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Articles 121 - 150 of 2927
Full-Text Articles in Entire DC Network
A Comparative Study On Feature Extraction Techniques For The Discrimination Of Frontotemporal Dementia And Alzheimer's Disease With Electroencephalography In Resting-State Adults, Utkarsh Lal, Arjun Vinayak Chikkankod, Luca Longo
A Comparative Study On Feature Extraction Techniques For The Discrimination Of Frontotemporal Dementia And Alzheimer's Disease With Electroencephalography In Resting-State Adults, Utkarsh Lal, Arjun Vinayak Chikkankod, Luca Longo
Articles
Early-stage Alzheimer's disease (AD) and frontotemporal dementia (FTD) share similar symptoms, complicating their diagnosis and the development of specific treatment strategies. Our study evaluated multiple feature extraction techniques for identifying AD and FTD biomarkers from electroencephalographic (EEG) signals. We developed an optimised machine learning architecture that integrates sliding windowing, feature extraction, and supervised learning to distinguish between AD and FTD patients, as well as from healthy controls (HCs). Our model, with a 90% overlap for sliding windowing, SVD entropy for feature extraction, and K-Nearest Neighbors (KNN) for supervised learning, achieved a mean F1-score and accuracy of 93% and 91%, 92.5% …
Analyzing Operator States And The Impact Of Ai-Enhanced Decision Support In Control Rooms: A Human-In-The-Loop Specialized Reinforcement Learning Framework For Intervention Strategies, Ammar N. Abbas, Chidera W. Amazu, Joseph Mietkiewicz, Houda Briwa, Andres Alonso Perez, Gabriele Baldissone, Micaela Demichela, Georgios C. Chasparis, John D. Kelleher, Maria Chiara Leva
Analyzing Operator States And The Impact Of Ai-Enhanced Decision Support In Control Rooms: A Human-In-The-Loop Specialized Reinforcement Learning Framework For Intervention Strategies, Ammar N. Abbas, Chidera W. Amazu, Joseph Mietkiewicz, Houda Briwa, Andres Alonso Perez, Gabriele Baldissone, Micaela Demichela, Georgios C. Chasparis, John D. Kelleher, Maria Chiara Leva
Articles
In complex industrial and chemical process control rooms, effective decision-making is crucial for safety and efficiency. The experiments in this paper evaluate the impact and applications of an AI-based decision support system integrated into an improved human-machine interface, using dynamic influence diagrams, a hidden Markov model, and deep reinforcement learning. The enhanced support system aims to reduce operator workload, improve situational awareness, and provide different intervention strategies to the operator adapted to the current state of both the system and human performance. Such a system can be particularly useful in cases of information overload when many alarms and inputs are …
Valuing Social Data, Amanda Parsons, Salome Viljoen
Valuing Social Data, Amanda Parsons, Salome Viljoen
Articles
Social data production—accumulating, processing, and using large volumes of data about people—is a unique form of value creation that characterizes the digital economy. Social data production also presents critical challenges for the legal regimes that encounter it. This Article provides scholars and policymakers with the tools to comprehend this new form of value creation through two descriptive contributions. First, it presents a theoretical account of social data, a mode of production that is cultivated and exploited for two distinct (albeit related) forms of value: prediction value and exchange value. Second, it creates and defends a taxonomy of three “scripts” that …
Use Of Artificial Intelligence In Drug Development, Louise C. Druedahl, Nicholson Price, Timo Minssen, Dipl Jur, Ameet Sarpatwari
Use Of Artificial Intelligence In Drug Development, Louise C. Druedahl, Nicholson Price, Timo Minssen, Dipl Jur, Ameet Sarpatwari
Articles
Considerable focus has been placed on the health care applications of artificial intelligence (AI). Already, machine learning, a subset of AI that involves “the use of data and algorithms to imitate the way that humans learn” has been used to predict diseases, while AI-powered smartphone apps have been developed to promote mental health and weight loss. Owing in part to such successes, the market for AI in health care has been forecasted to increase more than 1000% between 2022 and 2029, from $13.8 billion to $164.1 billion. One area of substantial promise is drug development, which is poised to benefit …
Enhancing Control Room Operator Decision Making, Joseph Mietkiewicz, Ammar N. Abbas, Chidera W. Amazu, Gabriele Baldissone, Anders L. Madsen, Micaela Demichela, Maria Chiara Leva
