bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of Orem's Self-Care Model of Nursing on Hand Symptoms and Life Activities in Geriatric Individuals Diagnosed With Rheumatoid Arthritis: A Pilot Study
Authors: Tuna Halil Ibrahim , Alparslan Guler Balci 
Published: April 2021

Background and PurposeAccording to Orem's self-care deficit theory, when patients cannot meet their care needs, they need nursing systems for maintaining their health. Nursing care for elderly patients with rheumatoid arthritis (RA) should be based on maintaining self-care. This study aims to determine the effects of Orem's self-care model of nursing care given to geriatric patients with RA on hand symptoms, life activities, and hand pain.MethodsThe study sample comprised a total of 22 patients (intervention group, 11; control group, 11) who met the sample selection criteria at a rheumatology outpatient clinic of a university hospital between June 17, 2019 and September 20, 2019. All interviews with patients in the intervention group were conducted by daily phone calls and a face-to-face interview at the hospital every 4 weeks. Patients continued to receive routine prescription by a physician during the course of application.ResultsNo difference was observed between the groups in terms of descriptive patient characteristics (p > .05). Hand pain, hand symptoms, and life activities of patients in the intervention group were measured at study initiation, week 4, and week 8. Intragroup comparison revealed that hand pain, hand symptoms, and life activity scores were lowest at week 8 in the intervention group (p < .05).Implications for PracticeThis study indicates that nursing care given according to Orem's self-care model is effective in reducing pain, improving hand functions, and performing life activities.
A Framework for Protecting Pregnant Women in the Era of COVID-19 Pandemic
Authors: Dongarwar Deepa , Ajewole Veronica , Harris Kiydra , Oduguwa Emmanuella , Ofili Theresa , Onyenaka Collins , Arnold Sade , Broussard Jorhn , Ishioye Joan , Marshal Jasmine , Mayoya Jamila , Le Danchau , Fadel Mouch , Olaleye Omonike , Salihu Hamisu 
Published: April 2021

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent for the coronavirus disease 2019 (COVID-19) pandemic, highlighted and compounded problems while posing new challenges for the pregnant population. Although individual organizations have provided disparate information, guidance, and updates on managing the pregnant population during the current COVID-19 pandemic, it is important to develop a collective model that highlights all the best practices needed to protect the pregnant population during the pandemic. To establish a standard for ensuring safety during the pandemic, we present a framework that describes best practices for the management of the pregnant population during the ongoing COVID-19pandemic.

Copyright © 2021 Dongarwar, et al. Published by Global Health and Education Projects, Inc. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in this journal, is properly cited.
Application of LC-MS and Methyl Orange Methods for Improved Residual Surfactant Detection in Liquids-Rich Shale Plays
Authors: He Kai , Heckel John , De Hernandez Vittoria Balsamo , Nguyen Duy 
Published: April 2021

