bluuebunny/crossref_metadata_2025_split huggingface dataset:
Machine Learning Assisted Well Placement Optimization
Authors: Davudov Davud , Venkatraman Ashwin , Mabadeje Ademide O. , Malkov Anton , Singh Gurpreet , Dindoruk Birol , Al-Aulaqi Talal 
Published: May 2023

Abstract
Well placement optimization is a complicated problem which is usually solved by direct combination of reservoir simulators with optimization algorithm. However, depending on complexity of the reservoir model studied, thousands of simulations is usually needed for accurate and reliable results. In this research, we present a novel approach – machine learning (ML) assisted proxy model that combines reservoir simulations and reduced physics model to reduce computational cost.
In the proposed model framework, first several (depending on the complexity of the problem) uniformly distributed random coordinates are selected. These chosen coordinates are considered as data points for ML model. For the chosen coordinates (training set) reservoir simulations are executed and NPV/recovery values are calculated (target variable). Spatial locations as well as petrophysical properties of the same coordinates extracted from simulation model are also used as an input to the ML model. ML model is further improved by combining with Fast Marching Model (FMM) which is a robust reduced physics model. The inclusion of FMM helps identify drainage volume for producers and hence enhance model training. Finally, the trained ML model is coupled with stochastic optimization algorithms to determine infill well location with highest NPV/recovery.
Using an example field data, we present two specific cases of using proposed model: a) for greenfield with a single new well, b) for greenfield with multiple new wells. Results indicate that developed ML model can predict NPV with around 96% accuracy (testing score). This gives great confidence in predictions from the trained hybrid model that can be used as a proxy model for reservoir simulations. Coupling the trained hybrid model with Particle Swarm Optimization (PSO), the location of the new producers with maximum NPV are determined. The results are further confirmed with an exhaustive search from all potential locations.
A novel approach is presented to show how traditional physics-based approaches can be combined with machine learning algorithms to optimize well placement. Such approaches can be integrated in current greenfield and brownfield reservoir engineering workflow to drastically reduce decision making times.
Experimental Study: Investigating the Anions and Cations’ Effects on the Elasticity of the Anionic and Cationic High Viscosity Friction Reducers
Authors: Ge Xiaojing , Biheri Ghith , Imqam Abdulmohsin , Bai Baojun , Zhang Yuwei 
Published: May 2023

Abstract
High viscosity friction reducers (HVFRs) are widely used as friction-reducing agents and proppant carriers during hydraulic fracturing. The reuse of produced water has gained popularity due to environmental and economic benefits. Currently, the field’s most commonly used friction reducers are anionic and cationic HVFRs. Anionic HVFRs are typically pumped with freshwater, while cationic HVFRs are used with high Total Dissolved Solids (TDS) produced water. Cationic friction reducers are believed to have better TDS tolerance, friction reduction performance, and proppant transport capabilities compared to anionic friction reducers under high TDS conditions due to their superior viscoelastic properties. In addition, the impact of different anions and cations on the viscosity of HVFRs has been thoroughly studied, and viscosity reduction mechanisms include charge shielding, increasing the degree of hydrolysis, and forming coordination complexes. However, anions and cations’ effects on the elasticity of HVFRs still remain to be investigated. Besides, most previous experimental studies either do not specify experimental procedures or control the experimental variables well. Therefore, the ultimate objective of this experimental study is to analyze various cations and anions’ effects on the elasticity of anionic and cationic HVFRs comparably and precisely with experimental variables well controlled. Two hypotheses based on anions and cations’ effects on the viscosity of HVFRs are proposed and will be tested in this study. First, the elasticity reduction of anionic HVFRs is mainly due to cations, whereas the elasticity reduction of cationic HVFRs is mainly due to anions. Second, the salts’ effects on the elasticity reduction of HVFRs should follow the same trend as the salts’ effects on the viscosity reduction of HVFRs. For anionic HVFRs, monovalent Alkali metals should have a similar effect; divalent Alkaline earth metals should have a similar effect; transition metals should have the most severe effect. For cationic HVFRs, SO42- should have more pronounced effects than Cl-. To demonstrate both hypotheses, an anionic and a cationic HVFR at 4 gallons per thousand gallons (GPT) were selected and analyzed. The elasticity measurements of both anionic and cationic HVFRs were conducted with deionized (DI) water and various salts respectively. Fe3+ and H+ (or pH) effects were specifically investigated. The results showed both hypotheses were accepted.
Evaluating Oil Quality and Microbial Activity Across Fault Blocks and Subunits of the Ugnu (N. Slope, Alaska) by Volatiles Analysis of Cuttings and Produced Crude - Implications for Completions and Production
Authors: Smith Christopher M , Nolan Seth , Edwards Reid , Conrad Caleb , Gordon Patrick S , Smith Timothy M , Smith Michael P 
Published: May 2023