Enhancing Control Room Operator Decision Making, Joseph Mietkiewicz, Ammar N. Abbas, Chidera W. Amazu, Gabriele Baldissone, Anders L. Madsen, Micaela Demichela, Maria Chiara Leva
Articles
In the dynamic and complex environment of industrial control rooms, operators are often inundated with numerous tasks and alerts, leading to a state known as task overload. This condition can result in decision fatigue and increased reliance on cognitive biases, which may compromise the decision-making process. To mitigate these risks, the implementation of decision support systems (DSSs) is essential. These systems are designed to aid operators in making swift, well-informed decisions, especially when their judgment may be faltering. Our research presents an artificial intelligence (AI)-based framework utilizing dynamic influence diagrams and reinforcement learning to develop a powerful decision support system. …
Exploring The Influence Of Human System Interfaces: Introducing Support Tools And An Experimental Study, Chidera W. Amazu, Joseph Mietkiewicz, Ammar N. Abbas, Houda Briwa, Andres Alonso-Perez, Gabriele Baldissone, Davide Fissore, Micaela Demichela, Maria Chiara Leva
Exploring The Influence Of Human System Interfaces: Introducing Support Tools And An Experimental Study, Chidera W. Amazu, Joseph Mietkiewicz, Ammar N. Abbas, Houda Briwa, Andres Alonso-Perez, Gabriele Baldissone, Davide Fissore, Micaela Demichela, Maria Chiara Leva
Articles
Situational awareness and decision support tools such as procedures and alarm systems are vital for effective interaction among control room operators, especially in safety-critical situations. In safety-critical environments such as process plants, there remains a gap in evaluating specific tools during actual operations, or ”work-as-done.” Additionally, the underlying factors that might impact operators' cognitive states and performance concerning safety have not been thoroughly explored. The need for such an evaluation is further bolstered by current interaction configurations where operators are more passive than active, thus reducing their cognitive performance. Therefore, this experimental study addresses the highlighted evaluation gap by introducing …
Feedback Loops: Feedback Machines, Patrick Barry
Feedback Loops: Feedback Machines, Patrick Barry
Articles
Yes, AI raises serious concerns about bias, privacy, copyright infringement, environmental sustainability, and a whole bunch of other important topics. But if you are looking for a positive use case - and a new way to approach professional development - try asking chatgpt or some other AI chatbot for feedback, especially on something you've written.
Sins And Omissions: Slavery And The Bill Of Rights, Richard Primus
Sins And Omissions: Slavery And The Bill Of Rights, Richard Primus
Articles
According to the conventional story, the Constitutional Convention declined to include a bill of rights in the Constitution because it trusted the enumeration of congressional powers to do the necessary work of limiting the federal government. That conventional story is historically unfounded. It is not supported by contemporary evidence, and it was roundly disbelieved at the time. Although it is not possible to know for certain why (really, for what mix of reasons) the Framers omitted a bill of rights, it seems likely that one major reason was that formulating a bill of rights would have provoked a bitter fight …
Assessing Baby Leaf Kale (Brassica Oleracea) Waste Production Mitigation In The Transition To Sustainable Packaging With The Application Of Silicon Through An Integrative Model Of Quality, Francesco S. Giordano, Andrew Reynolds, Catherine M. Burgess, Lorraine Foley, Jesus M. Frias
Assessing Baby Leaf Kale (Brassica Oleracea) Waste Production Mitigation In The Transition To Sustainable Packaging With The Application Of Silicon Through An Integrative Model Of Quality, Francesco S. Giordano, Andrew Reynolds, Catherine M. Burgess, Lorraine Foley, Jesus M. Frias
Articles
This research builds a mathematical modelling to assess food waste production when designing sustainable packaging solutions integrated with an agricultural intervention in kale production. The model utilizes experimental data obtained from simulated retail and distribution storage conditions to assess the probability of the product to be found out of technical specification and becoming waste. The packaging design was made using a system of differential equations describing the gas exchanges inside the packaging. The waste was estimated fitting linear mixed effect models to the postharvest experimental data, accounting for the variability between and within groups. A field experiment with kale treated …
