Search results for: Peter Temitope Agboola

Authors: Yichao Liu, Peter Fransson, Julian Heidecke, Jonas Wallin, Joacim Rockloev

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Dengue, a mosquito-borne viral disease, poses a significant public health challenge in endemic tropical or subtropical countries, including Sri Lanka. To reveal insights into the complexity of the dynamics of this disease and study the drivers, a comprehensive model capable of both robust forecasting and insightful inference of drivers while capturing the co-circulating of several virus strains is essential. However, existing studies mostly focus on only one aspect at a time and do not integrate and carry insights across the siloed approach. While mechanistic models are developed to capture immunity dynamics, they are often oversimplified and lack integration of all the diverse drivers of disease transmission. On the other hand, purely data-driven methods lack constraints imposed by immuno-epidemiological processes, making them prone to overfitting and inference bias. This research presents a hybrid model that combines machine learning techniques with mechanistic modelling to overcome the limitations of existing approaches. Leveraging eight years of newly reported dengue case data, along with socioeconomic factors, such as human mobility, weekly climate data from 2011 to 2018, genetic data detecting the introduction and presence of new strains, and estimates of seropositivity for different districts in Sri Lanka, we derive a data-driven vector (SEI) to human (SEIR) model across 16 regions in Sri Lanka at the weekly time scale. By conducting ablation studies, the lag effects allowing delays up to 12 weeks of time-varying climate factors were determined. The model demonstrates superior predictive performance over a pure machine learning approach when considering lead times of 5 and 10 weeks on data withheld from model fitting. It further reveals several interesting interpretable findings of drivers while adjusting for the dynamics and influences of immunity and introduction of a new strain. The study uncovers strong influences of socioeconomic variables: population density, mobility, household income and rural vs. urban population. The study reveals substantial sensitivity to the diurnal temperature range and precipitation, while mean temperature and humidity appear less important in the study location. Additionally, the model indicated sensitivity to vegetation index, both max and average. Predictions on testing data reveal high model accuracy. Overall, this study advances the knowledge of dengue transmission in Sri Lanka and demonstrates the importance of incorporating hybrid modelling techniques to use biologically informed model structures with flexible data-driven estimates of model parameters. The findings show the potential to both inference of drivers in situations of complex disease dynamics and robust forecasting models.

Keywords: compartmental model, climate, dengue, machine learning, social-economic

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Authors: Breanna Wright, Peter Bragge

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Diagnostic error rates in healthcare are approximately 10% of cases. Diagnostic errors can cause patient harm due to inappropriate, inadequate or delayed treatment, and such errors contribute heavily to medical liability claims globally. Therefore, addressing diagnostic error is a high priority. In most cases, diagnostic errors are the result of faulty information synthesis rather than lack of knowledge. Specifically, the majority of diagnostic errors involve cognitive factors, and in particular, cognitive biases. Emergency Departments are an environment with heightened risk of diagnostic error due to time and resource pressures, a frequently chaotic environment, and patients arriving undifferentiated and with minimal context. This project aimed to develop a behavioural, evidence-informed intervention to reduce diagnostic error in Emergency Departments through co-design with emergency physicians, insurers, researchers, hospital managers, citizens and consumer representatives. The Forum Process was utilised to address this aim. This involves convening a small (4 – 6 member) expert panel to guide a focused literature and practice review; convening of a 10 – 12 person citizens panel to gather perspectives of laypeople, including those affected by misdiagnoses; and a 18 – 22 person structured stakeholder dialogue bringing together representatives of the aforementioned stakeholder groups. The process not only provides in-depth analysis of the problem and associated behaviours, but brings together expertise and insight to facilitate identification of a behaviour change intervention. Informed by the literature and practice review, the Citizens Panel focused on eliciting the values and concerns of those affected or potentially affected by diagnostic error. Citizens were comfortable with diagnostic uncertainty if doctors were honest with them. They also emphasised the importance of open communication between doctors and patients and their families. Citizens expect more consistent standards across the state and better access for both patients and their doctors to patient health information to avoid time-consuming re-taking of long patient histories and medication regimes when re-presenting at Emergency Departments and to reduce the risk of unintentional omissions. The structured Stakeholder Dialogue focused on identifying a feasible behavioural intervention to review diagnoses in Emergency Departments. This needed to consider the role of cognitive bias in medical decision-making; contextual factors (in Victoria, there is a legislated 4-hour maximum time between ED triage and discharge / hospital admission); resource availability; and the need to ensure the intervention could work in large metropolitan as well as small rural and regional ED settings across Victoria. The identified behavioural intervention will be piloted in approximately ten hospital EDs across Victoria, Australia. This presentation will detail the findings of all review and consultation activities, describe the behavioural intervention developed and present results of the pilot trial.

Keywords: behavioural intervention, cognitive bias, decision-making, diagnostic error

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Authors: Vijayabhaskar Reddy Kandula, Peter Provost Taillac, Balasubramanya M. A., Ram Krishnan Nair, Gokul Toshnival, Vibhu Dhawan, Vijaya Karanam, Buffy Cramer

