloads 181

Authors: Zeinab Zaremohzzabieh, Syasya Firzana Azmi, Haslinda Abdullah, Soh Kim Geok, Aini Azeqa Ma'rof, Hayrol Azril Mohammed Shaffril

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The escalating prevalence of doping in sports, casting a shadow over both high-performance and recreational settings, has emerged as a formidable concern, particularly within the realm of young athletes. Doping, characterized by the surreptitious use of prohibited substances to gain a competitive edge, underscores the pressing need for comprehensive and efficacious preventive measures. This study aims to address a crucial void in current research by unraveling the motivations that drive clean adolescent athletes to steadfastly abstain from performance-enhancing substances. In navigating this intricate landscape, the study adopts a positive psychology perspective, investigating into the conditions and processes that contribute to the holistic well-being of individuals and communities. At the heart of this exploration lies the application of the PERMA model, a comprehensive positive psychology framework encapsulating positive emotion, engagement, relationships, meaning, and accomplishments. This model functions as a distinctive lens, dissecting intervention results to offer nuanced insights into the complex dynamics of clean sport behavior. The research is poised to usher in a paradigm shift from conventional anti-doping strategies, predominantly fixated on identifying deficits, towards an innovative approach firmly rooted in positive psychology. The objective of this study is to evaluate the efficacy of a positive education intervention program tailored to promote clean sport behavior among Malaysian adolescent athletes. Representing unexplored terrain within the landscape of anti-doping efforts, this initiative endeavors to reshape the focus from deficiencies to strengths. The meticulously crafted pilot study engages thirty adolescent athletes, divided into a control group of 15 and an experimental group of 15. The pilot study serves as the crucible to assess the effectiveness of the prepared intervention package, providing indispensable insights that will meticulously guide the finalization of an all-encompassing intervention program for the main study. The main study adopts a pioneering two-arm randomized control trial methodology, actively involving adolescent athletes from diverse Malaysian high schools. This approach aims to address critical lacunae in anti-doping strategies, specifically calibrated to resonate with the unique context of Malaysian schools. The study, cognizant of the imperative to develop preventive measures harmonizing with the cultural and educational milieu of Malaysian adolescent athletes, aspires to cultivate a culture of clean sport. In conclusion, this research aspires to contribute unprecedented insights into the efficacy of positive education interventions firmly rooted in the PERMA model. By unraveling the intricacies of clean sport behavior, particularly within the context of Malaysian adolescent athletes, the study seeks to introduce transformative preventive methods. The adoption of positive psychology as an avant-garde anti-doping tool represents an innovative and promising approach, bridging a conspicuous gap in scholarly research and offering potential panaceas for the sporting community. As this study unfurls its chapters, it carries the promise not only to enrich our understanding of clean sport behavior but also to pave the way for positive metamorphosis within the realm of adolescent sports in Malaysia.

Keywords: positive education interventions, a pilot study, clean sport behavior, adolescent athletes, Malaysia

Procedia PDF Downloads 32

Authors: Agboka Komi Mensah, John Odindi, Elfatih M. Abdel-Rahman, Onisimo Mutanga, Henri Ez Tonnang