High-Precision Digital Light Processing (Dlp) Printing Of Microstructures For Microfluidics Applications Based On A Machine Learning Approach, Xinhui Wang, Jinghang Liu, Ruihai Dong, Michael D. Gilchrist, Nan Zhang
High-Precision Digital Light Processing (Dlp) Printing Of Microstructures For Microfluidics Applications Based On A Machine Learning Approach, Xinhui Wang, Jinghang Liu, Ruihai Dong, Michael D. Gilchrist, Nan Zhang
Articles
Digital light processing (DLP) is renowned for its precision, but the challenge lies in the identification of optimal print parameters to minimise print errors and enhance overall print accuracy. This study introduces a groundbreaking approach by integrating 'Random Forest' (RF) models with DLP printing to construct a predictive model for printing errors to achieve unparalleled precision. We conducted experiments using common commercial resins to print, resulting in a comprehensive dataset of 690 experimental datasets. Consequently, we validated this approach by fabricating Y-type microfluidic structures with a minimum feature size printing of 2 µm and herringbone mixer structures with feature sizes …
Modeling Redistribution Of Nanozeolites In Holographic Recording, Dana Mackey, Jack Lyons, Izabela Naydenova
Modeling Redistribution Of Nanozeolites In Holographic Recording, Dana Mackey, Jack Lyons, Izabela Naydenova
Articles
Zeolite doped photopolymers have been studied experimentally due to their potential application in the development of optical sensors. It has been shown that dopant redistribution can be achieved by holographic recording and has a direct influence on the sensitivity of the recorded grating. To achieve better theoretical understanding of these processes, this paper proposes an extended photopolymerization-diffusion mathematical model for describing the dynamics of nanozeolite redistribution during recording in an acrylamide-based photopolymer. Using numerical simulations of this model, we investigate how recording conditions, dopant transport parameters, and initial load affect the refractive index modulation of the resulting photonic structure.
Disaggregating Longer-Term Trends From Seasonal Variations In Measured Pv System Performance, Chibuisi Chinasaokwu Okorieimoh, Brian Norton, Michael Conlon
Disaggregating Longer-Term Trends From Seasonal Variations In Measured Pv System Performance, Chibuisi Chinasaokwu Okorieimoh, Brian Norton, Michael Conlon
Articles
Photovoltaic (PV) systems are widely adopted for renewable energy generation, but their performance is influenced by complex interactions between longer-term trends and seasonal variations. This study aims to remove these factors and provide valuable insights for optimising PV system operation. We employ comprehensive datasets of measured PV system performance over five years, focusing on identifying the distinct contributions of longer-term trends and seasonal effects. To achieve this, we develop a novel analytical framework that combines time series and statistical analytical techniques. By applying this framework to the extensive performance data, we successfully break down the overall PV system output into …
Dynamic Thermal Effect In A Hollow Core Microbottle Resonator, Zhe Wang, Zhuochen Wang, Anuradha Rout, Rayhan Habib Jibon, Anand V. R, Fangfang Wei, Qiang Wu, Yuliya Semenova, Northumbria University
Dynamic Thermal Effect In A Hollow Core Microbottle Resonator, Zhe Wang, Zhuochen Wang, Anuradha Rout, Rayhan Habib Jibon, Anand V. R, Fangfang Wei, Qiang Wu, Yuliya Semenova, Northumbria University
Articles
Dynamic thermal wavelength shift in hollow core microbottle resonators has been experimentally demonstrated using the frequency-detuning method. A linewidth broadening phenomenon is observed when the tunable laser is swept from a shorter wavelength to a longer wavelength. The thermal effect in the microbottles with various diameters as a function of the power and sweep frequency of the tunable laser has been studied and analyzed. In addition, the effect of thermal broadening on multiple WGM resonances within the spectrum has been observed, demonstrating that broadening of the linewidth of the first WGM resonance suppresses the subsequent WGM resonances during the up-scanning …
Addressing The Complexity Of Spatial Teaching: A Narrative Review Of Barriers And Enablers, Ergi Bufasi, Ting Jun Lin, Ursa Benedicic, Marten Westerhof, Rohit Mishra, Dace Namsone, Inese Dudareva, Sheryl Sorby, Lena Gumaelius, Remke M. Klapwijk, Jeroen Spandaw, Brian Bowe, Colm O'Kane, Gavin Duffy, Marianna Pagkratidou, Jeffrey Buckley