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Introduction: The lack of Emergency Care Services (ECS) is a cause of extensive and serious public health problems in low- and middle-income countries (LMIC), Many LMIC countries have ambulance services that allow timely transfer of ill patients but due to poor care during the ‘Golden Hour’ many deaths occur which are otherwise preventable. Lack of adequate training as evidenced by a study in India is a major reason for poor care during the ‘Golden Hour’. Adapting developed country models which includes staffing specialty-trained doctors in emergency care, is neither feasible nor guarantees cost-effective ECS. Methods: Based on our assessment and felt needs by first-line doctors providing emergency care in 2014, Rajiv Gandhi Health Sciences University’s JeevaRaksha Trust in partnership with the University of Utah, USA, designed, piloted and successfully implemented a 4-day Comprehensive-Emergency Care and Life Support course (C-ECLS) for allopathic doctors. 1730 doctors completed the 4-day course between June 2014 and December- 2020. Subsequently, we conducted a survey to investigate the utilization rates and usefulness of the training. 1662 were contacted but only 309 completed the survey. The respondents had the following designations: Senior faculty (33%), junior faculty (25), Resident (16%), Private-Practitioners (8%), Medical-Officer (16%) and not-working (11%). 51% were generalists (51%) and the rest were specialists (>30 specialties). Results: 97% (271/280) felt they are better doctors because of C-ECLS. 79% (244/309) reported that training helped to save life- specialists more likely than generalists (91% v/s 68%. P<0.05). 64% agreed that they were confident of managing COVID-19 symptomatic patients better because of C-ECLS. 27% (77) were neutral; 9% (24) disagreed. 66% agreed that training helps to be confident in managing COVID-19 critically ill patients. 26% (72) were neutral; 8% (23) disagreed. Frequency of use of C-ECLS skills: Hemorrhage-control (70%), Airway (67%), circulation skills (62%), Safe-transport and communication (60%), managing critically ill patients (58%), cardiac arrest (51%), Trauma (49%), poisoning/animal bites/stings (44%), neonatal-resuscitation (39%), breathing (36%), post-partum-hemorrhage and eclampsia (35%). Among those who used the skills, the majority (ranging from (88%-94%) reported that they were able to apply the skill more effectively because of ECLS training. Conclusion: JeevaRaksha’s C-ECLS is the world’s first comprehensive training. It improves the confidence of front-line doctors and enables them to provide quality care during the ‘Golden Hour’ of emergency. It also prepares doctors to manage unknown emergencies (e.g., COVID-19). C-ECLS was piloted in Morocco, and Uzbekistan and implemented countrywide in Bhutan. C-ECLS is relevant to most settings and offers a replicable model across LMIC.

Keywords: comprehensive emergency care and life support, training, capacity building, low- and middle-income countries, developing countries

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Authors: Iorwase Derek Kaka’an, Peter Smolianov, Steven Dion, Christopher Schoen, Jaclyn Norberg, Charles Gabriel Iortimah

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This study examines the current state of football in Nigeria to identify the country's practices, which could be useful internationally, and to determine areas for improvement. Over 200 sources of literature on sport delivery systems in successful sports nations were analyzed to construct a globally applicable model of elite football integrated with mass participation, comprising of the following three levels: macro (socio-economic, cultural, legislative, and organizational), meso (infrastructures, personnel, and services enabling sports programs) and micro level (operations, processes, and methodologies for the development of individual athletes). The model has received scholarly validation and has shown to be a framework for program analysis that is not culturally bound. It has recently been utilized for further understanding such sports systems as US rugby, tennis, soccer, swimming, and volleyball, as well as Dutch and Russian swimming. A questionnaire was developed using the above-mentioned model. Survey questions were validated by 12 experts including academicians, executives from sports governing bodies, football coaches, and administrators. To identify best practices and determine areas for improvement of football in Nigeria, 116 coaches completed the questionnaire. Useful exemplars and possible improvements were further identified through semi-structured discussions with 10 Nigerian football administrators and experts. Finally, a content analysis of the Nigeria Football Federation's website and organizational documentation was conducted. This paper focuses on the micro level of Nigerian football delivery, particularly talent search and development as well as advanced athlete preparation and support. Results suggested that Nigeria could share such progressive practices as the provision of football programs in all schools and full-time coaches paid by governments based on the level of coach education. Nigerian football administrators and coaches could provide better football services affordable for all, where success in mass and elite sports is guided by science focused on athletes' needs. Better implemented could be international best practices such as lifelong guidelines for health and excellence of everyone and integration of fitness tests into player development and ranking as done in best Dutch, English, French, Russian, Spanish, and other European clubs; integration of educational and competitive events for elite and developing athletes as well as fans as done at the 2018 World Cup Russia; and academies with multi-stage athlete nurturing as done by Ajax in Africa as well as Barcelona FC and other top clubs expanding across the world. The methodical integration of these practices into the balanced development of mass and elite football will help contribute to international sports success as well as national health, education, crime control, and social harmony in Nigeria.

Keywords: football, high performance, mass participation, Nigeria, sport development

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Authors: Nadine Raidl, Benjamin Kaufmann, Michael Hofstätter, Peter Supancic

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If polycrystalline ZnO is properly doped and sintered under very specific conditions, it shows unique electrical properties, which are indispensable for today’s electronic industries, where it is used as the number one overvoltage protection material. Under a critical voltage, the polycrystalline bulk exhibits high electrical resistance but becomes suddenly up to twelve magnitudes more conductive if this voltage limit is exceeded (i.e., varistor effect). It is known that these peerless properties have their origin in the grain boundaries of the material. Electric charge is accumulated in the boundaries, causing a depletion layer in their vicinity and forming potential barriers (so-called Double Schottky Barriers, or DSB) which are responsible for the highly non-linear conductivity. Since ZnO is a piezoelectric material, mechanical stresses induce polarisation charges that modify the DSB heights and as a result the global electrical characteristics (i.e., piezotronic effect). In this work, a finite element method was used to simulate emerging stresses on individual grains in the bulk. Besides, experimental efforts were made to testify a coherent model that could explain this influence. Electron back scattering diffraction was used to identify grain orientations. With the help of wet chemical etching, grain polarization was determined. Micro lock-in infrared thermography (MLIRT) was applied to detect current paths through the material, and a micro 4-point probes method system (M4PPS) was employed to investigate current-voltage characteristics between single grains. Bulk samples were tested under uniaxial pressure. It was found that the conductivity can increase by up to three orders of magnitude with increasing stress. Through in-situ MLIRT, it could be shown that this effect is caused by the activation of additional current paths in the material. Further, compressive tests were performed on miniaturized samples with grain paths containing solely one or two grain boundaries. The tests evinced both an increase of the conductivity, as observed for the bulk, as well as a decreased conductivity. This phenomenon has been predicted theoretically and can be explained by piezotronically induced surface charges that have an impact on the DSB at the grain boundaries. Depending on grain orientation and stress direction, DSB can be raised or lowered. Also, the experiments revealed that the conductivity within one single specimen can increase and decrease, depending on the current direction. This novel finding indicates the existence of asymmetric Double Schottky Barriers, which was furthermore proved by complementary methods. MLIRT studies showed that the intensity of heat generation within individual current paths is dependent on the direction of the stimulating current. M4PPS was used to study the relationship between the I-V characteristics of single grain boundaries and grain orientation and revealed asymmetric behavior for very specific orientation configurations. A new model for the Double Schottky Barrier, taking into account the natural asymmetry and explaining the experimental results, will be given.