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Ecosystems are networks of organisms and populations that form a community of various species interacting within their habitats. Such habitats are defined by abiotic and biotic conditions that establish the initial limits to a population's growth, development, and reproduction. The habitat’s conditions explain the context in which species interact to access resources such as food, water, space, shelter, and mates, allowing for feeding, dispersal, and reproduction. Dispersal is an essential life-history strategy that affects gene flow, resource competition, population dynamics, and species distributions. Despite the importance of dispersal in population dynamics and survival, understanding the mechanism underpinning the dispersal of organisms remains challenging. For instance, when an organism moves into an ecosystem for survival and resource competition, its progression is highly influenced by extrinsic factors such as its physiological state, climatic variables and ability to evade predation. Therefore, greater spatial detail is necessary to understand organism dispersal dynamics. Understanding organisms dispersal can be addressed using empirical and mechanistic modelling approaches, with the adopted approach depending on the study's purpose Cellular automata (CA) is an example of these approaches that have been successfully used in biological studies to analyze the dispersal of living organisms. Cellular automata can be briefly described as occupied cells by an individual that evolves based on proper decisions based on a set of neighbours' rules. However, in the ambit of modelling individual organisms dispersal at the landscape scale, we lack user friendly tools that do not require expertise in mathematical models and computing ability; such as a visual analytics framework for tracking and forecasting the dispersal behaviour of organisms. The term "visual analytics" (VA) describes a semiautomated approach to electronic data processing that is guided by users who can interact with data via an interface. Essentially, VA converts large amounts of quantitative or qualitative data into graphical formats that can be customized based on the operator's needs. Additionally, this approach can be used to enhance the ability of users from various backgrounds to understand data, communicate results, and disseminate information across a wide range of disciplines. To support effective analysis of the dispersal of organisms at the landscape scale, we therefore designed Pydisp which is a free visual data analytics tool for spatiotemporal dispersal modeling built in Python. Its user interface allows users to perform a quick and interactive spatiotemporal analysis of species dispersal using bioecological and climatic data. Pydisp enables reuse and upgrade through the use of simple principles such as Fuzzy cellular automata algorithms. The potential of dispersal modeling is demonstrated in a case study by predicting the dispersal of Fopius arisanus (Sonan), endoparasitoids to control Bactrocera dorsalis (Hendel) (Diptera: Tephritidae) in Kenya. The results obtained from our example clearly illustrate the parasitoid's dispersal process at the landscape level and confirm that dynamic processes in an agroecosystem are better understood when designed using mechanistic modelling approaches. Furthermore, as demonstrated in the example, the built software is highly effective in portraying the dispersal of organisms despite the unavailability of detailed data on the species dispersal mechanisms.

Keywords: cellular automata, fuzzy logic, landscape, spatiotemporal

Procedia PDF Downloads 58

Authors: Evelyn Castle, Adam Thompson

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Background: In 2013, the Kano State Primary Health Care Management Board redesigned its Routine immunization supply chain from diffused pull to direct delivery push. It addressed issues around stockouts and reduced time spent by health facility staff collecting, and reporting on vaccine usage. The health care board sought the help of a 3PL for twice-monthly deliveries from its cold store to 484 facilities across 44 local governments. eHA’s Health Delivery Systems group formed a 3PL to serve 326 of these new facilities in partnership with the State. We focused on designing and implementing a technology system throughout. Basic methodologies: GIS Mapping: - Planning the delivery of vaccines to hundreds of health facilities requires detailed route planning for delivery vehicles. Mapping the road networks across Kano and Bauchi with a custom routing tool provided information for the optimization of deliveries. Reducing the number of kilometers driven each round by 20%, - reducing cost and delivery time. Direct Delivery Information System: - Vaccine Direct Deliveries are facilitated through pre-round planning (driven by health facility database, extensive GIS, and inventory workflow rules), manager and driver control panel customizing delivery routines and reporting, progress dashboard, schedules/routes, packing lists, delivery reports, and driver data collection applications. Move: Last Mile Logistics Management System: - MOVE has improved vaccine supply information management to be timely, accurate and actionable. Provides stock management workflow support, alerts management for cold chain exceptions/stock outs, and on-device analytics for health and supply chain staff. Software was built to be offline-first with user-validated interface and experience. Deployed to hundreds of vaccine storage site the improved information tools helps facilitate the process of system redesign and change management. Findings: - Stock-outs reduced from 90% to 33% - Redesigned current health systems and managing vaccine supply for 68% of Kano’s wards. - Near real time reporting and data availability to track stock. - Paperwork burdens of health staff have been dramatically reduced. - Medicine available when the community needs it. - Consistent vaccination dates for children under one to prevent polio, yellow fever, tetanus. - Higher immunization rates = Lower infection rates. - Hundreds of millions of Naira worth of vaccines successfully transported. - Fortnightly service to 326 facilities in 326 wards across 30 Local Government areas. - 6,031 cumulative deliveries. - Over 3.44 million doses transported. - Minimum travel distance covered in a round of delivery is 2000 kms & maximum of 6297 kms. - 153,409 kms travelled by 6 drivers. - 500 facilities in 326 wards. - Data captured and synchronized for the first time. - Data driven decision making now possible. Conclusion: eHA’s Vaccine Direct delivery has met challenges in Kano and Bauchi State and provided a reliable delivery service of vaccinations that ensure t health facilities can run vaccination clinics for children under one. eHA uses innovative technology that delivers vaccines from Northern Nigerian zonal stores straight to healthcare facilities. Helped healthcare workers spend less time managing supplies and more time delivering care, and will be rolled out nationally across Nigeria.

