bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Ontology of Well Engineering Entities to Extract and Structure Text Data from Daily Reports
Authors: Queiroz J. , Jaculli M. A. , Choueri Junior N. , Silveira I. M. , Mendes J. R. P. , Penteado B. E. , Guilherme I. R. , Perrout S. R. 
Published: February 2025

Summary
Oil and gas activities generate, inevitably, huge amounts of data, especially in the form of Daily Operational Reports during construction and production activities. Extracting information from these reports can be achieved using embeddings combined with Large Language Models (LLMs), with domain knowledge being mandatory for this extracted information to be meaningful and properly presented to end-users. A solution for this challenge is the use of Knowledge Graphs (KG) to organize and relate all the information in a way that properly represents the concepts (e.g., entities, events, and processes) of the specific domain. A KG can address the lack of domain knowledge presented by LLMs, as well as enhance the semantics of embedding-based indexes such as those provided by Transformers, but also as a searching source itself that enables to take advantage of the information relationships (i.e., the natural links between entities or pieces of data). However, the creation of a KG from a specific domain based on unstructured data sources requires not only an ontology to describe the entities and their relationships but also strategies and tools capable of properly extracting and mapping them from the data sources to a KG. In this context, this work proposes a well engineering ontology to guide extracting information from Daily Operational Reports, structure them into KGs, and support information retrieval applications. To assure interoperability, the development of the proposed ontology is aligned with upper-level ontologies and industrial standards like ISO 15926. The results of this work include not only the ontology itself and the procedure followed to build it, but also a discussion of further applications that can be developed using it as a basis. The main applications resulting from this work are named entity recognition, visualization of incidents, classification of operations, templates and auto-filling of reports, calculation of drilling metrics, and queries within the reports database. We have noticed that having structured domain knowledge, in the form of an ontology and KG has improved the success of these applications compared to raw text processing. Finally, this work emphasizes the importance of domain knowledge in the form of a comprehensive ontology that focuses on the relevant entities of the application domain and enables the creation of KGs that can facilitate the organization and query of complex unstructured text information and enhance data analysis and LLM-based applications in the Oil&Gas domain.
Optimizing Operational Processes and Reducing Equipment Failure Through a Real Time Alerting Platform
Authors: Martinez S. , Godumagadda A. , Pandey B. , Malliganuru N. 
Published: February 2025

Abstract
The ability to monitor data in real time has become increasingly important as the industry continues digitalization efforts. Over the past several years this contractor has upgraded the capabilities of a real time monitoring system that has been providing value through improved operational efficiency and visibility of operations across its onshore fleet. These updates open a wide set of alerting opportunities that were previously not possible by distributing the alerting system to local, rig-based devices. An overview of the technology and architecture necessary to make this system possible, as well as the impact on performance will be discussed.
This contractor's efforts have focused on converting the system from a cloud-based system to an edge-based system, with all computations and alerts issued at the rig location. The architecture comprises migrating cloud applications to run on the edge and leveraging edge hardware and rig historians to enable alerting on all data available at the rig location. Streamlining and synchronizing the rules/alert definitions and notifying users instantly using cloud infrastructure is a novel implementation. Housed within the edge platform, the system can operate on batches of data in real time without being held back by cloud computing related latency.
Preexisting infrastructure made it possible to receive exception-based alerting within 15 minutes of an event occurring. With the new implementation running on the edge, it is possible to receive alerts to the user's phone, email and/or web-based dashboard within a minute. Leveraging increased real-time monitoring capabilities, this contractor has been able to reduce the amount of premature equipment failures as well as improve drilling connection operations. These successes have resulted in a reduction in capital spend and improved spud to release times. The above will be reviewed in detail.
This change in data architecture from a cloud-based to a distributed rig-based computing system provides a more efficient way to trigger alerts and opens the possibility of generating alerts locally at the driller's console. Previously, the cloud-based alerting system only had access to data streamed off-location, providing limited insight into equipment health and drilling conditions. As a result of this update, we can provide end users with alert notifications containing detailed messages and specific data from a wide range of local data sources, including thousands of equipment-related data feeds, downhole data, complex artificial intelligence(AI)/machine learning(ML) model outputs, and drilling performance metrics which were not previously synchronized into a system that allowed alerts to be generated across this entire dataset. Quicker computing and notification delivery times will pave the way for well control, drilling dysfunction and more sophisticated equipment health alerts on the driller's console in real time.
Breaking the Mold: Rethinking Liner Cementing Practices in Ecuador
Authors: Pleshkov D. , Taylor A. , Mora K. , Ordonez M. , Carrillo R. 
Published: February 2025