Keywords: Asymmetric Double Schottky Barrier, piezotronic, varistor, zinc oxide

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Authors: Tamam Albelwi, Robert Rogers, Hans-Peter Kubis

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Background: Exercise is widely acknowledged as a highly important health behavior, which reduces risks related to lifestyle diseases like type 2 diabetes, cardiovascular disease. However, exercise adherence is low in high-risk groups and sedentary lifestyle is more the norm than the exception. Expressed reasons for exercise participation are often based on delayed outcomes related to health threats and benefits but also enjoyment. Whether exercise is perceived as rewarding is well established in animal literature but the evidence is sparse in humans. Additionally, the question how stable any reward is perceived with time delays is an important question influencing decision-making (in favor or against a behavior). For the modality exercise, this has not been examined before. We, therefore, investigated the discounting of pre-established self-selected exercise compared with established rewards of food and money with a computer-based discounting paradigm. We hypothesized that exercise will be discounted like an established reward (food and money); however, we expect that the discounting rate is similar to a consumable reward like food. Additionally, we expected that individuals’ characteristics like preferred intensity, physical activity and body characteristics are associated with discount rates. Methods: 71 participants took part in four sessions. The sessions were designed to let participants select their preferred exercise intensity on a treadmill. Participants were asked to adjust their speed for optimizing pleasantness over an exercise period of up to 30 minutes, heart rate and pleasantness rating was measured. In further sessions, the established exercise intensity was modified and tested on perceptual validity. In the last exercise session rates of perceived exertion was measured on the preferred intensity level. Furthermore, participants filled in questionnaires related to physical activity, mood, craving, and impulsivity and answered choice questions on a bespoke computer task to establish discounting rates of their preferred exercise (kex), their favorite food (kfood) and a value-matching amount of money (kmoney). Results: Participants self-selected preferred speed was 5.5±2.24 km/h, at a heart rate of 120.7±23.5, and perceived exertion scale of 10.13±2.06. This shows that participants preferred a light exercise intensity with low to moderate cardiovascular strain based on perceived pleasantness. Computer assessment of discounting rates revealed that exercise was quickly discounted like a consumable reward, no significant difference between kfood and kex (kfood =0.322±0.263; kex=0.223±0.203). However, kmoney (kmoney=0.080±0.02) was significantly lower than the rates of exercise and food. Moreover, significant associations were found between preferred speed and kex (r=-0.302) and between physical activity levels and preferred speed (r=0.324). Outcomes show that participants perceived and discounted self-selected exercise like an established reward (food and money) but was discounted more like consumable rewards. Moreover, exercise discounting was quicker in individuals who preferred lower speeds, being less physically active. This may show that in a choice conflict between exercise and food the delay of exercise (because of distance) might disadvantage exercise as the chosen behavior particular in sedentary people. Conclusion: exercise can be perceived as a reward and is discounted quickly in time like food. Pleasant exercise experience is connected to low to moderate cardiovascular and perceptual strain.

Keywords: delay discounting, exercise, temporal discounting, time perspective

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Authors: Shewit Kidane, Abebe Getahun, Wassie Anteneh, Admassu Demeke, Peter Goethals

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We have reviewed major findings of scientific studies on Lake Tana fish resources and their threats. The aim was to provide summarized information for all concerned bodies and international readers to get full and comprehensive picture about the lake’s fish resource and conservation problems. The Lake Tana watershed comprise 28 fish species, of which 21 are endemic. Moreover, Lake Tana is the one among the top 250 lake regions of global importance for biodiversity and it is world recognized migratory birds wintering site. Lake Tana together with its adjacent wetlands provide directly and indirectly a livelihood for more than 500,000 people. However, owing to anthropogenic activities, the lake ecosystem as well as fish and attributes of the fisheries sector are severely degraded. Fish species in Lake Tana are suffering due to illegal fishing, damming, habitat/breeding ground degradation, wastewater disposal, introduction of exotic species, and lack of implementing fisheries regulations. Currently, more than 98% of fishers in Lake Tana are using the most destructive monofilament. Indeed, dams, irrigation schemes and hydropower are constructed in response to the emerging development need only. Mitigation techniques such as construction of fish ladders for the migratory fishes are the most forgotten. In addition, water resource developers are likely unaware of both the importance of the fisheries and the impact of dam construction on fish. As a result, the biodiversity issue is often missed. Besides, Lake Tana wetlands, which play vital role to sustain biodiversity, are not wisely utilised in the sense of the Ramsar Convention’s definition. Wetlands are considered as unhealthy and hence wetland conversion for the purpose of recession agriculture is still seen as advanced mode of development. As a result, many wetlands in the lake watershed are shrinking drastically over time and Cyprus papyrus, one of the characteristic features of Lake Tana, has dramatically declined in its distribution with some local extinction. Furthermore, the recently introduced water hyacinth (Eichhornia crassipes) is creating immense problems on the lake ecosystem. Moreover, currently, 1.56 million tons of sediment have deposited into the lake each year and wastes from the industries and residents are directly discharged into the lake without treatment. Recently, sign of eutrophication is revealed in Lake Tana and most coarsely, the incidence of cyanobacteria genus Microcystis was reported from the Bahir Dar Gulf of Lake Tana. Thus, the direct dependency of the communities on the lake water for drinking as well as to wash their body and clothes and its fisheries make the problem worst. Indeed, since it is home to many endemic migratory fish, such kind of unregulated developmental activities could be detrimental to their stocks. This can be best illustrated by the drastic stock reduction (>75% in biomass) of the world unique Labeobarbus species. So, unless proper management is put in place, the anthropogenic impacts can jeopardize the aquatic ecosystems. Therefore, in order to sustainably use the aquatic resources and fulfil the needs of the local people, every developmental activity and resource utilization should be carried out adhering to the available policies.