Abstract
Hilcorp's Milne Point S-203 was drilled in 2019 targeting the biodegraded heavy oil of the Ugnu Formation, for exploration and development; being one of the first Ugnu wells to be successfully drilled, completed, and conventionally produced. S-203 crossed three fault blocks and intersected multiple Ugnu subunits. A volatiles analysis, via rock volatiles stratigraphy (RVS), of the cuttings from the main borehole and sidetracks enabled a spatial assessment of oil quantity, microbial activity, and the effect of faults in the different subunits. Produced oil from early in the life cycle of the well was analyzed with RVS, both RVS datasets were combined with completions to assess production contribution across the borehole. These results provide important insights for development of the Ugnu as a heavy oil play on the Alaskan North Slope.
A tool for assessing sexual knowledge of people with Intellectual disabilities in Norway
Authors: Svae Gøril Brevik , Zachariassen Peter , Fjeld Wenche , Søndenaa Erik 
Published: May 2023

Abstract
Background: Previous research has shown that people with intellectual disabilities have limited sexual knowledge, which can be essential for developing positive sexuality. This study aimed to check the validity and reliability of an assessment tool (SexKunn) for measuring the sexual knowledge of people with intellectual disabilities in Norway. Further, we aimed to identify potential knowledge gaps among the participants and highlight their potential impact.
Methods: 37 people with intellectual disabilities completed one assessment. 20 participants then completed a retest. Clinicians’ (n=23) views on the assessment tool were measured to obtain face validity.
Results: A weighted Cohen’s kappa for the test and retest of the overall scores was considered to be substantial. The clinicians described an acceptable face validity regarding high positive value scores and low negative burden scores. They also suggested improvements. The study identified that the participants lacked knowledge about female genitals, hygiene, appropriate touching/sexual acts with friends/ intimate partners, and contraception.
Conclusions: The SexKunn is a feasible assessment tool to measure sexual knowledge in people with intellectual disabilities. A lack of sexual knowledge of people with intellectual disabilities may violate their sexual rights.
Willingness to vaccinate against COVID-19: The impact of national identity and the nature of propaganda
Authors: Zhou Shuang-Zhu , Wu Chen-Yang , GUO Yu-Huan , Bai Xue , Tang Ri-Xin 
Published: May 2023

Abstract
Objective: Fighting the COVID-19 pandemic requires many citizens to adopt disease-preventive practices. To enhance citizens' vaccination willingness, we explored the impact of national identity and different propaganda slogans on vaccination willingness.
Methods: A total of 1098 questionnaires were collected in Study 1, and all participants completed the national identity questionnaire, knowledge of vaccine side effects, vaccine trust, and vaccination willingness. The initial vaccination willingness of the participants (N=804) was measured in Study 2. All participants were then randomly divided into three groups: self-interested, altruistic, and neutral; each group watched the corresponding propaganda video. Each video, which lasted about 11 seconds, consisted of five self-interested, altruistic, or neutral propaganda slogans. Vaccination willingness was then measured again.
Results: 1. National identity can significantly predict vaccination willingness in the presence of side effects. 2. The effect of altruistic propaganda slogans on promoting individual vaccination willingness was significantly greater than that of the self-interested propaganda slogan, and the effect of altruistic propaganda slogans on individual vaccination willingness was significantly greater than that of neutral propaganda slogans.
Conclusions: National identity, knowledge of vaccine side effects, and vaccine trust can jointly predict individual vaccination willingness in cases of strong national identity. Altruistic slogans have the greatest influence on the change in individuals’ vaccination willingness, and the influence of altruistic propaganda slogans can significantly improve individual vaccination willingness.
Sleep quality of undergraduates in Fujian and its influencing factors : a cross-sectional study
Authors: Liu Fuzhi , Zhu Dandan , Deng Lifeng , Zhao Yanyan , Chen Yangjia , Tu Zhuote 
Published: May 2023