Abstract
This paper discusses the transformation of liner cementing practices in Ecuador and the elimination of recurring packoff behavior through the enhancement of wellbore cleanout, cementing fluids and pumping schedule optimization, liner hanger technical specifications, and centralizer type selection and placement. It also discusses the risk and potential severity of high circulating pressure during cementing operations, as well as the impact of high circulating pressure on packoff behavior.
This paper presents the results of a comprehensive well cementing improvement project conducted on 60 wells. The project began with a 20-well pilot phase, during which several enhancements were identified and tested. Following the successful pilot, these improvements were applied to an additional 40 wells, yielding consistently positive outcomes. This study aims to detail the methodologies, results, and implications of these improvements for future well cementing operations.
The success of this project highlights the importance of continuous improvement and innovation in well cementing practices. The identified improvements not only enhance the quality and reliability of cement jobs but also contribute to overall operational efficiency. Future work will focus on further refining these techniques and exploring their applicability in different fields across Ecuador.
As a result of this extensive project, liner cementing practices in Ecuador have changed with respect to wellbore cleanout, the fluids used, liner hanger technical specifications, and centralizer type selection and placement. The number of severe packoff events that typically had led to remediation work has been reduced to zero.
Federated Learning for Drilling Data Integration: A Collaborative Framework with Application to LWD Lag Correction
Authors: Liu Ye , Zhang Nan , Rong Chunming , Cao Jie 
Published: February 2025

Abstract
Data-driven AI (artificial intelligence) models have become instrumental in drilling operations, offering potential efficiency gains through real-time predictions and decision support. However, while access to diverse datasets from different fields and companies can significantly enhance model performance, data sharing is often constrained by strict data security and privacy regulations. To overcome these challenges, we developed a federated learning framework that enables collaborative model training across decentralized datasets without compromising data confidentiality. This research presents an FL (federated learning)-based architecture specifically applied to address the lag in logging while drilling (LWD) data, where physical separation between LWD tools and the drill bit introduces delays in real-time formation information. Our FL framework employs multi-party secure aggregation, allowing each participating oil field to train models locally and share only encrypted model updates, which are then aggregated to create a global model. This approach not only preserves data privacy but also enhances model generalization by leveraging diverse data from multiple fields with varying geological and operational characteristics. In this study, we validate the FL framework through a case study involving three oil fields with heterogeneous datasets, each with unique feature characteristics and geological conditions. Results indicate that the FL-based model significantly improves predictive accuracy compared to independently trained models, reducing mean absolute error from 54.58 to 1.39 in the Volve field, from 27.11 to 2.49 in Bohai oilfield (BH), and from 40.91 to 3.88 in Xinjiang oilfield (XJ). These improvements demonstrate FL's ability to produce robust, generalizable models for drilling applications, offering a scalable and secure solution for cross-field collaboration in the petroleum industry. This study establishes a foundation for future applications of FL in addressing complex, data-intensive challenges in oil and gas operations.
Multistring Analysis of a Mudline Hanger System in High-Temperature Wells During Production
Authors: Sathuvalli Udaya B. , Suryanarayana P. V. R. , Bathgate Grant , Delgado Johan , Arcos Renato , Painter Jay , Rahman Shaikh 
Published: February 2025

