bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ageing Resistance of Bi-Layer Coating Systems for Dry Lubrication of Premium OCTG Connections
Authors: Baska Philippe , François-Heude Alexandre , Millet Cécile , Thebault Florian 
Published: December 2021

Abstract
The latest dope-free configuration combines an electrodeposited zinc-nickel (ZnNi) plating, which provides anti-galling and most of anticorrosion properties, and an organic topcoat which provides lubrication through its low friction coefficient. This dry lubrication constitutes an alternative to storage and running dope meanwhile it improves running performances, reduces operational costs on the yard and rig and avoids dope discharge to the environment. Since the technology is "rig-ready", it must withstand the different risks of degradation occurring along its whole lifecycle. The present study aims at assessing the robustness towards ageing along storage on yards, transportation to the rig and or service life in well conditions.
The performances of the different layers were checked stepwise, first assessing the ZnNi plating alone, and then considering the additional protection brought by thermoset topcoat. Regarding atmospheric corrosion, the characterization path involved both accelerated laboratory tests (such as the VDA 233-102 cyclic corrosion test) and outdoor exposures, under plastic protectors and after their removal, in different climates: temperate, desertic and tropical. The specimens were inspected regarding at: (i) efficiency of cathodic protection provided by the metallic coating; (ii) paint blistering, (iii) propagation of corrosion from a scribe down to substrate. Regarding rig operations, some examples of rig-return were reported and the compatibility with completion fluids, encountered in case of misrun and subsequent pull-out of the column, was checked though immersion in alkaline brines. In respect to the service in simulated well conditions, the resistance to Stress Corrosion Cracking (SCC) in brines were carried out to complete the former autoclave tests to assess resistance of carbon and stainless steel to well conditions.
Both the ZnNi plating and the bi-layer system revealed lifetimes in storage conditions ranging from 3 to more than 5 years before any sign of significant degradation such as red rust, paint blistering or disbonding. According to cyclic corrosion tests results, higher lifetimes could be even expected thanks to the additional anticorrosion protection of the topcoat. Regarding exposure to completion fluids, the bilayer coating was shown to withstand 3000h exposure with no more than scarce rust indications. These results testify of the technology robustness from storage on yards to rig operations. In the multiple service conditions in wells, it was shown that the corrosion and cracking resistance of the substrate was not deteriorated by the plating presence, but instead improved in the multiple assessed well service conditions.
The present communication updates the results of atmospheric corrosion compared to the former one [1] and it details new results after rig-return and regarding the risks of cracking.
A Journey of People Development, Processes and Tools
Authors: Gomes Jorge Salgado , Merrill Robert Clifford , Sohail Shaheena 
Published: December 2021

Abstract

Objective/Scope
Abu Dhabi National Oil Company (ADNOC) places a priority on People Development. The reorganisation in 2016, a changing demographic, and increased emphasis on "Emiratisation" of the workforce has only reinforced that priority. The reorganisation fused together disparate companies, each with its own competency standards. The goal of ensuring that UAE national staff are used and developed throughout the organisation, coupled with our demographics, has added to the requirement for standard set of measures and processes for capability development across the ADNOC Group.
This initiative has been implemented in phases, beginning with the creation/unification of core technical, behavioral/leadership and business competencies for all subsurface disciplines across the Group. We are now creating a learning organization to address our remaining challenges. A joint effort is required between our human capital and technical discipline leaders.