Addressing The Complexity Of Spatial Teaching: A Narrative Review Of Barriers And Enablers, Ergi Bufasi, Ting Jun Lin, Ursa Benedicic, Marten Westerhof, Rohit Mishra, Dace Namsone, Inese Dudareva, Sheryl Sorby, Lena Gumaelius, Remke M. Klapwijk, Jeroen Spandaw, Brian Bowe, Colm O'Kane, Gavin Duffy, Marianna Pagkratidou, Jeffrey Buckley
Articles
Extensive research has established that spatial ability is a crucial factor for achieving success in Science, Technology, Engineering, and Mathematics (STEM). However, challenges that educators encounter while teaching spatial skills remain uncertain. The purpose of this study is to develop a research framework that examines the interrelationships, barriers, and enablers amongst various educational components, including schools, teachers, students, classrooms, and training programs, that are encountered when teaching for spatial ability development. A thorough examination of international research, in combination with a detailed review of the primary Science and Mathematics curricula in Ireland, Latvia, Sweden, and the Netherlands, is undertaken to …
Influence Of Seasonality And Public-Health Interventions On The Covid-19 Pandemic In Northern Europe, Gerry A. Quinn, Michael Connolly, Norman E. Fenton, Steven J. Hatfill, Paul Hynds, Coilín Óhaiseadha, Karol Sikora, Willie Soon, Ronan Connolly
Influence Of Seasonality And Public-Health Interventions On The Covid-19 Pandemic In Northern Europe, Gerry A. Quinn, Michael Connolly, Norman E. Fenton, Steven J. Hatfill, Paul Hynds, Coilín Óhaiseadha, Karol Sikora, Willie Soon, Ronan Connolly
Articles
Background: Most government efforts to control the COVID-19 pandemic revolved around non-pharmaceutical interventions (NPIs) and vaccination. However, many respiratory diseases show distinctive seasonal trends. In this manuscript, we examined the contribution of these three factors to the progression of the COVID-19 pandemic. Methods: Pearson correlation coefficients and time-lagged analysis were used to examine the relationship between NPIs, vaccinations and seasonality (using the average incidence of endemic human beta-coronaviruses in Sweden over a 10-year period as a proxy) and the progression of the COVID-19 pandemic as tracked by deaths; cases; hospitalisations; intensive care unit occupancy and testing positivity rates in six …
Structure-Function Relationship Of Oat Flour Fractions When Blended With Wheat Flour: Instrumental And Nutritional Quality Characterization Of Resulting Breads, Mahmoud Said Rashed, Milica Pojić, Ciara Mcdonagh, Eimear Gallagher, Jesus M. Frias, Shivani Pathania
Structure-Function Relationship Of Oat Flour Fractions When Blended With Wheat Flour: Instrumental And Nutritional Quality Characterization Of Resulting Breads, Mahmoud Said Rashed, Milica Pojić, Ciara Mcdonagh, Eimear Gallagher, Jesus M. Frias, Shivani Pathania
Articles
Abstract: The present work investigated the structure-function relationship of dry fractionated oat flour (DFOF) as a techno-functional ingredient using bread as a model system. Mechanically, DFOF fractions (F), that is, F1: <224 µm, F2: 250–280 µm, F3: 280–500 µm, F4: 500–600 µm, and whole oat flour (F5) were blended with white wheat flour at 10%, 30%, and 50% substitution levels for bread making. The blended flours, doughs, and bread samples were assessed for their techno-functional, nutritional, and structural characteristics. The results of Mixolab and the Rapid Visco Analyzer show that the 50% substituted F3 fraction exhibits the highest water absorption properties (69.53%), whereas the 50% F1 fraction exhibits the highest peak viscosity of the past slurry. Analysis of bread samples revealed a lower particle size of DFOF fractions and higher supplementation levels, increased β-glucan levels (0.13–1.29 g/100 bread (db), reduced fermentable monosaccharides, that is, glucose (1.44–0.33 g/100 g), and fructose (1.06–0.28 g/100 g). The effect of particle size surpassed the substitution level effect on bread volume reduction. The lowest hardness value for F1 is 10%, and the highest value for F2 is 50%. The total number of cells in the bread slice decreased from the control to the F4 fraction (50%). Multi-criteria analysis indicated that DFOF fractions produced breads with similar structure and higher nutritional value developed from white wheat flour. Practical Application: The use of mechanically fractionated oat flours fractions in white wheat flour breads can improve the nutritional profile without affecting the physical properties of the bread product. Based on the oat flour fractions, bakers and food processing companies can tailor the bread formulations for high β-glucan, high fiber, and low reduced sugar claims.