Keywords: direct delivery information system, health delivery system, GIS mapping, Northern Nigeria, vaccines

Procedia PDF Downloads 346

Authors: Anne E. Goodenough

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One of the most important roles of higher education professionals is to ensure that graduates have excellent employment prospects. This means providing students with the skills necessary to be immediately effective in the workplace. Increasingly, universities are seeking to achieve this by moving from lecture-based and campus-delivered curricula to more varied delivery, which takes students out of their academic comfort zone and allows them to engage with, and be challenged by, real world issues. One popular approach is integration of problem-based learning (PBL) projects into curricula. However, although the potential benefits of PBL are considerable, it can be difficult to devise projects that are meaningful, such that they can be regarded as mere ‘hoop jumping’ exercises. This study examines three-way partnerships between academics, students, and external link organizations. It studied the experiences of all partners involved in different collaborative projects to identify how benefits can be maximized and challenges overcome. Focal collaborations included: (1) development of real-world modules with novel assessment whereby the organization became the ‘client’ for student consultancy work; (2) frameworks where students collected/analyzed data for link organizations in research methods modules; (3) placement-based internships and dissertations; (4) immersive fieldwork projects in novel locations; and (5) students working as partners on staff-led research with link organizations. Focus groups, questionnaires and semi-structured interviews were used to identify opportunities and barriers, while quantitative analysis of students’ grades was used to determine academic effectiveness. Common challenges identified by academics were finding suitable link organizations and devising projects that simultaneously provided education opportunities and tangible benefits. There was no ‘one size fits all’ formula for success, but careful planning and ensuring clarity of roles/responsibilities were vital. Students were very positive about collaboration projects. They identified benefits to confidence, time-keeping and communication, as well as conveying their enthusiasm when their work was of benefit to the wider community. They frequently highlighted employability opportunities that collaborative projects opened up and analysis of grades demonstrated the potential for such projects to increase attainment. Organizations generally recognized the value of project outputs, but often required considerable assistance to put the right scaffolding in place to ensure projects worked. Benefits were maximized by ensuring projects were well-designed, innovative, and challenging. Co-publication of projects in peer-reviewed journals sometimes gave additional benefits for all involved, being especially beneficial for student curriculum vitae. PBL and student projects are by no means new pedagogic approaches: the novelty here came from creating meaningful three-way partnerships between academics, students, and link organizations at all undergraduate levels. Such collaborations can allow students to make a genuine contribution to knowledge, answer real questions, solve actual problems, all while providing tangible benefits to organizations. Because projects are actually needed, students tend to engage with learning at a deep level. This enhances student experience, increases attainment, encourages development of subject-specific and transferable skills, and promotes networking opportunities. Such projects frequently rely upon students and staff working collaboratively, thereby also acting to break down the traditional teacher/learner division that is typically unhelpful in developing students as advanced learners.

Keywords: higher education, employability, link organizations, innovative teaching and learning methods, interactions between enterprise and education, student experience

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Authors: Ananya Pappu, Sneha Mishra