Methods, Procedures, Process
The ADNOC Competency Frameworks were created through a joint effort between subject matter experts (SME) and the People Development Team. The deployment of these frameworks was done in two main steps:Creation and verification. This was a joint effort between our Human Capital organisation and domain experts from the operating companies. This deployment also saw the creation of discipline authorities for the subsurface organisation. These "Heads of Discipline" are domain experts with a focus on skills and staff development. A "self-assessment" + "manager verification" process was used to populate the competency framework database.Data analysis. A statistical subset of the data were independently verified by SME interviews. Anomalies, and disciplines with insufficient coverage were scrubbed from the data. A number of analytical tools were used for data analysis, including "Heat Maps" for visual impact.Results, Observations and ConclusionsThe results revealed strength in the "engine room" of the organization, however, some "gaps" were identified. One gap was identified in the transitional grades between the "junior" and "operational" staff. This was consistent for all disciplines, and it is being addressed through specialized training and on-the job work assignments. Another gap was identified in some specialties, in which ADNOC depends on one or two individuals for key skillsets.As we took immediate action to address some gaps, we recognised that a longer term solution was required. This has taken the form of the ADNOC Learning Institute (ALI). The ALI is a comprehensive solution which includes strategic workforce planning, future capabilities, competency and learning frameworks. These will underpin future efforts in technical succession planning and mobility.Novel AdditionsThe ADNOC Learning Institute was crafted to meet the competing challenges of skills development, demographics and Emiratisation. The ALI demonstrates how a unified vision is required to meet future challenges.
Accelerating Mature Field EOR Evaluation Using Machine Learning Uncertainty Workflows Integrating Subsurface And Economics
Authors: Bayerl Mathias , Neff Pascale , Clemens Torsten , Sieberer Martin , Stummer Barbara , Zamolyi Andras 
Published: December 2021

Abstract
Field re-development planning for tertiary recovery projects in mature fields traditionally involves a comprehensive subsurface evaluation circle, including static/dynamic modeling, scenario assessment and candidate selection based on economic models. The aforementioned sequential approach is time-consuming and includes the risk of delaying project maturation. This work introduces a novel approach which integrates subsurface geological and dynamic modeling as well as economics and uses machine learning augmented uncertainty workflows to achieve project acceleration.
In the elaborated enhanced oil recovery (EOR) evaluation process, a machine learning assisted approach is used in order to narrow geological and dynamic parameter ranges both for model initialization and subsequent history matching. The resulting posterior parameter distributions are used to create the input models for scenario evaluation under uncertainty. This scenario screening comprises not only an investigation of qualified EOR roll-out areas, but also includes detailed engineering such as well spacing optimization and pattern generation. Eventually, a fully stochastic economic evaluation approach is performed in order to rank and select scenarios for EOR implementation.
The presented workflow has been applied successfully for a mature oil field in Central/Eastern Europe with 60+ years of production history. It is shown that by using a fully stochastic approach, integrating subsurface engineering and economic evaluation, a considerable acceleration of up to 75% in project maturation time is achieved. Moreover, the applied workflow stands out due to its flexibility and adaptability based on changes in the project scope. In the course of this case study, a sector roll-out of chemical EOR is elaborated, including a proposal for 27 new well candidates and 17 well conversions, resulting in an incremental oil production of 4.7MM bbl.
The key findings were: A workflow is introduced that delivers a fully stochastic economic evaluation while honoring the input and measured data.The delivered scenarios are conditioned to the geological information and the production history in a Bayesian Framework to ensure full consistency of the selected subsurface model advanced to forecasting.The applied process results in substantial time reduction for an EOR re-development project evaluation cycle.
Artificial Intelligence for the Online Prediction of the Cool-down Time in a Subsea Pipeline After an Unplanned Shutdown
Authors: Gerri Alberto , Shokry Ahmed , Zio Enrico , Montini Marco 
Published: December 2021