Abstract
Successful field trials of surfactant-based Production Enhancement (PROE) technology in different shale plays including Permian Basin, Bakken and Eagle Ford indicate that specially tailored surfactant formulations can improve the unconventional well productivity during flowback and production. One major challenge for the operator is to further optimize the surfactant dosage to maximize the economic return. Analysis of the residual surfactant concentration in the produced water (PW) might provide a new path to optimize the surfactant application in the field. Such quantitative measurements can help understand how much surfactant is consumed in the downhole and how much surfactant is in the flowback, and possibly correlate back to the well performance. Additionally, surfactant partitioning and adsorption behaviors can be studied through residual analysis, which will further provide guidance to develop next generation of surfactant formulations.
In this study, a liquid chromatography-mass spectrometry (LC-MS) method was developed to accurately measure the residual surfactant concentration in the produced water. The liquid chromatograph (LC) separates the surfactant from sample matrix and avoids the possible interference, and then the mass spectrometer (MS) detects the separated surfactant, signal correlating to the residual concentration. This analytical method provides unrivalled selectivity and specificity compared to other methods reported in the literature. In addition, a Methyl Orange method was developed and can potentially be used in the field for quicker measurements. Produced water samples collected from a Huff-and-Puff treatment in the Permian Basin were evaluated using both methods. Our results indicate that both methods can successfully capture the trend of residual concentration vs. production time. The deviation between LC-MS and Methyl Orange measurements was due to the presence of ADBAC (alkyldimethylbenzylammonium chloride) in the produced water, which is a cationic amine surfactant typically used as biocide in the well stimulation. It produces positive interference and thus leads to a higher residual detection in the Methyl Orange test. Notably, the residual concentration of surfactant in produced water decreased with time after the well was placed back to production, which is consistent with the concept that more surfactant will adsorb to the rock surface or partition into the oil phase over production time.
In summary, we believe the LC-MS and Methyl Orange methods can potentially be used to detect residual concentration for any type of surfactant-based applications in unconventional reservoirs including Huff-and-Puff, completion, frac protect, surfactant flooding and re-frac. The field application of surfactant-based chemistry followed by this type of residual analysis can help understand the underlying mechanisms of the surfactant and provide further guidance for production optimization of shales.
Comprehensive Analysis of Water Cut Metering Accuracies
Authors: Castrup Suzanne 
Published: April 2021

Abstract
Accurate oil production monitoring is essential for scheduling well work and optimizing the economic performance of primary and enhanced recovery projects. The significance of water cut monitoring accuracy on oil rate determination is discussed and illustrated. This paper provides a comprehensive uncertainty analysis of several water cut monitoring methods commonly employed by oil field operators. These include liquid sampling, capacitance, microwave, ultrasonic, spectroscopy and density methods.
The basic operating principles of each monitoring method are described and measurement uncertainty analysis procedures are employed to identify key parameters that affect the overall accuracy of each water cut monitoring method. The analysis results provide useful accuracy assessments that can be used in water cut meter selection, field testing and implementation.
A Practical Gas Apparent Permeability Model: Multi-Scale Simulations of Rarefied Gas Flow in Matrix
Authors: Chai Di , Li Xiaoli 
Published: April 2021

Abstract
A common practice in gas-shale reservoir simulation, which arbitrarily increases intrinsic matrix permeability to match the production data, has been proven inefficient and unreliable. Alternatively, accurate estimations of gas apparent permeability (AP) in matrix is desired. This work presents an analytical AP model considering rarefaction in nanopores and coupling experimentally confirmed mechanisms in shale matrix for theoretical completeness. Meanwhile, physical terms in AP model are simplified with semi-empirical correlations for the practicability in large-scale field simulation. Compared with other gas transport models in nanopores, the newly-developed analytical model has been successfully validated against molecular dynamic (MD) simulation, direct simulation Monte Carlo (DSMC), Lattice Boltzmann (LB) simulation, and experimental flux results for five types of gases (i.e., methane, nitrogen, helium, argon, and oxygen) with the minimum deviation. It is observed that analytical models excluding Knudsen diffusion mechanism cannot fully characterize rarefaction effect. Next, Knudsen diffusion cannot be explained as the only underlying mechanism of rarefaction because the mass flux is largely underestimated in transition flow regime. However, the weighted superposition of second-order slip boundary and Knudsen diffusion can provide the satisfactory fitting with data. This work provides an analytical model which not only considers non-negligible multi-physics in shale reservoirs (i.e., rarefaction effect, multilayer adsorption, surface diffusion and confinement effect) but also simplifies non-linear physical terms using semi-empirical linear correlations to facilitate AP calculations in core-scale simulations.
Hybrid Sand Control Screen Using the Combined Surface and Depth Filtration
Authors: Hosseini Seyed Abolhassan , Roostaei Morteza , Mohammadtabar Farshad , Mohammadtabar Mohammad , Soroush Mohammad , Berner Kelly , Mahmoudi Mahdi , Miller Roger , Fattahpour Vahidoddin 
Published: April 2021