Abstract
Purpose:This study aims to investigate the sleep quality of college students and explore the factors influencing it. Furthermore, it seeks to determine an effective intervention that can enhance the quality of student sleep.
Patients and methods:The quality of sleep was assessed through the use of the Pittsburgh Sleep Quality Index (PSQI) questionnaire, and the General Survey Questionnaire was also utilized. The research was conducted through an online survey administered on the Wenjuanxing platform.
Results:A total of 971 valid questionnaires were recovered. The mean total PSQI score was 4.52 ± 3.17. A total of 310 students had sleep disorders, and the detection rate was 32.0%. Significant differences exist in sleep quality in different ages, genders, educational levels and majors. College students (<20 years) had significantly higher sleep duration and total PSQI score than college students (> years). However, students (<20 years) had significantly fewer sleep disturbances than students (>20 years). According to the research findings, there were notable differences between males and females in terms of sleep patterns. Females experienced more sleep disturbance and had higher total PSQI scores, while males tended to sleep duration. Interestingly, the junior college participants showed significantly higher levels of sleep latency and daytime dysfunction compared to the undergraduate and postgraduate students.Medical students experienced significantly longer sleep latency and daytime dysfunction when compared to non-medical students. In contrast, medical educations than non-medical students.The multivariate logistic regression analysis showed that smoking(OR=1.932),electronic products addiction(OR=2.918), personal history of acute illness(OR=2.238)were identified as independent risk factors.In turn, level of education (OR=0.606) and parents without sleep problems (OR=0.500)were protective factors.
Conclusion:College students in Fujian have some sleep problems.We should pay attention to the relationship between smoking,electronic products addiction, personal history of acute illness and sleep quality.Health policymakers should consider these factors in improving college students, sleep quality.
Charge-induced ultralow friction
Authors: Cammarata Antonio , Polcar Tomas , Liao Mengzhou 
Published: May 2023

Abstract
Reaching near-zero friction is one of the jewels on the crown of tribology, and structural lubricity is a crucial mechanism to achieve it. Previous works focus mainly on the structural lubricity at incommensurate crystalline interfaces. However, realizing such interfaces on a large scale without defects and contaminations is a formidable challenge. Here, we report a charge-induced robust macroscale superlubricity between single crystal graphite and atomically flat surfaces in the ambient condition. We transferred single crystal graphite flakes on Si3N4 balls and used them to measure the friction properties on pristine and charged atomically flat surfaces such as 300 nm SiO2/Si and sapphire. We found that the surface charge can dramatically reduce the coefficient of friction between graphite and substrates by two orders of magnitude to 10-4, and the sliding is wearless even under harsh contact conditions (~ 1.1 GPa center pressure and > 100 m). We demonstrate that the surface charge is critical in achieving superlubricity because it can reduce adhesion between graphite and substrate surfaces and make the substrate surfaces resistant to contaminations. Our method offers a ready-to-use solution to superlubricity alternative to achieve incommensurate crystalline interfaces. Thus, it can reduce the difficulty of realizing macroscale superlubricity for applications.
A Scoping Review of Machine Learning in Dental Radiography: Its Current Applications and Relevance in Dentistry
Authors: Shamaun Mizaan , Field James 
Published: May 2023