Abstract
Hydrates formation in subsea pipelines is one of the main reliability concerns for flow assurance engineers. A fast and reliable assessment of the Cool-Down Time (CDT), the period between a shut-down event and possible hydrates formation in the asset, is of key importance for the safety of operations. Existing methods for the CDT prediction are highly dependent on the use of very complex physics-based models that demand large computational time, which hinders their usage in an online environment. Therefore, this work presents a novel methodology for the development of surrogate models that predict, in a fast and accurate way, the CDT in subsea pipelines after unplanned shutdowns. The proposed methodology is, innovatively, tailored on the basis of reliability perspective, by treating the CDT as a risk index, where a critic CDT threshold (i.e. the minimum time needed by the operator to preserve the line from hydrates formation) is considered to distinguish the simulation outputs into high-risk and low-risk domains.
The methodology relies on the development of a hybrid Machine Learning (ML) based model using datasets generated through complex physics-based model’ simulations. The hybrid ML-based model consists of a Support Vector Machine (SVM) classifier that assigns a risk level (high or low) to the measured operating condition of the asset, and two Artificial Neural Networks (ANNs) for predicting the CDT at the high-risk (low CDT) or the low-risk (high CDT) operating conditions previously assigned by the classifier.
The effectiveness of the proposed methodology is validated by its application to a case study involving a pipeline in an offshore western African asset, modelled by a transient physics-based commercial software. The results show outperformance of the capabilities of the proposed hybrid ML-based model (i.e., SVM + 2 ANNs) compared to the classical approach (i.e. modelling the entire system with one global ANN) in terms of enhancing the prediction of the CDT during the high-risk conditions of the asset.
This behaviour is confirmed applying the novel methodology to training datasets of different size. In fact, the high-risk Normalized Root Mean Square Error (NRMSE) is reduced on average of 15% compared to the NRMSE of a global ANN model. Moreover, it’s shown that high-risk CDT are better predicted by the hybrid model even if the critic CDT, which divides the simulation outputs in high-risk and low-risk values (i.e. the minimum time needed by the operator to preserve the line from hydrates formation), changes. The enhancement, in this case, is on average of 14.6%. Eventually, results show how the novel methodology cuts down by more than one hundred seventy-eight times the computational times for online CDT predictions compared to the physics-based model.
Association of Zoonotic Protozoan Parasites With Microplastics in Seawater: Implications for Human and Wildlife Health
Authors: Zhang Emma , Kim Minji , Rueda Lezlie , Rochman Chelsea , VanWormer Elizabeth , Moore James , Shapiro Karen 
Published: December 2021

Abstract
Plastics are widely recognized as a pervasive marine pollutant. Microplastics have been garnering increasing attention due to reports documenting their ingestion by animals, including those intended for human consumption. Their accumulation in the marine food chain may also pose a threat to wildlife that consume species that can accumulate microplastic particles. Microplastic contamination in marine ecosystems has thus raised concerns for both human and wildlife health. Our study addresses an unexplored area of research targeting the interaction between plastic and pathogen pollution of coastal waters. We investigated the association of the zoonotic protozoan parasites Toxoplasma gondii, Cryptosporidium parvum, and Giardia enterica with polyethylene microbeads and polyester microfibers. These pathogens were chosen because they have been recognized by the World Health Organization as underestimated causes of illness from shellfish consumption, and due to their persistence in the marine environment. We show that pathogens are capable of associating with microplastics in contaminated seawater, with more parasites adhering to microfiber surfaces as compared with microbeads. Given the global presence of microplastics in fish and shellfish, this study demonstrates a novel pathway by which anthropogenic pollutants may be mediating pathogen transmission in the marine environment, with important ramifications for wildlife and human health.
MLC-Seq: de novo Sequencing of Full-Length tRNAs and Quantitative Mapping of Multiple RNA Modifications
Authors: Zhang Shenglong , Yuan Xiaohong , Su Yue , Zhang Xudong , Turkel Spencer , Shi Shundi , Wang Xuanting , Choi Eun-Jin , Wu Wenzhe , Liu Haichuan , Viner Rosa , Russo James , Li Wenjia , Bao Xiaoyong , Chen Qi 
Published: December 2021

Abstract

Despite the extensive use of next-generation sequencing of RNA, simultaneous sequencing and quantitative mapping of multiple RNA modifications remain challenging. Herein, we develop MLC-Seq, a mass spectrometry-based direct sequencing method allowing for simultaneously unravelling the RNA sequences and quantitatively mapping different tRNA nucleotide modifications site-specifically. Importantly, MLC-Seq reveals the stoichiometric changes of tRNA modifications upon treatment with the dealkylating enzyme AlkB, and led to the discovery of new nucleotide modifications.
The Clinicopathological Features And Surgical Procedure of Adnexal Mass With Abdominal Pain In Pediatric And Adolescent Patients
Authors: Liu Qian , Zhou Huimei , Cao Dongyan , Yang Jiaxin , Shen Keng 
Published: December 2021