Keywords: anthropogenic impacts, dams, endemic fish, wetland degradation

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Authors: Benjamin Kaufmann, Michael Hofstätter, Nadine Raidl, Peter Supancic

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ZnO varistors are the leading overvoltage protection elements in today’s electronic industry. Their highly non-linear current-voltage characteristics, very fast response times, good reliability and attractive cost of production are unique in this field. There are challenges and questions unsolved. Especially, the urge to create even smaller, versatile and reliable parts, that fit industry’s demands, brings manufacturers to the limits of their abilities. Although, the varistor effect of sintered ZnO is known since the 1960’s, and a lot of work was done on this field to explain the sudden exponential increase of conductivity, the strict dependency on sinter parameters, as well as the influence of the complex microstructure, is not sufficiently understood. For further enhancement and down-scaling of varistors, a better understanding of the microscopic processes is needed. This work attempts a microscopic approach to investigate ZnO varistor performance. In order to cope with the polycrystalline varistor ceramic and in order to account for all possible current paths through the material, a preferably realistic model of the microstructure was set up in the form of three-dimensional networks where every grain has a constant electric potential, and voltage drop occurs only at the grain boundaries. The electro-thermal workload, depending on different grain size distributions, was investigated as well as the influence of the metal-semiconductor contact between the electrodes and the ZnO grains. A number of experimental methods are used, firstly, to feed the simulations with realistic parameters and, secondly, to verify the obtained results. These methods are: a micro 4-point probes method system (M4PPS) to investigate the current-voltage characteristics between single ZnO grains and between ZnO grains and the metal electrode inside the varistor, micro lock-in infrared thermography (MLIRT) to detect current paths, electron back scattering diffraction and piezoresponse force microscopy to determine grain orientations, atom probe to determine atomic substituents, Kelvin probe force microscopy for investigating grain surface potentials. The simulations showed that, within a critical voltage range, the current flow is localized along paths which represent only a tiny part of the available volume. This effect could be observed via MLIRT. Furthermore, the simulations exhibit that the electric power density, which is inversely proportional to the number of active current paths, since this number determines the electrical active volume, is dependent on the grain size distribution. M4PPS measurements showed that the electrode-grain contacts behave like Schottky diodes and are crucial for asymmetric current path development. Furthermore, evaluation of actual data suggests that current flow is influenced by grain orientations. The present results deepen the knowledge of influencing microscopic factors on ZnO varistor performance and can give some recommendations on fabrication for obtaining more reliable ZnO varistors.

Keywords: metal-semiconductor contact, Schottky diode, varistor, zinc oxide

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Authors: Taboka Motlhabane, Pradeep Sahoo

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The global demand for cooling has grown exponentially over the past century to meet economic development and social needs, accounting for approximately 10% of the global electricity consumption. As global temperatures continue to rise, the demand for cooling and heating, ventilation and air-conditioning (HVAC) equipment is set to rise with it. The increased use of HVAC equipment has significantly contributed to the growth of greenhouse gas (GHG) emissions which aid the climate crisis- one of the biggest challenges faced by the current generation. The need to address emissions caused directly by HVAC equipment and electricity generated to meet the cooling or heating demand is ever more pressing. Currently, developed countries account for the largest cooling and heating demand, however developing countries are anticipated to experience a huge increase in population growth in 10 years, resulting in a shift in energy demand. Developing countries, which are projected to account for nearly 60% of the world's GDP by 2030, are rapidly building infrastructure and economies to meet their growing needs and meet these projections. Cooling, a very energy-intensive process that can account for 20 % to 75% of a building's energy, depending on the building's use. Solar photovoltaic (PV) driven air-conditioning offers a great cost-effective alternative for adoption in both residential and non-residential buildings to offset grid electricity, particularly in countries with high irradiation, such as Botswana. This research paper explores the potential of a grid-connected solar photovoltaic vapor-compression air-conditioning system for the Peter-Smith herbarium at the Okavango Research Institute (ORI) University of Botswana campus in Maun, Botswana. The herbarium plays a critical role in the collection and preservation of botanical data, dating back over 100 years, with pristine collection from the Okavango Delta, a UNESCO world heritage site and serves as a reference and research site. Due to the herbarium’s specific needs, it operates throughout the day and year in an attempt to maintain a constant herbarium temperature of 16°?. The herbarium model studied simulates a variable-air-volume HVAC system with a system rating of 30 kW. Simulation results show that the HVAC system accounts for 68.9% of the building's total electricity at 296 509.60 kWh annually. To offset the grid electricity, a 175.1 kWp nominal power rated PV system requiring 416 modules to match the required power, covering an area of 928 m2 is used to meet the HVAC system annual needs. An economic assessment using PVsyst found that for an installation priced with average solar PV prices in Botswana totalled to be 787 090.00 BWP, with annual operating costs of 30 500 BWP/year. With self-project financing, the project is estimated to have recouped its initial investment within 6.7 years. At an estimated project lifetime of 20 years, the Net Present Value is projected at 1 565 687.00 BWP with a ROI of 198.9%, with 74 070.67 tons of CO2 saved at the end of the project lifetime. This study investigates the performance of the HVAC system to meet the indoor air comfort requirements, the annual PV system performance, and the building model has been simulated using DesignBuilder Software.

