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Monetization Of Crowd-Sourced Fog Node Services Using Blockchain And Smart Contracts And The Adaptation Of Ml For Data Reduction
Full text linkFog computing is increasingly becoming the building block for the explosive growth in edge computing as it affords the edge all the capabilities of the cloud with low latency and more decongested internet traffic. It accounts for the limitations found in IoT and other edge devices regarding memory, CPU, and bandwidth. While firms are providing these fog nodes, there remains the issue of data ownership, pricing fairness, and the amounts charged to customers based on the quality of services received. Our work proposed a decentralized blockchain-based fog paradigm that addressed these issues and provides a platform for users to contribute devices (nodes) to the fog network and get incentives when their contributed nodes are used for fog services. Our experiment showed that fairness can be achieved between the users and fog nodes, with both submitting reports of the services rendered or received at the end of every connection. An independent smart contract reviews these reports, runs analysis, and the proper charge is
levied on the user based on the services received. The system met the security core principle of confidentiality, integrity and availability. The feature of this system is enhanced by introducing a data reduction model that sits between the IoT and the fog nodes. This improves the performance of the fog network by reducing the noise and data size from IoT devices processed by the fog network. Our work introduced a system that efficiently handled this by building a machine learning model that utilized the math of principal component analysis and singular value decomposition (PCA/SVD) for data reduction. The unique value of this combination of data reduction and feature selection methods shows that while the data was greatly decreased, the feature of the data was retained. This was verified using standard benchmark datasets and a large private IoT dataset to verify the system\u27s effectiveness.
Index terms - Blockchain, cloud, edge computing, Ethereum, fairness, fog, Internet of Things (IoT), Nodes, Principal Component Analysis (PCA), Quality of Service (QoS), Singular Value Decomposition (SVD)
Spatial And Temporal Analysis Of Real Fluid Thermodynamics Nonlinearities On Turbulent Mixing In Supercritical Fluids
Full text linkThe impact of thermodynamic nonlinearities on flow properties and turbulence was the focus of this study, which investigated the spatial and temporal dynamics of supercritical CO₂ turbulent mixing layers. Beyond their critical point, where parameters such as density, pressure, temperature, isothermal compressibility, and thermal expansion show significant gradients and fluctuations, supercritical fluids deviate sharply from ideal gas behavior. These nonlinearities have a major effect on turbulence and cause complex mixing behavior that has important ramifications for the machines that operate in supercritical environments.
The study explored the effects of local variations of important thermodynamic variables on the fluid dynamics in a spatially evolving mixing layer axially along the X axis, and transversely across the mixing layer along the Y axis, using LES. Five locations downstream of a finite splitter plate are the subject of the analysis. This study also analyzed the change of parameters at the intersecting points of vertical stations and centerline with respect to time. Maxwell\u27s relations and the Jacobian inversion method were used to quantify the effects of factors such as isothermal compressibility and the thermal expansion coefficient on observables such as temperature and pressure.
The major findings include sudden inflections in the partial derivative of density with respect to pressure, which signify regions of a marked difference in isothermal compressibility. These changes are more pronounced downstream, highlighting the coupling of thermodynamic properties and turbulence. In temperature profiles, it is evident that the rise of fluctuations and sharp gradients enhances the formation of turbulent structures. This highlights the heat expansion effect on the mixing. Also, there are large pressure and enthalpy fluctuations in regions with significant thermodynamic gradients. Pressure fluctuations driven by these nonlinear property increased in amplitude downstream, potentially leading to instabilities in confined environments. In a qualitative sense the study shows that thermodynamic nonlinearities lead to active flow regimes, where turbulence is enhanced. Quantitatively, the outcomes indicate that near the critical point slight perturbations often produce dramatic property changes necessitating advanced modeling methods. These results highlight how thermodynamic nonlinearities are significant to supercritical CO₂ mixing-layer evolution.