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Introduction: The South Asian population experiences unique health challenges that predisposes this demographic to cardiometabolic diseases at lower BMIs. South Asians may therefore benefit from recommendations specific to their cultural needs. Here, we focus on current BMI guidelines for Asians with a discussion of South Asian dietary practices and culturally tailored interventions. By integrating traditional dietary practices with modern nutritional recommendations, this manuscript aims to highlight effective strategies to improving health outcomes among South Asians. Background: The South Asian community, including individuals from India, Pakistan, Bangladesh, and Sri Lanka, experiences high rates of cardiovascular diseases, cancers, diabetes, and strokes. Notably, the prevalence of diabetes and cardiovascular disease among Asians is elevated at BMIs below the WHO's standard overweight threshold. As it stands, a BMI of 25-30 kg/m² is considered overweight in non-Asians, while this cutoff is reduced to 23-27.4 kg/m² in Asians. This discrepancy can be attributed to studies which have shown different associations between BMI and health risks in Asians compared to other populations. Given these significant challenges, optimizing lifestyle management for cardiometabolic risk factors is crucial. Tailored interventions that consider cultural context seem to be the best approach for ensuring the success of both dietary and physical activity interventions in South Asian patients. Adopting a whole food, plant-based diet (WFPD) is one such strategy. The WFPD suggests that half of one meal should consist of non-starchy vegetables. In the South Asian diet, this includes traditional vegetables such as okra, tindora, eggplant, and leafy greens including amaranth, collards, chard, and mustards. A quarter of the meal should include plant-based protein sources like cooked beans, lentils, and paneer, with the remaining quarter comprising healthy grains or starches such as whole wheat breads, millets, tapioca, and barley. Adherence to the WFPD has been shown to improve cardiometabolic risk factors including weight, BMI, total cholesterol, HbA1c, and reduces the risk of developing non-alcoholic fatty liver disease (NAFLD). Another approach to improving dietary habits is timing meals. Many of the major cultures and religions in the Indian subcontinent incorporate religious fasting. Time-restricted eating (TRE), also known as intermittent fasting, is a practice akin to traditional fasting, which involves consuming all daily calories within a specific window. TRE has been shown to improve insulin resistance in prediabetic and diabetic patients. Common regimens include completing all meals within an 8-hour window, consuming a low-calorie diet every other day, and the 5:2 diet, which involves fasting twice weekly. These fasting practices align with the natural circadian rhythm, potentially enhancing metabolic health and reducing obesity and diabetes risks. Conclusion: South Asians develop cardiometabolic disease at lower BMIs; hence, it is important to counsel patients about lifestyle interventions that decrease their risk. Traditional South Asian diets can be made more nutrient-rich by incorporating vegetables, plant proteins like lentils and beans, and substituting refined grains for whole grains. Ultimately, the best diet is one to which a patient can adhere. It is therefore important to find a regimen that aligns with a patient’s cultural and traditional food practices.

Keywords: BMI, diet, obesity, South Asian, time-restricted eating

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Authors: Lolwa Alansari, Hanen Mrabet, Kholoud Khaled, Abdelhamid Azhaghdani, Sufia Athar, Aska Kaima, Zaineb Mhamdia, Zubaria Altaf, Almunzer Zakaria, Tamara Alshadafat