Signatures Of Time Interval Reproduction In The Human Electroencephalogram (Eeg), Harvey Mccone, John. S. Butler, Redmond. G. O'Connell
Signatures Of Time Interval Reproduction In The Human Electroencephalogram (Eeg), Harvey Mccone, John. S. Butler, Redmond. G. O'Connell
Articles
No abstract provided.
Probing A Neural Unreliability Account Of Auditory Sensory Processing Atypicalities In Rett Syndrome, Tufikameni Brima, Shlomit Beker, Kevin D. Prinsloo, John Butler, Aleksandra Djukic, Edward G. Freedman, Sophie Molholm, John J. Foxe
Probing A Neural Unreliability Account Of Auditory Sensory Processing Atypicalities In Rett Syndrome, Tufikameni Brima, Shlomit Beker, Kevin D. Prinsloo, John Butler, Aleksandra Djukic, Edward G. Freedman, Sophie Molholm, John J. Foxe
Articles
Background: In the search for objective tools to quantify neural function in Rett Syndrome (RTT), which are crucial in the evaluation of therapeutic efficacy in clinical trials, recordings of sensory-perceptual functioning using event-related potential (ERP) approaches have emerged as potentially powerful tools. Considerable work points to highly anomalous auditory evoked potentials (AEPs) in RTT. However, an assumption of the typical signal-averaging method used to derive these measures is “stationarity” of the underlying responses – i.e. neural responses to each input are highly stereotyped. An alternate possibility is that responses to repeated stimuli are highly variable in RTT. If so, this …
Covid-19 Vaccine Race–The Shadow Of Political And Multinational Interests, Daniel Rajmil, Lucía Morales, Toni Aira
Covid-19 Vaccine Race–The Shadow Of Political And Multinational Interests, Daniel Rajmil, Lucía Morales, Toni Aira
Articles
The COVID-19 pandemic caused global disruption in 2020, throwing the world into an unprecedented health crisis with unpredicted socio-economic consequences. Strikingly, politicians and supranational organizations failed to collaborate and coordinate a united global response. In light of this, this research study explores how the vaccine race may have been used as a weapon of political communication, constantly influenced by international relations and economic interests. This study analyses the US response to the COVID-19 pandemic and how the vaccine development was used to support Trump's political discourse to gain international political leadership amidst the electoral campaign to become reelected. The core …
Data Justice In Education: Toward A Research Agenda, Luci Pangrazio, Glenn Auld, Julianne Lynch, Carly Sawatzki, Gavin Duffy, Shelley Hannigan, Jo O'Mara
Data Justice In Education: Toward A Research Agenda, Luci Pangrazio, Glenn Auld, Julianne Lynch, Carly Sawatzki, Gavin Duffy, Shelley Hannigan, Jo O'Mara
Articles
Educational institutions increasingly rely on digital platforms to deliver content and learning, monitor attendance, communicate with stakeholders, and evaluate institutional performance. Despite the efficiency and accessibility gains they offer, digital platforms are powered by personal data which, through a process of datafication, can be used to track, monitor, and profile staff and students. The insights drawn from this data can be used to shape educational and professional futures. This article examines how datafication has become a social justice issue in education, discussing the implications for well-being, decision-making, governance, and power in education. Using Hintz and colleagues framework for data justice, …
An Image Processing Approach For Real-Time Safety Assessment Of Autonomous Drone Delivery, Assem A. Abdelhak, Dan Moss, Alan Hicks, Susan Mckeever
An Image Processing Approach For Real-Time Safety Assessment Of Autonomous Drone Delivery, Assem A. Abdelhak, Dan Moss, Alan Hicks, Susan Mckeever
Articles