Abstract
Background
Artificial Intelligence (AI) has rapidly developed over the past decade, with seamless integrations across many industries. In a world where healthcare is more crucial than ever, AI can assist clinicians in identifying and diagnosing dental-related anatomy and pathology.
Aims
Explain the current AI model designs utilised in dental radiography, map out the emergent themes in the current literature and comment on AI model accuracy in radiographic object recognition and interpretation.
Methods
Using four databases (PubMed, Web of Science, Scopus and EBSCOHost), a search strategy was employed to identify relevant published literature from January 2012 - September 2022. The Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool was used to assess the experimental validity of each study included in this review. For each study included, the data extracted included study source, image type, dataset number, AI architecture, data pre-processing, train/validation/test data split and model performance values.
Results
18 studies were included in the Discussion spanning four different categories including dental and maxillofacial radiology, orthodontics, periodontology, and restorative dentistry.
Conclusions
AI models as demonstrated in this study can identify dental-skeletal landmarks with reasonable accuracy and can be applied in numerous restorative dentistry contexts.
An Empirical Study of the Deep Gradient Network Model to Perform Efficient Packet Classification
Authors: Yazhini K , Umarani B 
Published: May 2023

Abstract
The fast expansion of the Internet has increased the significance of packet classification in a network environment. The classification of the packets was done using various centred-on data structure techniques. However, the current algorithms have an issue with time budget and can't handle big rule sets. The main challenge is creating a packet classification algorithm that adds processing overhead and can handle enormous sets of classification rules. The proposed deep gradient network model (DGN) fixes these difficult problems. The anticipated model assists in handling complex tasks with higher prediction accuracy. The network adopts the dense network modelling concept to measure the feature representation and performs the classification process to fulfil prediction accuracy. The model works well compared to other approaches where the analysis is done with the standard benchmark ACL and evaluation is done with k-NN, SVM and DNN. Based on the outcomes, it is proven that the model establishes a better trade-off compared to other approaches.
A radiomics nomogram based on 18F-FDG PET/CT and clinical risk factors for the Prediction of Peritoneal Metastasis in Gastric Cancer
Authors: Xie Jiageng , Xue Beihui , Bian Shuying , Ji Xiaowei , Lin Jie , Zheng Xiangwu , Tang Kun 
Published: May 2023

Abstract
Purpose Peritoneal metastasis (PM) is usually considered an incurable factor of gastric cancer (GC) and not fit for surgery. The patients may miss the time window of chemotherapy if they were diagnosed PM positive after the gastrectomy. Accurate preoperative prediction of PM in GC patients is vital for prognosis and treatment decisions making. The aim of this study is to develop and validate a 18F-FDG PET/CT derived radiomics model combining with clinical risk factors for predicting PM of GC.Method In this retrospective study, 410 GC patients (PM - = 281, PM + = 129) who underwent preoperative 18F-FDG PET/CT images from January 2015 to October 2021 were analyzed. The patients were randomly divided into a training cohort (n = 288) and a validation cohort (n = 122). The maximum relevance and minimum redundancy (mRMR) and the least shrinkage and selection operator (LASSO) method were applied to select feature. Multivariable logistic regression analysis was preformed to develop the predicting model. Discrimination, calibration, and clinical usefulness were used to evaluate the performance of the nomogram both in training and validation cohort.Result Fourteen radiomics feature parameters were selected to construct radiomics model. The Area Under Curve (AUC) of the radiomics model were 0.86 (95% confidence interval (CI), 0.81–0.90) in the training cohort and 0.85 (95%CI, 0.78–0.92) in the validation cohort. After multivariable logistic regression, peritoneal effusion, mean standardized uptake value (SUVmean), carbohydrate antigen 125 (CA125) and radiomics signature showed statistically significant differences between different PM status patients(P < 0.05). They were chosen to construct the comprehensive predicting model which showed a performance with an AUC of 0.92 (95%CI, 0.89–0.95) in the training cohort and 0.92 (95%CI, 0.86–0.98) in the validation cohort, respectively.Conclusion The nomogram based on 18F-FDG PET/CT radiomics features and clinical risk factors can be potentially applied in individualized treatment strategy making for gastric cancer patients before the surgery.
Assessment of Oral health related quality of life and its associated factors in head and neck cancer survivors, within one-year, post cancer treatment. A cross-sectional study
Authors: Farrukh Sana , Rozi Shafquat , Sawani Sobia , Khan Farhan Raza , Awan Muhammad Sohail , Akhtar Shabbir , Siddiqui Moghira Iqbaluddin , Abbas Syed Akbar , Taimoor Shazia 
Published: May 2023