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Introduction: The Obstetrics and Gynecology Emergency Department at Alwakra Hospital has faced significant challenges, which have been further worsened by the impact of the COVID-19 pandemic. These challenges involve issues such as overcrowding, extended wait times, and a notable surge in demand for emergency care services. Moreover, prolonged waiting times have emerged as a primary factor contributing to situations where patients leave without receiving attention, known as left without being seen (LWBS), and unexpectedly abscond. Addressing the issue of insufficient patient mobility in the obstetrics and gynecology emergency department has brought about substantial improvements in patient care, healthcare administration, and overall departmental efficiency. These changes have not only alleviated overcrowding but have also elevated the quality of emergency care, resulting in higher patient satisfaction, better outcomes, and operational rewards. Methodology: The COVID-19 pandemic has served as a catalyst for substantial transformations in the obstetrics and gynecology emergency, aligning seamlessly with the strategic direction of Hamad Medical Corporation (HMC). The fundamental aim of this initiative is to revolutionize the operational efficiency of the OB-GYN ED. To accomplish this mission, a range of transformations has been initiated, focusing on essential areas such as digitizing systems, optimizing resource allocation, enhancing budget efficiency, and reducing overall costs. The project utilized the Plan-Do-Study-Act (PDSA) model, involving a diverse team collecting baseline data and introducing throughput improvements. Post-implementation data and feedback were analysed, leading to the integration of effective interventions into standard procedures. These interventions included optimized space utilization, real-time communication, bedside registration, technology integration, pre-triage screening, enhanced communication and patient education, consultant presence, and a culture of continuous improvement. These strategies significantly reduced waiting times, enhancing both patient care and operational efficiency. Results: Results demonstrated a substantial reduction in overall average waiting time, dropping from 35 to approximately 14 minutes by August 2023. The wait times for priority 1 cases have been reduced from 22 to 0 minutes, and for priority 2 cases, the wait times have been reduced from 32 to approximately 13.6 minutes. The proportion of patients spending less than 8 hours in the OB ED observation beds rose from 74% in January 2022 to over 98% in 2023. Notably, there was a remarkable decrease in LWBS and absconded patient rates from 2020 to 2023. Conclusion: The project initiated a profound change in the department's operational environment. Efficiency became deeply embedded in the unit's culture, promoting teamwork among staff that went beyond the project's original focus and had a positive influence on operations in other departments. This effectiveness not only made processes more efficient but also resulted in significant cost reductions for the hospital. These cost savings were achieved by reducing wait times, which in turn led to fewer prolonged patient stays and reduced the need for additional treatments. These continuous improvement initiatives have now become an integral part of the Obstetrics and Gynecology Division's standard operating procedures, ensuring that the positive changes brought about by the project persist and evolve over time.

Keywords: overcrowding, waiting time, person centered care, quality initiatives

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Authors: Zdravko Trivic, John Chye Fung, Ruzica Bozovic-Stamenovic

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Within the context of rapidly ageing population in Singapore and the pressing demands on both caregivers and care providers, an integrated approach to ageing-friendly and ability-sensitive enabling environment becomes an imperative. This particularly applies to nursing home environments and their immediate surroundings, as they are becoming one of the main available options of long-term care for many senior adults who are unable to age at home. Yet, despite the considerable efforts to break the still predominant clinical approach to eldercare and to introduce more home-like design and person-centric care model, nursing homes keep being stigmatised and perceived as not so desirable environments to grow old in. The challenges are further emphasised by the associated physical, sensorial, psychological and cognitive declines that are the common consequences of ageing. Such declines have an immense impact on almost all aspects of older adults’ daily functioning, including problems with mobility and spatial orientation, difficulties in communication, withdrawal from social interaction, higher level of depression and decreased sense of independence and autonomy. However, typical nursing home designs tend to neglect the full capacities of balanced and carefully integrated multisensory stimuli as active component of care and ability building. This paper outlines part of a larger multi-disciplinary study of six nursing homes in Singapore, with overarching objectives to create new models of supportive nursing home environments that go beyond the clinical care model and encourage community integration with the nursing home settings. The paper focuses on the largely neglected aspects of sensorial comfort and multi-sensorial properties of nursing homes, including both indoor and immediate outdoor spaces (boundaries). The objective was to investigate the sensory rhythms and explore their role in nursing home users’ daily routine and therapeutic capacities. Socio-sensory rhythms were captured and analysed through a combination of on-site sensory recordings of “objective” quantitative sensory data (air temperature and humidity, sound level and luminance) using multi-function environment meter, perceived experienced data, spatial mapping, first-person observations of nursing home users’ activity patterns, and interviews. This was done in addition to employment of available assessment tools, such as Wisconsin Person Directed Care assessment tool, Dementia Quality of Life [DQoL] instrument, and Resident Environment Impact Scale [REIS], as these tools address the issues of sensorial experience insufficiently and selectively. Key findings indicate varied levels of sensory comfort, as well as diversity, intensity, and customisation of multi-sensory conditions within different nursing home spaces. Sensory stimulation is typically concentrated in communal living areas of the nursing homes or in the areas that often provide controlled or limited access, including specifically designed sensory rooms and outdoor green spaces (gardens and terraces). Opportunities for sensory stimulation are particularly limited for bed-bound senior residents and within more functional areas, such as corridors. This suggests that the capacities of nursing home designs to provide more diverse and better integrated pleasant sensory conditions as integrated “therapeutic devices” to build nursing home residents’ physical and mental abilities, encourage activity and improve wellbeing are far from exhausted.