The aim of producing self-driving drones has driven many researchers to automate various drone driving functions, such as take-off, navigation, and landing. However, despite the emergence of delivery as one of the most important uses of autonomous drones, there is still no automatic way to verify the safety of the delivery stage. One of the primary steps in the delivery operation is to ensure that the dropping zone is a safe area on arrival and during the dropping process. This paper proposes an image-processing-based classification approach for the delivery drone dropping process at a predefined destination. It employs live streaming …
A Novel Integration Of Data-Driven Rule Generation And Computational Argumentation For Enhanced Explainable Ai, Lucas Rizzo, Damiano Verda, Serena Berretta, Luca Longo
A Novel Integration Of Data-Driven Rule Generation And Computational Argumentation For Enhanced Explainable Ai, Lucas Rizzo, Damiano Verda, Serena Berretta, Luca Longo
Articles
Explainable Artificial Intelligence (XAI) is a research area that clarifies AI decision-making processes to build user trust and promote responsible AI. Hence, a key scientific challenge in XAI is the development of methods that generate transparent and interpretable explanations while maintaining scalability and effectiveness in complex scenarios. Rule-based methods in XAI generate rules that can potentially explain AI inferences, yet they can also become convoluted in large scenarios, hindering their readability and scalability. Moreover, they often lack contrastive explanations, leaving users uncertain why specific predictions are preferred. To address this scientific problem, we explore the integration of computational argumentation—a sub-field …
Relative Effectiveness Of A Radionuclide (210pb), Surface Elevation Table (Set), And Lidar At Monitoring Mangrove Forest Surface Elevation Change, Richard Mackenzie, Ken Krauss, Nicole Cormier, Eugene Eperiam, Jan Van Aardt, Ali Rouzbeh-Kargar, Jessica Grow, Val Klump
Relative Effectiveness Of A Radionuclide (210pb), Surface Elevation Table (Set), And Lidar At Monitoring Mangrove Forest Surface Elevation Change, Richard Mackenzie, Ken Krauss, Nicole Cormier, Eugene Eperiam, Jan Van Aardt, Ali Rouzbeh-Kargar, Jessica Grow, Val Klump
Articles
Sea-level rise (SLR) is one of the greatest future threats to mangrove forests. Mangroves have kept up with or paced past SLR by maintaining their forest floor elevation relative to sea level through root growth, sedimentation, and peat development. Monitoring surface elevation change (SEC) or accretion rates allows us to understand mangrove response to SLR and prioritizes resilient ecosystems for conservation or vulnerable ecosystems for restoration. We compared three methods to measure SEC and accretion in mangrove forests: 210Pb, surface elevation tables (SETs), and a terrestrial light detection and ranging system (compact biomass LiDAR—CBL). Lead-210 accretion rates were not significantly …
The Need For Energy Storage On Renewable Energy Generator Outputs To Lessen The Geeth Effect, I.E. Short-Term Variations Mainly Associated With Wind Turbine Active Power Output, Tony Kealy
Articles
Many studies investigating the short-term variations associated with the power output from wind turbine generators utilise simulated or modelled data in the analysis. This current study uses short-term empirical data downloaded directly from operational wind turbines via electrical power quality meters. The empirical data shows that the short-term variations (one-second or sub-one-second timeframe) occur continuously over most of the power output range. A novel name is proposed, the Geeth Effect, for this variability phenomenon. The Geeth Effect is measured using the coefficient of variation mathematical expression and is likely contributing to (i) lower-than-expected financial and environmental benefits associated with …
Exploring The Impact Of Signal Quality Enhancement On Heart Sound Classification Models, Davoud Shariat Panah, Andrew Hines, Susan Mckeever
Exploring The Impact Of Signal Quality Enhancement On Heart Sound Classification Models, Davoud Shariat Panah, Andrew Hines, Susan Mckeever
Articles