Keywords: vapor compression refrigeration, solar cooling, renewable energy, herbarium

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Authors: Caspar Goeke, Holger Finger, Dorena Diekamp, Peter König

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Online-based research has recently gained increasing attention from various fields of research in the cognitive sciences. Technological advances in the form of online crowdsourcing (Amazon Mechanical Turk), open data repositories (Open Science Framework), and online analysis (Ipython notebook) offer rich possibilities to improve, validate, and speed up research. However, until today there is no cross-platform integration of these subsystems. Furthermore, implementation of online studies still suffers from the complex implementation (server infrastructure, database programming, security considerations etc.). Here we propose and test a new JavaScript framework that enables researchers to conduct any kind of behavioral research in the browser without the need to program a single line of code. In particular our framework offers the possibility to manipulate and combine the experimental stimuli via a graphical editor, directly in the browser. Moreover, we included an action-event system that can be used to handle user interactions, interactively change stimuli properties or store participants’ responses. Besides traditional recordings such as reaction time, mouse and keyboard presses, the tool offers webcam based eye and face-tracking. On top of these features our framework also takes care about the participant recruitment, via crowdsourcing platforms such as Amazon Mechanical Turk. Furthermore, the build in functionality of google translate will ensure automatic text translations of the experimental content. Thereby, thousands of participants from different cultures and nationalities can be recruited literally within hours. Finally, the recorded data can be visualized and cleaned online, and then exported into the desired formats (csv, xls, sav, mat) for statistical analysis. Alternatively, the data can also be analyzed online within our framework using the integrated Ipython notebook. The framework was designed such that studies can be used interchangeably between researchers. This will support not only the idea of open data repositories but also constitutes the possibility to share and reuse the experimental designs and analyses such that the validity of the paradigms will be improved. Particularly, sharing and integrating the experimental designs and analysis will lead to an increased consistency of experimental paradigms. To demonstrate the functionality of the framework we present the results of a pilot study in the field of spatial navigation that was conducted using the framework. Specifically, we recruited over 2000 subjects with various cultural backgrounds and consequently analyzed performance difference in dependence on the factors culture, gender and age. Overall, our results demonstrate a strong influence of cultural factors in spatial cognition. Such an influence has not yet been reported before and would not have been possible to show without the massive amount of data collected via our framework. In fact, these findings shed new lights on cultural differences in spatial navigation. As a consequence we conclude that our new framework constitutes a wide range of advantages for online research and a methodological innovation, by which new insights can be revealed on the basis of massive data collection.

Keywords: cultural differences, crowdsourcing, JavaScript framework, methodological innovation, online data collection, online study, spatial cognition

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Authors: Jawaad Saleem, Hannah Wright, Peter Sommerville, Adrian Hopper

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Introduction: Inpatient falls are the most commonly reported patient safety incidents, and carry a significant burden on resources, morbidity, and mortality. Ensuring adequate post falls management of patients by staff is therefore paramount to maintaining patient safety especially in out of hours and resource stretched settings. Aims: This quality improvement project aims to improve the current practice of falls management at Guys St Thomas Hospital, London as compared to our 2016 Quality Improvement Project findings. Furthermore, it looks to increase current junior doctors confidence in managing falls and their use of new guidance protocols. Methods: Multifaceted Interventions implemented included: the development of new trust wide guidelines detailing management pathways for patients post falls, available for intranet access. Furthermore, the production of 2000 lanyard cards distributed amongst junior doctors and staff which summarised these guidelines. Additionally, a ‘safety signal’ email was sent from the Trust chief medical officer to all staff raising awareness of falls and the guidelines. Formal falls teaching was also implemented for new doctors at induction. Using an established incident database, 189 consecutive falls in 2017were retrospectively analysed electronically to assess and compared to the variables measured in 2016 post interventions. A separate serious incident database was used to analyse 50 falls from May 2015 to March 2018 to ascertain the statistical significance of the impact of our interventions on serious incidents. A similar questionnaire for the 2017 cohort of foundation year one (FY1) doctors was performed and compared to 2016 results. Results: Questionnaire data demonstrated improved awareness and utility of guidelines and increased confidence as well as an increase in training. 97% of FY1 trainees felt that the interventions had increased their awareness of the impact of falls on patients in the trust. Data from the incident database demonstrated the time to review patients post fall had decreased from an average of 130 to 86 minutes. Improvement was also demonstrated in the reduced time to order and schedule X-ray and CT imaging, 3 and 5 hours respectively. Data from the serious incident database show that ‘the time from fall until harm was detected’ was statistically significantly lower (P = 0.044) post intervention. We also showed the incidence of significant delays in detecting harm ( > 10 hours) reduced post intervention. Conclusions: Our interventions have helped to significantly reduce the average time to assess, order and schedule appropriate imaging post falls. Delays of over ten hours to detect serious injuries after falls were commonplace; since the intervention, their frequency has markedly reduced. We suggest this will lead to identifying patient harm sooner, reduced clinical incidents relating to falls and thus improve overall patient safety. Our interventions have also helped increase clinical staff confidence, management, and awareness of falls in the trust. Next steps include expanding teaching sessions, improving multidisciplinary team involvement to aid this improvement.

Keywords: patient safety, quality improvement, serious incidents, falls, clinical care

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Authors: Juan A. Arzate, Funda C. Ertem, M. Nicolas Cruz-Bournazou, Peter Neubauer, Stefan Junne

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— One of the biggest challenges the world faces today is global warming that is caused by greenhouse gases (GHGs) coming from the combustion of fossil fuels for energy generation. In order to mitigate climate change, the European Union has committed to reducing GHG emissions to 80–95% below the level of the 1990s by the year 2050. Renewable technologies are vital to diminish energy-related GHG emissions. Since water and biomass are limited resources, the largest contributions to renewable energy (RE) systems will have to come from wind and solar power. Nevertheless, high proportions of fluctuating RE will present a number of challenges, especially regarding the need to balance the variable energy demand with the weather dependent fluctuation of energy supply. Therefore, biogas plants in this content would play an important role, since they are easily adaptable. Feedstock availability varies locally or seasonally; however there is a lack of knowledge in how biogas plants should be operated in a stable manner by local feedstock. This problem may be prevented through suitable control strategies. Such strategies require the development of convenient mathematical models, which fairly describe the main processes. Modelling allows us to predict the system behavior of biogas plants when different feedstocks are used with different loading rates. Life cycle assessment (LCA) is a technique for analyzing several sides from evolution of a product till its disposal in an environmental point of view. It is highly recommend to use as a decision making tool. In order to achieve suitable strategies, the combination of a flexible energy generation provided by biogas plants, a secure production process and the maximization of the environmental benefits can be obtained by the combination of process modelling and LCA approaches. For this reason, this study focuses on the biogas plant which flexibly generates required energy from the co-digestion of maize, grass and cattle manure, while emitting the lowest amount of GHG´s. To achieve this goal AMOCO model was combined with LCA. The program was structured in Matlab to simulate any biogas process based on the AMOCO model and combined with the equations necessary to obtain climate change, acidification and eutrophication potentials of the whole production system based on ReCiPe midpoint v.1.06 methodology. Developed simulation was optimized based on real data from operating biogas plants and existing literature research. The results prove that AMOCO model can successfully imitate the system behavior of biogas plants and the necessary time required for the process to adapt in order to generate demanded energy from available feedstock. Combination with LCA approach provided opportunity to keep the resulting emissions from operation at the lowest possible level. This would allow for a prediction of the process, when the feedstock utilization supports the establishment of closed material circles within a smart bio-production grid – under the constraint of minimal drawbacks for the environment and maximal sustainability.