Abstract
Development of weakly and unconsolidated sand reservoirs require effective sand control media to prevent sand production. The existing sand control devices in the market are either relying on surface filtration to prevent sand production through size exclusion or bridging or depth filtration which relies on the pore size distribution of a porous filter or pack to prevent the sand from producing along the production fluids. In this study, we introduce a new hybrid sand screen that works based on a combined surface and depth filtration.
Radial Sand Control Evaluation (RSCE) testing facility was used to compare the solid production and flow performance of the new hybrid screen with various mesh media in multi-phase gas and liquid flow under various fluid injection scenarios. Solid production and flow performance were compared with investigated cases.
The new hybrid screen provides an optimized Open to Flow Area (OFA) in comparison to available surface filtration or depth filtration media, which provides required OFA, while prevents sanding. The robust design, low cost and manufacturing ease make it a suitable screen media for most sand control applications. The sand retention test results under various fluid injection scenarios including multi-phase oil, brine, and gas show that it outperforms the Dutch Twill (DT) weave and Reverse Dutch Twill (RDT) weave of equivalent aperture size, with better flow performance at constant flow rate tests compare to best-performing mesh media, while keeping the produced sand far below the acceptable thresholds. Hybrid design handles both high velocity and high Gas-Oil Ratio (GOR) better than equivalent depth filtration media of equivalent size.
This paper presents a detailed characterization, flow performance testing of a new hybrid sand control media that combines the surface filtration and depth filtration properties to achieve better solid retention and flow performance. The hybrid screen media is suitable for high-rate producers with high GOR.
Keywords: Hybrid Screen, Surface Filtration, Depth Filtration, Radial Sand Control Evaluation (RSCE) Testing
Application of Slurry Injection Technology in Biowaste Management - A New Discipline in Managing Bio-Waste in Economic and Environmentally Friendly Manner
Authors: Panchal Yashesh , Mounir Nihal , Loloi Mehdi , Mohamed Ibrahim , Abou-Sayed Omar , Abou-Sayed Ahmed 
Published: April 2021

Abstract
Carbon offset describes the environmental benefit from an initiative that avoids, reduces or removes greenhouse gases (GHGs) from the atmosphere. The Intergovernmental Panel on Climate Change has identified Carbon Dioxide (CO2), Methane (CH4) and Nitrous Oxide (N2O) as major constituent of the GHGs. Wastewater Treatment Facilities (WWTFs) among several other sectors is a neglected source for GHG emission. Considering the risk of rise in GHGs, United States along with other countries signed the Paris Agreement to respond to the global climate change threat in 2016. It is assessing projects to cut GHGs in exchange for emission credits that can be used to comply with goals they set under the United Nations pact.
In order to curb the GHG emission by WWTFs, an innovative approach "Bioslurry Injection" (BSI) can be implemented to reduce the emission of the GHGs produced during the course of biological and chemical treatment of wastewater. The technology is inherited from the traditional drill cutting injection and Carbon sequestration technology implemented by the Oil and Gas industry since 1980's. The BSI operation has the ability to accept the feed from different treatment stages after the initial screening process to prepare the injection slurry and help in controlling the GHG emission at respective treatment stage along with managing the intake volume.
The slurry can be prepared by mixing the treated biosolids with wastewater and injected into a pre-selected underground earth formation, where biosolids undergo anaerobic digestion and decompose into CO2 and CH4. An injection formation with sufficient capacity to accept the slurry is selected by conducting a detailed geomechanical and fracture simulation analyses. Along with the injection feasibility, the calculations of the amount of Carbon dioxide equivalent (CO2e) sequestrated underground by implementing BSI technique is presented in this paper.
The sequestration of decomposed GHGs is an environmentally friendly activity that has proved to be economically beneficial due to its ability to earn carbon offsets. According to the new carbon law in the state of California the amount of CO2e eliminated from the atmosphere can be traded to earn carbon credits. TIRE facility through its ability to sequester and thus eliminate emission of the GHGs from the atmosphere can gain up to $1.5M worth of carbon credits per year providing both environmental and economic benefit. Also, low capital and operating cost for the BSI facility due to its compact surface requirement is an additional advantage along with reduced risk of spillage hazard when BSI facility is incorporated within the WWTF boundaries.
Ignition Forecast Based on Chemical Kinetics and Uncertainty Quantification
Authors: Li Yunan , Anderson Timothy I. , Kovscek Anthony R. 
Published: April 2021