Summary
We present a semi-analytical method to analyze the multistring response of tubulars in offshore wells with a mudline suspension system (MLS). Though the governing equations are linear, structural redundancies at the mudline hangers (MLH) require a one-step iterative solution. The iteration ensures that the final response of the MLS and the tubulars is consistent with restrictions at the wellhead and mudline. Our method is computationally simple and can be implemented in a spreadsheet.
We apply the method to an offshore well with six strings, four of which are suspended at the mudline. The hangers at the mudline are arranged such that a suspended string transfers its weight to the next outer string. Furthermore, the MLS hardware is such that a lifted-off string raises its immediate inner neighbor. In the model, the tubulars are regarded as elastic springs, and the load transfer pathways at the MLH shoulders are represented by displacement constraints. The length changes created by pressure and temperature changes during well operations are combined with the installed conditions to determine the contact force at the MLH.
The model shows that the net movement at the surface and the forces on the structural members depend on the installed condition, the preload in the casing strings, and annular pressures at the surface wellhead. Furthermore, the reduction of annular pressures significantly reduces the force on the conductor slip lock in the wellhead. Cold injection creates a net downward force at critical locations in the MLS. Finally, the model was used to show that the net downward force did not exceed the design capacity of the MLS hardware and to define annulus pressure management procedures to maintain well integrity.
Sex, Age, and Urban Context: Modeling Social and Demographic Drivers of Mumps Transmission in Chengdu, China (2008–2019)
Authors: Yang Tianlong , Du Xunbo , Li Junfan , Long Lu , Xie Li , Wang Yao , Wang Liang 
Published: February 2025

Abstract

Objectives
This study investigates mumps epidemiology in Chengdu (2008–2019), focusing on sex and age-specific transmission characteristics.
Methods
A sex- and age-specific Susceptible – Exposed – Pre-symptomatic – Symptomatic Infected – Asymptomatic Infected – Recovered (SEPIAR) model, adjusted for seasonal variations, was employed to categorize the population and analyze transmission dynamics.
Results
Over the study period, 40,087 mumps cases were reported in Chengdu, with an annual incidence of 21.72 per 100,000, peaking in 2011 at 40.83 per 100,000. Incidence rates were highest among male students aged 5–14, with significant seasonal peaks in May-July and November-December. District-wise, Wenjiang and Jinniu had the highest rates (45.45 and 43.25 per 100,000), while Jianyang city had the lowest (3.26 per 100,000). The SEPIAR model demonstrated robust fitting across demographics (R² = 0.13–0.73, P < 0.001). Notably, females aged 10–14 exhibited the highest transmission risk to males aged 0–14, with all mean time-varying reproduction numbers (Rt) exceeding 1. The median Rt for females aged 10–14 to males aged 5–9 was 1.18, to males aged 0–4 was 0.75, and within the same age group was 0.55.
Conclusions
This study underscores the critical role of sex and age in mumps transmission and validates the utility of the SEPIAR model for outbreak analysis. To mitigate transmission, we recommend: 1) targeted vaccination campaigns during seasonal peaks, 2) prioritizing booster doses for females aged 10–14, 3) strengthening surveillance in high-incidence districts, and 4) improving healthcare reporting in rural regions. These strategies are vital for achieving sustained mumps control in megacities.
Report on the Symposium "30 Years After “Veritatis Splendor.” Moral Absolutes and War – War on Moral Absolutes," Cardinal Stefan Wyszynski University in Warsaw, December 13, 2023
Authors: Cebula Adam 
Published: February 2025

The 2023 symposium at the Cardinal Stefan Wyszynski University focused on Christian ethics, revisiting key themes from Pope John Paul II’s encyclical Veritatis Splendor. The discussion highlighted the enduring relevance of absolute moral norms and examined shifts in the Catholic Church’s stance on capital punishment and killing in war, emphasizing the significance of intention and the object of a moral act in moral reasoning. The event also addressed Catholic perspectives on war ethics, contrasting the just war doctrine with pacifist views. Additional topics included the idea of the indissolubility of marriage amid contemporary societal changes and the idea of moral autonomy, understood as the central point of contention between Kantian ethics and the Church’s traditional moral doctrine.
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Received: 30/10/2024. Reviewed: 5/12/2024. Accepted: 12/12/2024.
Therapeutic Effect of Rosolic Acid against Endothelial Dysfunction in Diabetic Wistar Rats
Authors: Amin Karan Naresh , Ramkumar Kunka Mohanram 
Published: February 2025