Abstract
Objective: To investigate the clinicopathological features and surgical procedures of adnexal masses with abdominal pain in pediatric and adolescent patients.Methods: A total of 212 pediatric and adolescent adnexal masses with abdominal pain who underwent surgery were retrospectively reviewed. The patients were divided into two groups, namely, the emergency surgery (EMS, n=96) group and the elective surgery (ELS, n=116) group, according to whether they had been surgically diagnosed with emergency conditions. EMS group refers to patients who had been surgically diagnosed with emergency conditions including adnexal masses torsion，corpus luteum rupture，and rupture of ectopic pregnancy. ELS group refers to patients with adnexal mass without emergency condition. The differences between the two groups were compared using the chi- squared test.Results: At the surgery evaluation, the median age was 14.5±3.6 years. A total of 175 patients (82.5%, 175/212) had menstruation, and 37 patients (17.5%, 37/212) had not yet begun menstruating. A total of 126 (59.4%, 126/212) patients presented with an abrupt onset of abdominal pain. Pelvic abdominal ultrasound was the first imaging modality used in all the patients (n = 212/212; 100%). Tumor markers were abnormally elevated in 26 patients.Compared with the ELS group, the proportion of patients with emergency onset of pain, pain duration less than 3 months, persistent and intense of pain were significantly higher than those in ELS group (P < 0.05). There were significantly more patients without menarche in the EMS group than in the ELS group (p<0.05). The average tumor size in the ELS group was larger than that in the EMS group (p<0.05). In the EMS group, 78 cases（ 81.3%,78/96）had adnexal mass torsion, 16 cases (16.7%，16/96) had mass rupture, and 2 cases (2.1%, 2/96）had ectopic pregnancy. Of the 78 patients with adnexal mass torsion, 49 cases (62.8%, 49/78）underwent ovary-preserving surgery, and 24 cases (30.8%，24/78）underwent adnexectomy. The most common pathologic types of adnexal torsion were mature teratoma cysts and simple cysts, accounting for 29% and 26%, respectively.Conclusions: Adnexal masses combined with abdominal pain in pediatric and adolescent patients, especially for patients presented as acute pain which characterized by emergency pain onset, persistent pain that cannot be relieved or recurrent pain，should be considered due to the possibility of adnexal mass combined with acute complications, and emergency surgery should be performed immediately. For patients with suspected malignant lesions, a comprehensive evaluation of the lesions should be conducted preoperatively to select the appropriate surgical method and strategy. After the discovery of an adnexal mass, evaluation should be performed quickly, and long-term management should be implemented.
The Identification and Analysis of a Novel Model Based on Ferroptosis-Related Genes for Predicting the Prognosis of Diffuse Large B-Cell Lymphomas
Authors: Wang Jiayi , Peng Hongling , Zhang Guangsen , Xu Yunxiao , Yan Wenzhe 
Published: December 2021

Abstract
Background
Diffuse large B-cell lymphomas (DLBCLs) are the most common B-cell lymphoma featured as phenotypically and genetically heterogeneous. Ferroptosis is a new found programmed cell death and have a crucial role in the chemoresistance of tumor. We aim to build a ferroptosis-related genes (FRGs) prognostic signature to predict the outcome of DLBCLs.
Methods
Our study retrospectively investigated the mRNA expression level and clinical data of 604 DLBCL patients from 3 GEO public datasets. A series of bioinformatic approaches including Cox regression analysis, function enrich analysis, immune infiltration analysis, ROC curve analysis, Kaplan–Meier survival curve and the least absolute shrinkage and selection operator (LASSO) method by the corresponding R packages in R statistical software were combined to explored the heterogenicity of FRG based clusters and to build prognostic model. Immunohistochemistry was used to exam the protein expression of six FRGs in different molecular type of DLBCL.
Results
We first identified 19 FRGs with potential prognostic values and classfied the patients into cluster 1 and cluster 2, Results indicated that cluster 1 tend to have a shorter overall survival (OS) time, while patients in the two clusters have different patterns of infiltrating immune cells among. Furthermore, the LASSO was used to generated a six-genes (GCLC, LPCAT3, NFE2L2, ABCC1, SLC1A5, and GOT1) risk signature which constructed a risk score formula and prognostic model for the OS of DLBCL patients. Kaplan–Meier survival analysis proved that poorer OS was exhibited in higher risk patients stratified by the prognostic model in both the training cohort and test cohort. In addition, we constructed nomograms to predict the OS of DLBCL patients. Both the decision curve(DCA) and the calibration plots showed that the nomogram had good agreement between predicted results and actual observation. Finally, the validation by immunohistochemistry indicated the GCLC, LPCAT3, ABCC1, SLC1A5, and GOT1 were high expressed in DLBCL with various prognostic adverse molecular factor.
Conclusion
In sum, we built a new FRG-based prognostic model which will help improve diagnosis and treatment for DLBCL patients.
Estimating the Public Health Impact from Introducing Tobacco-Free Nicotine Pouches Into the US
Authors: Lee Peter N , Fry John S , Ljung Tryggve 
Published: December 2021