Abstract
The description of chemical kinetics is very import to the simulation of reactive transport for enhanced oil recovery (EOR). Characterizing petroleum ignition is especially important for simulation and prediction of In-Situ Combustion (ISC). In order to model crude oil oxidation reactions accurately, an experimental workflow is introduced to obtain kinetic parameters for ISC chemical reaction models. An optimization algorithm assists to match the reaction model parameters to the experimental results, and this validated model is used to predict ignition of crude oil in porous media. Apparent activation energy is estimated from ramped temperature oxidation experiments under several heating rates, including 1.5, 2.0, 2.5, 3.0, 5, 10, 15, and 20 °C/min. These experiments are separated into a small heating rates group (1.5, 2.0, 2.5, 3.0 °/min) and large heating rates (5, 10, 15, 20 °/min). The results show that experiments with small heating rates capture the details of reaction kinetics such that the estimated activation energy is more accurate, with the validated simulation model able to make accurate predictions for this particular crude oil. After matching the kinetics parameters, we predict the ignition conditions as a function of the air flow rates and the heat loss rates. The ignition envelope indicates that the window for air flow rates to ignite the oil decreases if the heat loss rate is high. Greater heat losses require more thermal energy to be released from the reaction to overcome losses and for ignition to occur. This leads to a narrower range of ignition air flow rates due to convective heat transfer. The uncertainty quantification results provide a confidence region for the ignition envelope impacted by the threshold temperature of the ignition criterion. The novelty of this work is the description of optimized combustion reaction models with rigorous experimental verification and uncertainty quantification for reactive transport simulations.
Fast Drilling Optimizer for Drilling Automation
Authors: Giftson Joy John Abish , Samuel Robello 
Published: April 2021

Abstract
The rate of penetration (ROP) was optimized using a particle swarm optimization algorithm for real-time field data to reduce drilling time and increase efficiency. ROP is directly related to drilling costs and is a major factor in determining mechanical specific energy, which is often used to quantify drilling efficiency. Optimization of ROP can therefore help cut down costs associated with drilling. ROP values were chosen from real-time field data, accounting for weight on bit, bit rotation, flow rate variation along with bit wear. A random forest regressor was used to find correlations between the dependent parameters. The parameters were then optimized for the given constraints to find the optimal solution space. The boundary constraints for the ROP function were determined from the real-time data. The function parameters were optimized using a particle swarm optimization algorithm. This is a meta-heuristic model used to optimize an objective function for its maximum or minimum within given constraints. The optimization method makes use of a population of solution particles which act as the particle swarm. These particles move collectively in the given solution space controlled by a mathematical model based on their position and velocity. This model makes use of the best-known solution for each particle and the global best position of the system to guide the swarm towards the optimal solution. The function was optimized for each well, providing optimal ROP values during real-time drilling. A fast drilling optimizer is crucial to automate and streamline the drilling process. This simultaneous optimization of ROP based on real-time data can be implemented during the process thereby increasing the efficiency of drilling as well as reducing the required drilling time.
NORM Scale Removal Using a High-Power Fiber Laser Beam Delivery
Authors: Lewis Janelle Branch , Dassey Adam , Grubb Daryl , Marshall Scott 
Published: April 2021