Keywords: ageing-supportive environment, enabling design, multi-sensory assessment, nursing home environment

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Authors: Gospel Iyioku, Jana Mazancova, Jiri Hejkrlik

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The “Agricultural Promotion Policy (2016–2020)” represents a strategic initiative by the Nigerian government to address domestic food shortages and the challenges in exporting products at the required quality standards. Hindered by an inefficient system for setting and enforcing food quality standards, coupled with a lack of market knowledge, the Federal Ministry of Agriculture and Rural Development (FMARD) aims to enhance support for the production and activities of key crops like cashew. By collaborating with farmers, processors, investors, and stakeholders in the cashew sector, the policy seeks to define and uphold high-quality standards across the cashew value chain. Given the challenges and opportunities faced by Nigerian cashew farmers, active participation in cashew marketing groups becomes imperative. These groups serve as essential platforms for farmers to collectively navigate market intricacies, access resources, share knowledge, improve output quality, and bolster their overall bargaining power. Through engagement in these cooperative initiatives, farmers not only boost their economic prospects but can also contribute significantly to the sustainable growth of the cashew industry, fostering resilience and community development. This study explores the perceptions and intentions of farmers regarding their involvement in cashew marketing cooperatives, utilizing an expanded version of the Theory of Planned Behaviour. Drawing insights from a diverse sample of 321 cashew farmers in Southwest Nigeria, the research sheds light on the factors influencing decision-making in cooperative participation. The demographic analysis reveals a diverse landscape, with a substantial presence of middle-aged individuals contributing significantly to the agricultural sector and cashew-related activities emerging as a primary income source for a substantial proportion (23.99%). Employing Structural Equation Modelling (SEM) with Maximum Likelihood Robust (MLR) estimation in R, the research elucidates the associations among latent variables. Despite the model’s complexity, the goodness-of-fit indices attest to the validity of the structural model, explaining approximately 40% of the variance in the intention to join cooperatives. Moral norms emerge as a pivotal construct, highlighting the profound influence of ethical considerations in decision-making processes, while perceived behavioural control presents potential challenges in active participation. Attitudes toward joining cooperatives reveal nuanced perspectives, with strong beliefs in enhanced connections with other farmers but varying perceptions on improved access to essential information. The SEM analysis establishes positive and significant effects of moral norms, perceived behavioural control, subjective norms, and attitudes on farmers’ intention to join cooperatives. The knowledge construct positively affects key factors influencing intention, emphasizing the importance of informed decision-making. A supplementary analysis using partial least squares (PLS) SEM corroborates the robustness of our findings, aligning with covariance-based SEM results. This research unveils the determinants of cooperative participation and provides valuable insights for policymakers and practitioners aiming to empower and support this vital demographic in the cashew industry.

Keywords: marketing cooperatives, theory of planned behaviour, structural equation modelling, cashew farmers

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Authors: Liane J. Ioannou, Jonathan Serpell, Cino Bendinelli, David Walters, Jenny Gough, Dean Lisewski, Win Meyer-Rochow, Julie Miller, Duncan Topliss, Bill Fleming, Stephen Farrell, Andrew Kiu, James Kollias, Mark Sywak, Adam Aniss, Linda Fenton, Danielle Ghusn, Simon Harper, Aleksandra Popadich, Kate Stringer, David Watters, Susannah Ahern