Abstract
BackgroundFor smokers not intending to quit, switching to a reduced-risk nicotine product should be healthier than continuing smoking. We estimate the health impact, over the period 2000-2050, of introducing into the US the nicotine pouch ZYN. ZYN’s toxicant profile and method of use is like that for Swedish snus, a product with known health effects much less than smoking. MethodsOur modelling approach is similar to others developed for estimating potential effects of new tobacco products. It starts with a simulated cohort of 100,000 individuals in the year 2000 subdivided by age, sex, and smoking status (including years since quitting). They are followed annually accounting for births, net immigrations, deaths and product use changes, with follow-up carried out in the Base Case (ZYN not introduced) and Modified Case (ZYN introduced). Using informed assumptions about initiation, quitting and switching rates, distributions of the population over time are then constructed for each Case, which are used to estimate product-related mortality based on assumptions about the relative risk according to product use. ResultsWhereas in both Base and Modified Cases, the prevalence of any current product use is predicted to decline from about 22% to 10% during follow-up, in the Modified Case about 25% of current users use ZYN by 2050, about a quarter being dual users and the rest ZYN-only users. Over the 50 years, deaths at ages 35-84 from product use among the 100,000 are estimated as 249 less in the Modified than the Base Case, equivalent to about 700,000 less deaths in the whole US. Sensitivity analyses varying individual parameter values confirm the benefits of switching to ZYN, which increase as either the switching rate to ZYN increases or the initiation rate of ZYN relative to smoking increases. Even assuming the reduction in excess mortality risk using ZYN use is 20% of that from smoking rather than the 3.5% assumed in the main analyses, the reduction in product-related deaths would still be 213, or about 600,000 in the US. ConclusionsAlthough such model-based estimates are subject to uncertainties, the results suggest that introducing ZYN could substantially reduce smoking-attributable deaths.
Gut Parabacteroides merdae protects against cardiovascular damage by increasing commensal bacteria-driven branched-chain amino acid catabolism
Authors: Qiao Shanshan , Liu Chang , Sun Li , Wang Tao , Dai Huanqin , Kai Wang , Li Bao , Li Hantian , Liu Shuang-jiang , Liu Hongwei 
Published: December 2021

Abstract
Atherosclerosis is a chronic inflammatory disease of arteries featured with accumulated lipids, becoming the primary cause of cardiovascular diseases and death. Branched-chain amino acids (BCAAs) accumulation is defined as biomarkers of cardiometabolic diseases. Here, we revealed metabolic benefits of a previously reported gut microbiota-modulator (GMD) on atherosclerosis in ApoE−/− mice, and identify a gut symbiont Parabacteroides merdae-driven BCAA catabolism beneficial for the alleviation of atherosclerosis lesions. We also show that the porA gene responsible for the conversion of BCAAs into branched short-chain fatty acids is required for the in vivo efficacy of P. merdae. Furthermore, the down-regulation of BCAA-activated plaque mammalian target of rapamycin complex 1 (mTORC1) pathway is suggested as the mechanism underlying the benefits of P. merdae. Our results demonstrate the critical role of the commensal bacteria-driven BCAA catabolism in maintaining the host cardiovascular health and supporting the gut microbiota-targeted therapeutic strategy for cardiometabolic diseases.