Introduction:
Endothelial dysfunction (ED) results from impaired vascular
endothelial cell function, disrupting key processes such as hemostasis, vascular tone regulation,
vasculogenesis, angiogenesis, and inflammation. These processes are mediated
by a complex signaling network involving hormones, cytokines, and chemokines. ED is
recognized as a major contributor to the onset and progression of several micro- and
macrovascular diseases, including diabetes. Our previous study demonstrated that the polyphenol
Rosolic acid (RA) protects against ER stress-induced ED in vitro by activating
nuclear factor erythroid 2-related factor 2 (Nrf2). Additionally, RA enhanced the proliferation
and survival of pancreatic β-cells in a co-culture model with endothelial cells under
ER stress conditions.

Methods:
In this study, we investigated RA's protective effects against diabetes-induced
ED using high-fat diet (HFD)-fed and streptozotocin-induced type-2 diabetic rat models.
We evaluated RA’s impact on vascular function and metabolic parameters in these models.

objective:
To evaluate the protective effects of Rosolic acid (RA) on endothelial dysfunction (ED) in high-fat diet (HFD)-fed and streptozotocin-induced type-2 diabetic rat models.

To assess the impact of RA on vascular function in diabetic rats by analyzing key markers of endothelial dysfunction, including ICAM-1, VCAM-1, and Endothelin-1.

To investigate the effects of RA on metabolic parameters, such as glucose tolerance and lipid profiles, in diabetic conditions.

To examine the role of RA in modulating Nrf2 and its downstream target genes involved in oxidative stress and endothelial function in aortic tissues.

To compare the therapeutic efficacy of RA with the standard anti-diabetic drug Gliclazide in protecting against diabetes-induced endothelial dysfunction.

Results:
RA significantly mitigated diabetes-induced ED in the aortic tissues of HFDfed
diabetic Wistar rats. RA treatment improved glucose tolerance and reduced hyperlipidemia,
showing efficacy comparable to the anti-diabetic drug Gliclazide. Moreover, RA
elevated Nrf2 levels and its downstream target genes in aortic tissues while reducing ED
markers such as ICAM-1, VCAM-1, and endothelin-1.

Conclusion:
These findings highlight RA as a promising therapeutic agent for diabetes
and its associated vascular complications, with potential for broader clinical applications.
Unfurling the Potential of Antiviral Agents Aimed for RNA Virus Ailment
Authors: Babbar Ritchu , Kaur Jasmine , Kaur Kajalpreet , Swikriti  , Vagh Vijay Dhondiram , Sachdeva Monika , Behl Tapan , Gulati Monica , Gasmi Amin 
Published: February 2025

Abstract:
Globally, high mortality is brought on by RNA viruses, which are linked to chronic human
disorders. Viruses dominate the WHO's current ranking of the top 10 global health hazards,
especially RNA viruses. RNA viruses, like HIV, SARS-CoV-2, and influenza, which are among
the most prevalent and frequently encountered RNA viruses, use RNA as their genetic material,
making them prone to quick changes. They adapt rapidly, complicating the body's immune responses.
HIV, a significant retrovirus, infiltrates the immune system, causing AIDS by compromising
defenses against infections. SARS-CoV-2, which led to COVID-19, sparked a worldwide pandemic
with respiratory symptoms, emphasizing the need for research and therapeutic innovations.
The COVID-19 pandemic has demonstrated the insufficiency of available resources in effectively
addressing emerging viral infections. Influenza, a seasonal RNA virus, triggers flu outbreaks, impacting
public health. Research is crucial to understanding how these viruses interact with hosts,
aiding the development of effective treatments and strengthening our ability to face new viral
threats. The most effective defenses against viral illnesses are virus-specific vaccinations and antiviral
drugs. The present review emphasizes the prevalence of the three most pathogenic and widespread
RNA viruses, namely HIV, influenza, and SARS-CoV2, their pathophysiology, and the current
treatment with FDA-approved drugs. It also incorporates novel analogs that are under clinical
trials as there is an urgent need for innovative antiviral medications, and enormous global efforts
are required to find secure and efficient cures for these viral infections.
Spinal KCC2 Mediates the Modulation Effect of HDAC2 on Bone Cancer Pain in Rats
Authors: Wang Tongxuan , Li Yalin , Hou Xinran , Guo Qulian , Weng Yingqi 
Published: February 2025