Limited cardiology resources increase the urgency for automated heart disease screening for the general public. Heart sound diagnostic models have been recently employed as a cost-effective solution for the initial screening of heart disease. Noise in heart sound recordings, however, can reduce the performance of such data-driven models. Various quality enhancement approaches have been adopted to alleviate the destructive impact of noise on model performance. One approach is universal noise reduction which applies denoising techniques to recordings, irrespective of their noise level. The second approach is targeted noise reduction, which applies denoising solely to recordings deemed to need it, based …
Renormalized Stress-Energy Tensor For Scalar Fields In Hartle-Hawking, Boulware, And Unruh States In The Reissner-Nordström Spacetime, Julio Arrechea, Cormac Breen, Adrian Ottewill, Peter Taylor
Renormalized Stress-Energy Tensor For Scalar Fields In Hartle-Hawking, Boulware, And Unruh States In The Reissner-Nordström Spacetime, Julio Arrechea, Cormac Breen, Adrian Ottewill, Peter Taylor
Articles
In this paper, we consider a quantum scalar field propagating on the Reissner-Nordström black hole spacetime. We compute the renormalized stress-energy tensor for the field in the Hartle-Hawking, Boulware and Unruh states. When the field is in the Hartle-Hawking state, we renormalize using the recently developed “extended coordinate” prescription. This method, which relies on Euclidean techniques, is very fast and accurate. Once, we have renormalized in the Hartle-Hawking state, we compute the stress-energy tensor in the Boulware and Unruh states by leveraging the fact that the difference between stress-energy tensors in different quantum states is already finite. We consider a …
Raman Spectroscopic Analysis Of Human Serum Samples Of Convalescing Covid-19 Positive Patients, Hugh Byrne, Naomi Jackson, Jaythoon Hassan
Raman Spectroscopic Analysis Of Human Serum Samples Of Convalescing Covid-19 Positive Patients, Hugh Byrne, Naomi Jackson, Jaythoon Hassan
Articles
Rapid screening, detection and monitoring of viral infection is of critical importance, as exemplified by the rapid spread of SARS-CoV-2, leading to the worldwide pandemic of COVID-19. This is equally the case for the stages of patient convalescence as for the initial stages of infection, to understand the medium and long terms effects, as well as the efficacy of therapeutic interventions. Optical spectroscopic techniques potentially offer an alternative to currently employed techniques of screening for the presence, or the response to infection. In this study, the ability of Raman spectroscopy to distinguish between samples of the serum of convalescent COVID-19 …
The Federal Reserve's Mandates, David T. Zaring, Jeffery Y. Zhang
The Federal Reserve's Mandates, David T. Zaring, Jeffery Y. Zhang
Articles
Solutions to systemic problems such as climate change and racial inequities have eluded policymakers for decades. In searching for creative solutions, some policymakers have recently thought about expanding the Federal Reserve’s core set of macroeconomic mandates to tackle these issues. But there are real questions about whether that can be done from a legal perspective and whether that should be done from a policy perspective.
A Primer On The Legendre Transformation, Steven J. Kilner, David L. Farnsworth
A Primer On The Legendre Transformation, Steven J. Kilner, David L. Farnsworth
Articles
Guidance is offered for understanding and using the Legendre transformation and its associated duality among functions and curves. The genesis of this paper was encounters with colleagues and students asking about the transformation. A main feature is simplicity of exposition, while keeping in mind the purpose or application for using the transformation.
Cognitive Function Among Military Veterans With Stem Occupations., Justin T Mcdaniel, Kevin N Hascup, Erin R Hascup, Ugochukwu G Ezigbo, Amanda M Weidhuner, Harvey Henson, David L Albright
Cognitive Function Among Military Veterans With Stem Occupations., Justin T Mcdaniel, Kevin N Hascup, Erin R Hascup, Ugochukwu G Ezigbo, Amanda M Weidhuner, Harvey Henson, David L Albright
Articles
No abstract provided.