Keywords: AMOCO model, GHG emissions, life cycle assessment, modelling

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Authors: Joanne DiFrancisco-Donoghue, Seth E. Jenny, Peter C. Douris, Sophia Ahmad, Kyle Yuen, Hillary Gan, Kenney Abraham, Amber Sousa

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Background: Guidelines for the maintenance of health of esports players and the cognitive changes that accompany competitive gaming are understudied. Executive functioning is an important cognitive skill for an esports player. The relationship between executive functions and physical exercise has been well established. However, the effects of prolonged sitting regardless of physical activity level have not been established. Prolonged uninterrupted sitting reduces cerebral blood flow. Reduced cerebral blood flow is associated with lower cognitive function and fatigue. This decrease in cerebral blood flow has been shown to be offset by frequent and short walking breaks. These short breaks can be as little as 2 minutes at the 30-minute mark and 6 minutes following 60 minutes of prolonged sitting. The rationale is the increase in blood flow and the positive effects this has on metabolic responses. The primary purpose of this study was to evaluate executive function changes following 6-minute bouts of walking and complete rest mid-session, compared to no break, during prolonged gameplay in competitive first-person shooter (FPS) esports players. Methods: This study was conducted virtually due to the Covid-19 pandemic and was approved by the New York Institute of Technology IRB. Twelve competitive FPS participants signed written consent to participate in this randomized pilot study. All participants held a gold ranking or higher. Participants were asked to play for 2 hours on three separate days. Outcome measures to test executive function included the Color Stroop and the Tower of London tests which were administered online each day prior to gaming and at the completion of gaming. All participants completed the tests prior to testing for familiarization. One day of testing consisted of a 6-minute walk break after 60-75 minutes of play. The Rate of Perceived Exertion (RPE) was recorded. The participant continued to play for another 60-75 minutes and completed the tests again. Another day the participants repeated the same methods replacing the 6-minute walk with lying down and resting for 6 minutes. On the last day, the participant played continuously with no break for 2 hours and repeated the outcome tests pre and post-play. A Latin square was used to randomize the treatment order. Results: Using descriptive statistics, the largest change in mean reaction time incorrect congruent pre to post play was seen following the 6-minute walk (662.0 (609.6) ms pre to 602.8 (539.2) ms post), followed by the 6-minute rest group (681.7(618.1) ms pre to 666.3 (607.9) ms post), and with minimal change in the continuous group (594.0(534.1) ms pre to 589.6(552.9) ms post). The mean solution time was fastest in the resting condition (7774.6(6302.8)ms), followed by the walk condition (7929.4 (5992.8)ms), with the continuous condition being slowest (9337.3(7228.7)ms). the continuous group 9337.3(7228.7) ms; 7929.4 (5992.8 ) ms 774.6(6302.8) ms. Conclusion: Short walking breaks improve blood flow and reduce the risk of venous thromboembolism during prolonged sitting. This pilot study demonstrated that a low intensity 6 -minute walk break, following 60 minutes of play, may also improve executive function in FPS gamers.

Keywords: executive function, FPS, physical activity, prolonged sitting

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Authors: Melissa de Zeeuw, Peter Smolianov, Arnold Bohl

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This study was designed to help and improve international performance as well increase swimming participation in the Netherlands. Over 200 sources of literature on sport delivery systems from 28 Australasian, North and South American, Western and Eastern European countries were analyzed to construct a globally applicable model of high performance swimming integrated with mass participation, comprising of the following seven elements and three levels: Micro level (operations, processes, and methodologies for development of individual athletes): 1. Talent search and development, 2. Advanced athlete support. Meso level (infrastructures, personnel, and services enabling sport programs): 3. Training centers, 4. Competition systems, 5. Intellectual services. Macro level (socio-economic, cultural, legislative, and organizational): 6. Partnerships with supporting agencies, 7. Balanced and integrated funding and structures of mass and elite sport. This model emerged from the integration of instruments that have been used to analyse and compare national sport systems. The model has received scholarly validation and showed to be a framework for program analysis that is not culturally bound. It has recently been accepted as a model for further understanding North American sport systems, including (in chronological order of publications) US rugby, tennis, soccer, swimming and volleyball. The above model was used to design a questionnaire of 42 statements reflecting desired practices. The statements were validated by 12 international experts, including executives from sport governing bodies, academics who published on high performance and sport development, and swimming coaches and administrators. In this study both a highly structured and open ended qualitative analysis tools were used. This included a survey of swim coaches where open responses accompanied structured questions. After collection of the surveys, semi-structured discussions with Federation coaches were conducted to add triangulation to the findings. Lastly, a content analysis of Dutch Swimming’s website and organizational documentation was conducted. A representative sample of 1,600 Dutch Swim coaches and administrators was collected via email addresses from Royal Dutch Swimming Federation' database. Fully completed questionnaires were returned by 122 coaches from all key country’s regions for a response rate of 7,63% - higher than the response rate of the previously mentioned US studies which used the same model and method. Results suggest possible enhancements at macro level (e.g., greater public and corporate support to prepare and hire more coaches and to address the lack of facilities, monies and publicity at mass participation level in order to make swimming affordable for all), at meso level (e.g., comprehensive education for all coaches and full spectrum of swimming pools particularly 50 meters long), and at micro level (e.g., better preparation of athletes for a future outside swimming and better use of swimmers to stimulate swimming development). Best Dutch swimming management practices (e.g., comprehensive support to most talented swimmers who win Olympic medals) as well as relevant international practices available for transfer to the Netherlands (e.g., high school competitions) are discussed.