Background:
Bone cancer pain is a global medical concern with limited treat-ment options that significantly reduce the quality of life for cancer patients. Therefore, identifying a promising therapeutic target for bone cancer pain is urgently needed.

Objective:
Our previous research indicated that KCC2 may be associated with the modula-tion of HDAC2 in a rat model of bone cancer pain. The current study aimed to investigate whether KCC2 in the lumbar spinal cord is a key downstream molecule in the modulation of HDAC2 related to bone cancer pain.

Methods:
In this study, we assessed the expression levels of KCC2 and HDAC2 in the lumbar spinal cord of rats with bone cancer pain using Western blotting and RT-PCR. Mechanical hyperalgesia was evaluated using Von Frey hairs, and immunofluores-cence was employed to localize KCC2 in central nervous system cells.

Results:
The expression of KCC2 was down-regulated in a time-dependent manner in the lumbar spinal cord of rats with bone cancer pain. Furthermore, the use of an RNA-interfering lentivirus targeting HDAC2 restored KCC2 expression and alleviated mechani-cal hyperalgesia in these rats. Notably, the analgesic effect of the HDAC2-targeting lenti-virus was completely reversed by the KCC2 inhibitor VU0240551.

result:
The expression of KCC2 was down-regulated in a time-dependent manner in the lumbar spinal cord of bone cancer pain rats. Furthermore, the use of an RNA-interfering lentivirus targeting HDAC2 restored KCC2 expression and alleviated mechanical hyperalgesia in these rats. Notably, the analgesic effect of the HDAC2-targeting lentivirus was completely reversed by the KCC2 inhibitor VU0240551.

Conclusion:
KCC2 in the lumbar spinal cord mediated the modulation of HDAC2 in rat models of bone cancer pain, suggesting that KCC2 could be a promising therapeutic target for treating bone cancer pain.
ISR Modulators in Neurological Diseases
Authors: Kalinin Alexander Pavlovich , Zubkova Ekaterina Sergeevna , Menshikov Mikhail Yuryevich , Parfyonova Yelena Victorovna 
Published: February 2025

Abstract:
The dysfunction of different cells lies in the pathogenesis of neurological diseases and is
usually associated with cellular stress. Various stressors trigger the integrated stress response (ISR)
signaling, whose highly conserved mechanism is primarily aimed at protecting a stress-exposed cell
to cope as safely as possible with such stressful conditions. On the contrary, if a cell is unable to
cope with excessive stress, the ISR can induce apoptosis. The ISR mechanism, whose main stage is
the inhibition of translation machinery in favor of the synthesis of specific proteins, including the
transcription factors ATF3, ATF4, CEBPA, and CEBPB, which function only as dimers and determine
the uniqueness of the ISR response in each individual case, thus ensures different outcomes of
the ISR. Inhibition of global protein synthesis is achieved through phosphorylation of eIF2α by
PERK, HRI, PKR, or GCN2. To date, a number of compounds have been developed that modulate
the ISR, including activators and inhibitors of the abovementioned ISR kinases as well as modulators
of p-eIF2α dephosphorylation. They target different ISR stages, allowing a broad ISR modulation
strategy. At the same time, there are no drugs that are both exceptionally safe and effective for the
treatment of several neurological diseases, so there is an urgent need for new approaches to the
treatment of these disorders. In this review, we represent ISR signaling as an important participant in
the pathogenesis of neurological diseases. We also describe how various ISR modulators may become
a part of future therapies for these diseases.