Abstract
In oil and gas operations, there is a potential for NORM scale to accumulate on process piping and equipment. This scale can be removed prior to recycling or disposal of the material, yet common removal methods may be costly, time consuming, or create large volumes of secondary waste streams that must be managed. The feasibility of using a laser beam delivery to remove NORM scale was investigated because of its potential to reduce the time and cost associated with scale removal without creating large secondary waste streams. Results from this study indicate that a laser beam delivery could be an effective method to remove NORM scale from a steel surface. Background levels of alpha and beta surface contamination and gamma exposure rate were achieved for certain pipe sections when applying a laser power of at least 5 kW. Alternative laser powers, linear speeds, or incident angles may optimize the removal efficiency for thicker scales or scales with higher surface contamination or gamma exposure rates.
A 17 Year Successional Enrichment Plantation of Tree Recruitment and Restoration in an African Tropical Forest
Authors: Omomoh Bernard Eromosele , Akomolafe Gbenga Festus , Brown Leah Spencer , Adekunle VAJ 
Published: April 2021

Abstract
Key message: The Enrichment Plantation of Akure Forest Reserve is one of the forests currently experiencing a 17-year-long post-disturbance following deforestation and fragmentation in Nigeria. Context: To better understand the contribution of enrichment planting on forest regeneration and restoration, when the Enrichment Plantation after 17 years of post-disturbance was examined. Aims: We studied the recruitment drive of aboveground and undergrowth stands of an Enrichment Plantation in the tropical forest reserve. We assess the trees diversity, species compositions, species richness, and growth forms of the vegetations. Methods: A total of 3(50m x50m) plots were sampled. A total of 47 aboveground tree species and 45 undergrowth stands from Enrichment Plantation were identified. A statistical analysis were used to quantified the data obtained from this resultsResults: The result shows an increase in the diversity and an even distribution of the species of the aboveground forest trees, compared to the undergrowth stands. Conversely, the aboveground forest trees have lower species richness as compared to the level of undergrowth stands. The sapling density was significantly higher than the aboveground tree of the. It was also observed that the aboveground forest trees and undergrowth stands are somewhat similar in species compositions, which implies that sapling recruitment is a key determinant of the tree species composition of the forest.Conclusion: It is then concluded that the method adopted for restoration encouraged species diversity in this successional forest among the aboveground trees species and undergrowth.
DBA_SSD ： A Novel End-to-End Object Detection Using Deep Attention Module for Helping Smart Device with Vegetable and Fruit Leaf Plant Disease Detection
Authors: Wang Jun , Yang Jing , Yu Liya , Dong Hao , Yun Kun , Wang Yifan 
Published: April 2021

Abstract
In response to the difficulty of detecting and classifying pests and vegetable and fruit leaves with pests and diseases, this study proposes a novel vegetable and fruit leaf pest detection method called deep block attention SSD (DBA_SSD) for the identification of pests and diseases and classification of the degree of pests and diseases of vegetable and fruit leaves. We propose three vegetable and fruit leaf pest detection methods, namely, squeeze-and excitation SSD (Se_SSD), DB_SSD, and DBA_SSD. Se_SSD fuses SSD feature extraction network and attention mechanism channel, DB_SSD improves VGG feature extraction network, and DBA_SSD fuses the improved VGG network and channel attention mechanism. To reduce the training time and accelerate the training process, the convolutional layers trained in the Image Net image dataset by the VGG model are migrated to this model, whereas the collected vegetable and fruit disease image dataset is randomly divided into training set, validation set, and test set in the ratio of 8:1:1. In addition, data enhancement methods, such as histogram equalization and horizontal flip were used to expand the image data. The performance of the three improved algorithms is compared and analyzed in the same environment and with the classical target detection algorithms YOLOv4, YOLOv3, Faster RCNN, and YOLOv4 tiny. Experiments show that DBA_SSD outperforms the two other improved algorithms, and its performance in comparative analysis is superior to other target detection algorithms.