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BACKGROUND: There are significant variations in the management, treatment and outcomes of thyroid cancer, particularly in the role of: diagnostic investigation and pre-treatment scanning; optimal extent of surgery (total or hemi-thyroidectomy); use of active surveillance for small low-risk cancers; central lymph node dissections (therapeutic or prophylactic); outcomes following surgery (e.g. recurrent laryngeal nerve palsy, hypocalcaemia, hypoparathyroidism); post-surgical hormone, calcium and vitamin D therapy; and provision and dosage of radioactive iodine treatment. A proven strategy to reduce variations in the outcome and to improve survival is to measure and compare it using high-quality clinical registry data. Clinical registries provide the most effective means of collecting high-quality data and are a tool for quality improvement. Where they have been introduced at a state or national level, registries have become one of the most clinically valued tools for quality improvement. To benchmark clinical care, clinical quality registries require systematic measurement at predefined intervals and the capacity to report back information to participating clinical units. OBJECTIVE: The aim of this study was to develop a core set clinical indicators that enable measurement and reporting of quality of care for patients with thyroid cancer. We hypothesise that measuring clinical quality indicators, developed to identify differences in quality of care across sites, will reduce variation and improve patient outcomes and survival, thereby lessening costs and healthcare burden to the Australian community. METHOD: Preparatory work and scoping was conducted to identify existing high quality, clinical guidelines and best practice for thyroid cancer both nationally and internationally, as well as relevant literature. A bi-national panel was invited to participate in a modified Delphi process. Panelists were asked to rate each proposed indicator on a Likert scale of 1–9 in a three-round iterative process. RESULTS: A total of 236 potential quality indicators were identified. One hundred and ninety-two indicators were removed to reflect the data capture by the Australian and New Zealand Thyroid Cancer Registry (ANZTCR) (from diagnosis to 90-days post-surgery). The remaining 44 indicators were presented to the panelists for voting. A further 21 indicators were later added by the panelists bringing the total potential quality indicators to 65. Of these, 21 were considered the most important and feasible indicators to measure quality of care in thyroid cancer, of which 12 were recommended for inclusion in the final set. The consensus indicator set spans the spectrum of care, including: preoperative; surgery; surgical complications; staging and post-surgical treatment planning; and post-surgical treatment. CONCLUSIONS: This study provides a core set of quality indicators to measure quality of care in thyroid cancer. This indicator set can be applied as a tool for internal quality improvement, comparative quality reporting, public reporting and research. Inclusion of these quality indicators into monitoring databases such as clinical quality registries will enable opportunities for benchmarking and feedback on best practice care to clinicians involved in the management of thyroid cancer.

Keywords: clinical registry, Delphi survey, quality indicators, quality of care

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Authors: Yu-Hsiu Lin, Wen-Chun Lin, Yen-Chang Cheng, Chia-Ju Yeh, Yu-Chuan Chen, Tai-You Li

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Demand-Side Management (DSM) has the potential to reduce electricity costs and carbon emission, which are associated with electricity used in the modern society. A home Energy Management System (EMS) commonly used by residential consumers in a down-stream sector of a smart grid to monitor, control, and optimize energy efficiency to domestic appliances is a system of computer-aided functionalities as an energy audit for residential DSM. Implementing fault detection and classification to domestic appliances monitored, controlled, and optimized is one of the most important steps to realize preventive maintenance, such as residential air conditioning and heating preventative maintenance in residential/industrial DSM. In this study, a cloud intelligence-based green EMS that comes up with an Internet of Things (IoT) technology stack for residential DSM is developed. In the EMS, Arduino MEGA Ethernet communication-based smart sockets that module a Real Time Clock chip to keep track of current time as timestamps via Network Time Protocol are designed and implemented for readings of load phenomena reflecting on voltage and current signals sensed. Also, a Network-Attached Storage providing data access to a heterogeneous group of IoT clients via Hypertext Transfer Protocol (HTTP) methods is configured to data stores of parsed sensor readings. Lastly, a desktop computer with a WAMP software bundle (the Microsoft® Windows operating system, Apache HTTP Server, MySQL relational database management system, and PHP programming language) serves as a data science analytics engine for dynamic Web APP/REpresentational State Transfer-ful web service of the residential DSM having globally-Advanced Internet of Artificial Intelligence (AI)/Computational Intelligence. Where, an abstract computing machine, Java Virtual Machine, enables the desktop computer to run Java programs, and a mash-up of Java, R language, and Python is well-suited and -configured for AI in this study. Having the ability of sending real-time push notifications to IoT clients, the desktop computer implements Google-maintained Firebase Cloud Messaging to engage IoT clients across Android/iOS devices and provide mobile notification service to residential/industrial DSM. In this study, in order to realize edge intelligence that edge devices avoiding network latency and much-needed connectivity of Internet connections for Internet of Services can support secure access to data stores and provide immediate analytical and real-time actionable insights at the edge of the network, we upgrade the designed and implemented smart sockets to be embedded AI Arduino ones (called embedded AIduino). With the realization of edge analytics by the proposed embedded AIduino for data analytics, an Arduino Ethernet shield WizNet W5100 having a micro SD card connector is conducted and used. The SD library is included for reading parsed data from and writing parsed data to an SD card. And, an Artificial Neural Network library, ArduinoANN, for Arduino MEGA is imported and used for locally-embedded AI implementation. The embedded AIduino in this study can be developed for further applications in manufacturing industry energy management and sustainable energy management, wherein in sustainable energy management rotating machinery diagnostics works to identify energy loss from gross misalignment and unbalance of rotating machines in power plants as an example.