Abstract
Background Patients after completing their treatment for HNC, are often functionally challenged by the acute and chronic complications in the oral cavity such as oral pain, limited mouth opening, xerostomia etc. These complications are known to reduce their OHRQoL, because of restricted food intake, limited social activity and economic growth, therefore impacting their overall well-being and survival. This study aims to assess the OHRQoL and its associated sociodemographic factors, oral hygiene related factors and oral clinical parameters such as OH status and OM grade in HNC survivors within one-year post cancer treatment.Methodology This was a cross-sectional study performed among HNC survivors at the ENT and dental clinics of Aga Khan University Hospital, Karachi. OHRQoL was assessed using EORTC QLQ H&N – 35, patients were examined for oral hygiene status using OHI- simplified and oral mucositis grade using WHO oral mucositis scale at one point in time. One sample t- test and multiple linear regression was used to test OHRQoL and its associations with the sociodemographic and clinical factors.Results The results of the study showed an overall higher mean score for OHRQoL of 25.02 ± 15.86 (95% CI 21.46–28.57), with difficulty in mouth opening and dry mouth because of salivary dysfunction among the most affected domains with higher symptoms scores in the study population. Significant association of OHRQoL were found with BMI, OH status, marital status, monthly income, gender and fluoride toothpaste use in HNC patients within one-year post cancer treatment (p < 0.05).Conclusion: High mean score for OHRQoL in HNC patients suggests their QoL is negatively impacted by their poor oral health post cancer treatment, therefore it is important to evaluate and modify the current treatment modalities and involve multidisciplinary teams, to improve their OHRQoL thereby enhancing overall QoL.
School-based Comprehensive Sexuality Education for Prevention of Adolescent Pregnancy: A Scoping Review
Authors: Myat Su Mon , Pattanittum Porjai , Sothornwit Jen , Ngamjarus Chetta , Rattanakanokchai Siwanon , Show Kyaw Lwin , Jampathong Nampet , Lumbiganon Pisake 
Published: May 2023

Abstract
Background Adolescent pregnancy is a global public health problem. Comprehensive Sexuality Education (CSE) aims at increasing contraceptive use to prevent adolescent pregnancy. Numerous approaches for CSE delivery in schools have been implemented around the world. Previous reviews did not follow the International Technical Guidance on Sexuality Education (ITGSE) and because this subject is very diverse in terms of population, interventions, settings and outcomes. We conducted this scoping review to identify and map the evidence of school-based CSE for prevention of adolescent pregnancy with emphasizing on adolescents’ contraceptive use, unintended pregnancy and abortion.Methods We searched PubMed, CENTRAL, Scopus, ISI Web of Science, CINAHL, and WHO ICTRP to identify potential eligible studies from their inception to 12th May 2022. We included randomized controlled trials (RCTs) and non-RCTs of CSE implemented in public or private schools for adolescents. CSE was defined as a multi-session intervention in school that covered topics including contraception, pregnancy, abortion, and HIV/STI. School-based interventions were the main intervention that may be either stand-alone or multicomponent. There was no limitation on study’s geographical area, but only English-language studies were considered. Two reviewers selected and extracted data independently, discussed for consensus or consulted the third reviewer if there are discrepancies for final conclusion. Data were presented using figures, map and table.Results Out of 5,342 records, 75 studies (97 reports) were included in this review. Most studies were conducted in the United States and other high-income countries in secondary or high schools with cluster RCTs. All studies included participatory methods. Almost all studies included Sexual and Reproductive Health which is the eighth concept of CSE. The number of concepts, duration and providers varied across the included studies. However, none of the interventions identified in this scoping review adhered to the ITGSE recommended approach. Condom use was the most common reported outcome.Conclusions Our scoping review shows gaps in school-based CSE implementation in terms of completeness of concepts, providers, duration and outcomes recommended by ITGSE.