Keywords: sport development, high performance, mass participation, swimming

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Authors: Lam Pham, Peter Hubber, Russell Tytler

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Students’ conceptual understandings of chemistry concepts/phenomena involve capability to coordinate across the three levels of Johnston’s triangle model. This triplet model is based on reasoning about chemical phenomena across macro, sub-micro and symbolic levels. In chemistry education, there is a need for further examining inquiry-based approaches that enhance students’ conceptual learning and problem solving skills. This research adopted a directed inquiry pedagogy based on students constructing and coordinating representations, to investigate senior school students’ capabilities to flexibly move across Johnston’ levels when learning dilution and molar concentration concepts. The participants comprise 50 grade 11 and 20 grade 10 students and 4 chemistry teachers who were selected from 4 secondary schools located in metropolitan Melbourne, Victoria. This research into classroom practices used ethnographic methodology, involved teachers working collaboratively with the research team to develop representational activities and lesson sequences in the instruction of a unit on solution chemistry. The representational activities included challenges (Representational Challenges-RCs) that used ‘representational tools’ to assist students to move across Johnson’s three levels for dilution phenomena. In this report, the ‘representational tool’ called ‘cross and portion’ model was developed and used in teaching and learning the molar concentration concept. Students’ conceptual understanding and problem solving skills when learning with this model are analysed through group case studies of year 10 and 11 chemistry students. In learning dilution concepts, students in both group case studies actively conducted a practical experiment, used their own language and visualisation skills to represent dilution phenomena at macroscopic level (RC1). At the sub-microscopic level, students generated and negotiated representations of the chemical interactions between solute and solvent underpinning the dilution process. At the symbolic level, students demonstrated their understandings about dilution concepts by drawing chemical structures and performing mathematical calculations. When learning molar concentration with a ‘cross and portion’ model (RC2), students coordinated across visual and symbolic representational forms and Johnson’s levels to construct representations. The analysis showed that in RC1, Year 10 students needed more ‘scaffolding’ in inducing to representations to explicit the form and function of sub-microscopic representations. In RC2, Year 11 students showed clarity in using visual representations (drawings) to link to mathematics to solve representational challenges about molar concentration. In contrast, year 10 students struggled to get match up the two systems, symbolic system of mole per litre (‘cross and portion’) and visual representation (drawing). These conceptual problems do not lie in the students’ mathematical calculation capability but rather in students’ capability to align visual representations with the symbolic mathematical formulations. This research also found that students in both group case studies were able to coordinate representations when probed about the use of ‘cross and portion’ model (in RC2) to demonstrate molar concentration of diluted solutions (in RC1). Students mostly succeeded in constructing ‘cross and portion’ models to represent the reduction of molar concentration of the concentration gradients. In conclusion, this research demonstrated how the strategic introduction and coordination of chemical representations across modes and across the macro, sub-micro and symbolic levels, supported student reasoning and problem solving in chemistry.

Keywords: cross and portion, dilution, Johnston's triangle, molar concentration, representations

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Authors: David A. Olasehinde, Peter I. Olasehinde, Segun M. A. Adelana, Dapo O. Olasehinde

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An investigation was carried out on underground water system dynamics within Ilorin metropolis to monitor the subsurface flow and its corresponding pollution. Africa population growth rate is the highest among the regions of the world, especially in urban areas. A corresponding increase in waste generation and a change in waste composition from predominantly organic to non-organic waste has also been observed. Percolation of leachate from non-engineered landfills, the chief means of waste disposal in many of its cities, constitutes a threat to the underground water bodies. Ilorin city, a transboundary town in southwestern Nigeria, is a ready microcosm of Africa’s unique challenge. In spite of the fact that groundwater is naturally protected from common contaminants such as bacteria as the subsurface provides natural attenuation process, groundwater samples have been noted to however possesses relatively higher dissolved chemical contaminants such as bicarbonate, sodium, and chloride which poses a great threat to environmental receptors and human consumption. The Geographic Information System (GIS) was used as a tool to illustrate, subsurface dynamics and the corresponding pollutant indicators. Forty-four sampling points were selected around known groundwater pollutant, major old dumpsites without landfill liners. The results of the groundwater flow directions and the corresponding contaminant transport were presented using expert geospatial software. The experimental results were subjected to four descriptive statistical analyses, namely: principal component analysis, Pearson correlation analysis, scree plot analysis, and Ward cluster analysis. Regression model was also developed aimed at finding functional relationships that can adequately relate or describe the behaviour of water qualities and the hypothetical factors landfill characteristics that may influence them namely; distance of source of water body from dumpsites, static water level of groundwater, subsurface permeability (inferred from hydraulic gradient), and soil infiltration. The regression equations developed were validated using the graphical approach. Underground water seems to flow from the northern portion of Ilorin metropolis down southwards transporting contaminants. Pollution pattern in the study area generally assumed a bimodal pattern with the major concentration of the chemical pollutants in the underground watershed and the recharge. The correlation between contaminant concentrations and the spread of pollution indicates that areas of lower subsurface permeability display a higher concentration of dissolved chemical content. The principal component analysis showed that conductivity, suspended solids, calcium hardness, total dissolved solids, total coliforms, and coliforms were the chief contaminant indicators in the underground water system in the study area. Pearson correlation revealed a high correlation of electrical conductivity for many parameters analyzed. In the same vein, the regression models suggest that the heavier the molecular weight of a chemical contaminant of a pollutant from a point source, the greater the pollution of the underground water system at a short distance. The study concludes that the associative properties of landfill have a significant effect on groundwater quality in the study area.