Index Terms: Bulk thermal expansion coefficient, isothermal compressibility, Large Eddy Simulation, supercritical condition, thermodynamic nonlinearities, and turbulent flow
Supercritical Water Oxidation And A Preliminary Concept For Lunar Application
Full text linkAs the reach of space exploration extends further from Earth, the cost, time, and energy requirements necessary for life support of crewed expeditions exponentially increases. This makes the reclamation of resources paramount to the viability of such missions and will eventually become a major constraint for future destinations due to the expensive delivery of materials. Thusly, Supercritical Water Oxidation (SCWO) has been proposed to meet the requirements for the recovery of potable water needed for the drinking, hygiene, laundry, and irrigation performed by astronauts. This technique utilizes supercritical water’s properties above 374°C and 22.1 MPa alongside oxidants to convert organic hydrocarbons into products of pure water and carbon dioxide: generating higher yields of recovery without the waste by-products present within alternative waste treatment methods. The purpose of this research was to validate the effectiveness of SCWO for continuous operation, improve upon previous reactor designs with the addition of a mixing nozzle, perform a preliminary single-species analysis of waste constituents, and to develop a conceptual SCWO reactor for an early lunar base.
For this work, a tubular reactor designed at NASA Glenn Research Center was used to perform SCWO methodologies on waste streams that include ersatz wastewater (EWW)—a simulant representative of waste found on the International Space Station, urea, acetic acid, and ethanol diluted with deionized water to varying concentrations. Peak reaction temperatures ranged between 588˚C to 690˚C with operation pressures ranging from 26 MPa to 28 MPa. Samples from each experiment were analyzed through measurements of Total Organic Carbon (TOC), pH, turbidity, conductivity, and Raman spectroscopy. On average, the ersatz-based solutions displayed a \u3e99% reduction in TOC. For the results of the urea-based solutions, the Raman characterizations showed greater development of intermittent species at lower throughputs suggesting an inverse trend with residence time and intermittent species generation. The opposite trend is present within the acetic acid Raman spectra that portray evidence of lesser intermittent species development at lower throughputs, or higher residence times. Finally, a lunar SCWO model was generated to perform a preliminary cost analysis for comparison with other water reclamation technologies proposed for ASA Artemis.
Index Terms: Raman spectroscopy, supercritical water, supercritical water oxidation (SCWO), Total Organic Carbon (TOC), water reclamation
Heavy Metals Removal By Micellar Enhanced Membrane Filtration From Aqueous Solution
No full textHeavy metals released from industrial effluents end up in rivers and oceans. These metals enter the human body through the ecosystem and accumulate, leading to severe health disorders. This study investigated the removal of heavy metals, cadmium (Cd2+) and cobalt (Co2+), using Micellar Enhanced Membrane Filtration (MEMF). MEMF is a surfactant-based membrane separation technique where the addition of a surfactant in wastewater forms micelles. Heavy metals attach to the hydrophilic heads of micelles. The resulting feed solution is subjected to a pressure difference in a filtration system, forcing it through a membrane with a smaller pore size that retains micelle particles and attached contaminants. In this study, sodium dodecyl sulfate (SDS) served as the surfactant, and flat sheet polyethersulfone (PES) ultrafiltration and microfiltration membranes were used as the filtration medium to separate Cd2+ and Co2+ metal ions from simulated lab water. The experiments involved studying several important parameters, such as examining the removal efficiency of membranes without using SDS, determining the optimum concentration of SDS for Cd2+ and Co2+ removal, and evaluating the performance of the membrane for a longer duration. Other parameters include analyzing the removal efficiency by varying concentrations of metal ions while keeping the SDS dosage constant, examining the effect of pH and electrolyte concentrations on the removal of Cd2+ and Co2+. Several analytical characterizations were performed, such as FT-IR, FE- SEM, etc. The optimum SDS concentration for Cd2+ and Co2+ removal was 1 Critical Micelle Concentration (CMC). Both microfiltration and ultrafiltration membranes showed a removal efficiency above 99% for removing Cd2+ and Co2+ at 1 CMC SDS. The real-time flux of the microfiltration membrane was higher than that of the ultrafiltration membrane. The presence of electrolytes reduced the removal efficiency for Cd2+ and Co2+. The removal efficiency of Cd2+ and Co2+ remained unchanged between pH 3 and 9. The results indicate that MEMF technology effectively removes heavy metals such as Cd2+ and Co2+. Our findings suggest that ultrafiltration and microfiltration membranes, aided by the surfactant SDS, are suitable for eliminating Cd2+, Co2+ ions, and other heavy metals from wastewater.