Keywords: demand-side management, edge intelligence, energy management system, fault detection and classification

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Authors: Lina Wu

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The excessive discharge of nitrogen in sewage greatly intensifies the eutrophication of water bodies and threatens water quality. Nitrogen pollution control has become a global concern. The concentration of nitrogen in water is reduced by converting ammonia nitrogen, nitrate nitrogen and nitrite nitrogen into nitrogen-containing gas through biological treatment, physicochemical treatment and oxidation technology. However, some wastewater containing high ammonia nitrogen including landfill leachate, is difficult to be treated by traditional nitrification and denitrification because of its high COD content. The core process of denitrification is that denitrifying bacteria convert nitrous acid produced by nitrification into nitrite under anaerobic conditions. Still, its low-carbon nitrogen does not meet the conditions for denitrification. Many studies have shown that the natural autotrophic anammox bacteria can combine nitrous and ammonia nitrogen without a carbon source through functional genes to achieve total nitrogen removal, which is very suitable for removing nitrogen from leachate. In addition, the process also saves a lot of aeration energy consumption than the traditional nitrogen removal process. Therefore, anammox plays an important role in nitrogen conversion and energy saving. The short-range nitrification and denitrification coupled with anaerobic ammoX ensures total nitrogen removal. It improves the removal efficiency, meeting the needs of society for an ecologically friendly and cost-effective nutrient removal treatment technology. In recent years, research has found that the symbiotic system has more water treatment advantages because this process not only helps to improve the efficiency of wastewater treatment but also allows carbon dioxide reduction and resource recovery. Microalgae use carbon dioxide dissolved in water or released through bacterial respiration to produce oxygen for bacteria through photosynthesis under light, and bacteria, in turn, provide metabolites and inorganic carbon sources for the growth of microalgae, which may lead the algal bacteria symbiotic system save most or all of the aeration energy consumption. It has become a trend to make microalgae and light-avoiding anammox bacteria play synergistic roles by adjusting the light-to-dark ratio. Microalgae in the outer layer of light particles block most of the light and provide cofactors and amino acids to promote nitrogen removal. In particular, myxoccota MYX1 can degrade extracellular proteins produced by microalgae, providing amino acids for the entire bacterial community, which helps anammox bacteria save metabolic energy and adapt to light. As a result, initiating and maintaining the process of combining dominant algae and anaerobic denitrifying bacterial communities has great potential in treating landfill leachate. Chlorella has a brilliant removal effect and can withstand extreme environments in terms of high ammonia nitrogen, high salt and low temperature. It is urgent to study whether the algal mud mixture rich in denitrifying bacteria and chlorella can greatly improve the efficiency of landfill leachate treatment under an anaerobic environment where photosynthesis is stopped. The optimal dilution concentration of simulated landfill leachate can be found by determining the treatment effect of the same batch of bacteria and algae mixtures under different initial ammonia nitrogen concentrations and making a comparison. High-throughput sequencing technology was used to analyze the changes in microbial diversity, related functional genera and functional genes under optimal conditions, providing a theoretical and practical basis for the engineering application of novel bacteria-algae symbiosis system in biogas slurry treatment and resource utilization.

Keywords: nutrient removal and recovery, leachate, anammox, Partial nitrification, Algae-bacteria interaction

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