Keywords: dumpsite, leachate, groundwater pollution, linear regression, principal component

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Authors: Enwin Anthony Dornubari, Visigah Kpobari Peter

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This research has developed a framework for the provision of sustainable and affordable housing to accommodate the low-income population of Greater Port Harcourt City. The objectives of this study among others, were to: examine UN-Habitat guidelines for acceptable and sustainable social housing provision, describe past efforts of the Rivers State Government and the Federal Government of Nigeria to provide housing for the poor in the Greater Port Harcourt City area; obtain a profile of prospective beneficiaries of the social housing proposed by this research as well as perceptions of their present living conditions, and living in the proposed self-sustaining social housing development, based on the initial simulation of the proposal; describe the nature of the framework, guideline and management of the proposed social housing development and explain the modalities for its implementation. The study utilized the mixed methods research approach, aimed at triangulating findings from the quantitative and qualitative paradigms. Opinions of professional of the built environment; Director, Development Control, Greater Port Harcourt City Development Authority; Directors of Ministry of Urban Development and Physical Planning; Housing and Property Development Authority and managers of selected Primary Mortgage Institutions were sought and analyzed. There were four target populations for the study, namely: members of occupational sub-groups for FGDs (Focused Group Discussions); development professionals for KIIs (Key Informant Interviews), household heads in selected communities of GPHC; and relevant public officials for IDI (Individual Depth Interview). Focus Group Discussions (FGDs) were held with members of occupational sub-groups in each of the eight selected communities (Fisherfolk). The table shows that there were forty (40) members across all occupational sub-groups in each selected community, yielding a total of 320 in the eight (8) communities of Mgbundukwu (Mile 2 Diobu), Rumuodomaya, Abara (Etche), Igwuruta-Ali(Ikwerre), Wakama(Ogu-Bolo), Okujagu (Okrika), Akpajo (Eleme), and Okoloma (Oyigbo). For key informant interviews, two (2) members were judgmentally selected from each of the following development professions: urban and regional planners; architects; estate surveyors; land surveyors; quantity surveyors; and engineers. Concerning Population 3-Household Heads in Selected Communities of GPHC, a stratified multi-stage sampling procedure was adopted: Stage 1-Obtaining a 10% (a priori decision) sample of the component communities of GPHC in each stratum. The number in each stratum was rounded to one whole number to ensure representation of each stratum. Stage 2-Obtaining the number of households to be studied after applying the Taro Yamane formula, which aided in determining the appropriate number of cases to be studied at the precision level of 5%. Findings revealed, amongst others, that poor implementation of the UN-Habitat global shelter strategy, lack of stakeholder engagement, inappropriate locations, undue bureaucracy, lack of housing fairness and equity and high cost of land and building materials were the reasons for the failure of past efforts towards social housing provision in the Greater Port Harcourt City area. The study recommended a public-private partnership approach for the implementation and management of the framework. It also recommended a robust and sustained relationship between the management of the framework and the UN-Habitat office and other relevant government agencies responsible for housing development and all investment partners to create trust and efficiency.

Keywords: development, framework, low-income, sustainable, social housing

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Authors: Faruk Ozdemir, Roy Kalawsky, Peter Hubbard

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Accurate estimation of RUL provides a basis for effective predictive maintenance, reducing unexpected downtime for industrial equipment. However, while models such as the Random Forest have effective predictive capabilities, they are the so-called ‘black box’ models, where interpretability is at a threshold to make critical diagnostic decisions involved in industries related to aviation. The purpose of this work is to present a prognostic framework that embeds Explainable Artificial Intelligence (XAI) techniques in order to provide essential transparency in Machine Learning methods' decision-making mechanisms based on sensor data, with the objective of procuring actionable insights for the aviation industry. Sensor readings have been gathered from critical equipment such as turbofan jet engine and landing gear, and the prediction of the RUL is done by a Random Forest model. It involves steps such as data gathering, feature engineering, model training, and evaluation. These critical components’ datasets are independently trained and evaluated by the models. While suitable predictions are served, their performance metrics are reasonably good; such complex models, however obscure reasoning for the predictions made by them and may even undermine the confidence of the decision-maker or the maintenance teams. This is followed by global explanations using SHAP and local explanations using LIME in the second phase to bridge the gap in reliability within industrial contexts. These tools analyze model decisions, highlighting feature importance and explaining how each input variable affects the output. This dual approach offers a general comprehension of the overall model behavior and detailed insight into specific predictions. The proposed framework, in its third component, incorporates the techniques of causal analysis in the form of Granger causality tests in order to move beyond correlation toward causation. This will not only allow the model to predict failures but also present reasons, from the key sensor features linked to possible failure mechanisms to relevant personnel. The causality between sensor behaviors and equipment failures creates much value for maintenance teams due to better root cause identification and effective preventive measures. This step contributes to the system being more explainable. Surrogate Several simple models, including Decision Trees and Linear Models, can be used in yet another stage to approximately represent the complex Random Forest model. These simpler models act as backups, replicating important jobs of the original model's behavior. If the feature explanations obtained from the surrogate model are cross-validated with the primary model, the insights derived would be more reliable and provide an intuitive sense of how the input variables affect the predictions. We then create an iterative explainable feedback loop, where the knowledge learned from the explainability methods feeds back into the training of the models. This feeds into a cycle of continuous improvement both in model accuracy and interpretability over time. By systematically integrating new findings, the model is expected to adapt to changed conditions and further develop its prognosis capability. These components are then presented to the decision-makers through the development of a fully transparent condition monitoring and alert system. The system provides a holistic tool for maintenance operations by leveraging RUL predictions, feature importance scores, persistent sensor threshold values, and autonomous alert mechanisms. Since the system will provide explanations for the predictions given, along with active alerts, the maintenance personnel can make informed decisions on their end regarding correct interventions to extend the life of the critical machinery.

Keywords: predictive maintenance, explainable artificial intelligence, prognostic, RUL, machine learning, turbofan engines, C-MAPSS dataset

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