Index Terms _ Cadmium (Cd2+), cobalt (Co2+), heavy metal removal, micellar-enhanced ultrafiltration, microfiltration, sodium dodecyl sulfate, and wastewater
Improving Hiv Pep Patient Follow-Up Appointment And Laboratory Testing In A Telehealth Setting: A Quality Improvement Project
Full text linkThe ongoing HIV epidemic in the United States highlights the need for innovative prevention strategies, including non-occupational post-exposure prophylaxis (nPEP). This Doctor of Nursing Practice (DNP) project evaluated a telehealth-based intervention aimed at increasing HIV PEP follow-up appointments and laboratory completion rates, while also enhancing provider knowledge. Dual interventions included a patient reminder system and provider education. While provider knowledge significantly improved post-intervention, based on Cohen’s d effect size of 0.62, clinical significance was demonstrated by follow-up appointment rates declining from 44% pre-intervention to 41% post-intervention. Laboratory completion rates also decreased, with 53% of patients completing labs pre-intervention compared to 38% post-intervention (χ² = 5.54, p = .019). These findings suggest that provider education was effective, with the reminder systems improving follow-up and laboratory adherence in a telehealth setting.
Keywords: HIV PEP (non-occupational post-exposure prophylaxis), laboratory completion, KAP (knowledge, attitude, and practice, patient-reminder system
Evaluation Of A Nurse Practitioner-Led Preoptimization Care Management Program’s Impact On Patient Satisfaction For Total Hip And Knee Arthroplasty
Full text linkThis evaluation project aimed to assess whether the nurse practitioner-led preoptimization care management program can increase patient satisfaction by improving the quality metrics, such as same-day ambulation post-surgery, discharge to home, and compliance in preoperative education. The evaluation retroactively reviewed 46 charts of primary total knee and hip arthroplasty patients, male (38%) and female (62%), aged 43 to 84. Using Fisher’s exact test to examine the Net Promoter Scores (NPS) for six months of the PCM program, there was no significant increase in patient satisfaction scores, despite PCM patients averaging 89% compared to non-PCM patients at 83%, based on an alpha value of .05, OR = 1.86, p = .532. The results suggested that the PCM program positively affected the patients enrolled, although it was not statistically significant. The results of the Chi-square test for same-day ambulation and discharge home indicated there was a statistically significant increase based on an alpha value of .05, χ2(1) = 6.03, p = .014, and an alpha value of .05, p = .025, respectively, suggesting that the implementation of the PCM program did significantly increase same-day ambulation and discharge home compliance rates. However, the Chi-square test results for preoperative education compliance were insignificant based on an alpha value of .05, χ2(1) = 0.35, p = .555.
These findings indicated that a quality-focused approach improved patient satisfaction. In addition, there was a statistically significant increase in patients meeting quality metrics measured by the facility for PCM patients versus non-PCM patients. The findings indicated that quality measures may not correlate with improving patient satisfaction, but healthcare providers should focus on individualized education and health assessment. Hospital administrators should consider re-evaluating quality measures and looking for metrics directly affecting patient satisfaction.
Keywords: total joint arthroplasty, NPS, net provider score, total hip arthroplasty satisfaction, patient satisfaction post joint replacement, joint replacement education, arthroplasty, preoperative education for joint replacement, preoptimization, joint replacement, nurse navigator, patient care management, joint replacement, same-day ambulatio
(R2151) Error Estimates of Barycentric Lagrange Interpolation
No full textBarycentric interpolation, which comes from Lagrange interpolation, is a useful method in numerical analysis. In this research paper, we explain how the barycentric interpolation formula is derived and discuss its features. We compare its stability and performance with the traditional Lagrange formula. First, we show how to get the barycentric formula from the Lagrange polynomial and present it as a rational function. We also provide an estimate of the error. Then, we use numerical examples to show that the barycentric formula is more stable and works better, especially when the degree of interpolation is high. Our results show that the barycentric method stays stable and gives smaller errors than the Lagrange method. This paper helps improve the understanding of how strong and reliable the barycentric method is, and how it can be better than older methods in numerical analysis. In particular, the novelty of this work lies in presenting a structured error analysis based on Legendre nodes and validating the stability of barycentric interpolation through comparison across four distinct classes of test functions