bluuebunny/crossref_metadata_2025_split huggingface dataset:
Changes in redox processes in the cells of test objects – bull spermatozoa under the effect of naphazoline nitrate
Authors: Kuzminov Borys , Zazulyak Tetyana , Ostapiv Dmytro 
Published: February 2025

Abstract
Naphazoline nitrate is a medicine with a number of side effects, which should be taken into account not only in therapeutic practice, but also when developing preventive measures in pharmaceutical production. The purpose of our work was to study the effect of naphazoline nitrate on redox processes and the duration of survival of bull spermatozoa. Bull semen samples were divided into groups: control – without adding naphazoline nitrate and experimental – with adding naphazoline nitrate. The respiratory activity of spermatozoa was determined by the polarographic method, reducing capacity – potentiometrically, succinate dehydrogenase activity – photo-metrically; sperm survival – visually. The respiratory activity of spermatozoa is significantly inhibited under the effect of all studied doses of naphazoline nitrate (η = 0.762 and 0.840) and the degree of effect for the highest dose reaches 85.5 %. The reducing capacity changes significantly, starting from a dose of 1/10 LD50 and above, the dose-indicator correlation is low, the dose of LD50 causes changes in the indicator by 229.0% with a change of charge of the medium. SDH activity significantly decreases under the effect of 1/10 LD50 and above, the dose-indicator correlation is moderate, the dose of LD50 causes changes in the indicator by 49.5 %. The substance affects the duration of survival only in the maximum dose, reducing the survival time by 18 %. Conclusion: The substance has the maximum effect on the respiratory activity of germ cells and on the reducing capacity, it has a lesser effect on the SDH activity and slightly affects the survival time. The dose-dependent nature of the effect of naphazoline nitrate on certain indicators of redox processes in spermatozoa confirms the prospects of using the latter as alternative test objects in studying the harmful effects of chemicals.
Phonological alterations of alveolar lateral sounds in Mewati: An analysis using Optimality Theory
Authors: Suhery Dedy , Raza Mohd Hamid , Idami Zahratul , Wati Shafrida , Meutia Cut Intan , Kurniasy Dessy , Mahriza Rita 
Published: February 2025

This study examines the complex phonological shifts within the Mewati language, focusing on the transformation of the alveolar lateral sound between two vowels into an alveolar tap/flap. Using Optimality Theory (OT), our primary goal is to uncover the underlying process responsible for this phonological alteration. Fieldwork, in-depth interviews, and audio recordings were used to acquire extensive data. Together, these three data sources contribute to a comprehensive understanding of the phonological alteration under investigation. In summary, fieldwork provides the context, in-depth interviews offer insights into speakers’ perspectives, and audio recordings supply the raw phonetic data. The research field was Haryana’s District Mewat, where we engaged a diverse group of fifty informants, including youth, adults, and the elderly. Mewati, a language native to Haryana’s Mewat district exhibits a striking pattern. Our findings revealed that Mewati speakers relinquished the identity of the alveolar lateral sound if it did not occur between two adjacent vowels. These linguistic constraints serve as crucial determinants in evaluating potential output candidates, aligning them with the ranking features of input candidates in the framework of OT. The data collected from the heart of Mewat unequivocally confirms the presence of a phonological alteration process within the linguistic landscape of this region.
Angiotensin-Neprilysin Inhibitor Therapy: A Retrospective Chart Study
Authors: Plakogiannis Roda , Stefanidis Abraham , Hernandez Nubriel , Vider Etty 
Published: February 2025

Background: Guideline-directed medical therapy in patients with systolic heart failure (HF) has demonstrated improvement in morbidity and mortality rates. The FDA approved sacubitril/valsartan in 2015 to reduce the risk of cardiovascular death and hospitalization for HF. Objective: The purpose of this study was to evaluate the change in loop diuretic dose and the clinical outcomes of angiotensin receptor-neprilysin inhibitor (ARNI) therapy within a 90-day follow-up period.
Methods: A retrospective chart review of 110 HF patients on concomitant ARNI and loop diuretic therapy at New York University Langone Health was conducted. The primary endpoint was a change in loop diuretic dose. Six secondary endpoints, including dose conversion from ACEi or ARB to ARNI therapy, were assessed.
Results: Of the 110 HF patients, 72 did not receive diuretic dose adjustments, yet 40 (55.56%) experienced laboratory-dependent dehydration. Fifty-six percent of patients experienced an improvement in systolic blood pressure, and 52 percent experienced a decrease in diastolic blood pressure. Sixty percent of patients experienced an improvement in EF, with a median increase of 10.00% over a 90-day follow-up. A significant negative correlation between patients’ age and absolute change in EF was identified (r= -0.28; p < 0.05), indicating that the increase in EF was stronger for younger patients. Eighteen hospitalizations occurred within a 90-day follow-up, with only 4 patients being admitted for heart failure exacerbation.
Conclusion and Relevance: This study examines the real-world effects of ARNI therapy in patients with systolic heart failure. Optimization of HF medications, including ARNI therapy, remains an important factor for achieving the maximum benefits in heart failure management. ARNI therapy requires careful monitoring to ensure effective diuresis in symptomatic heart failure patients while avoiding adverse events. Future studies should address diuretic dose adjustment in conjunction with the administration of ARNI and sodium-glucose cotransporter-2 inhibitors.
Green Politics and the Tyranny of the Thinker
Authors: Culbert Jeff 
Published: February 2025

Sometimes I think of human cognition as the ultimate environmental problem. It's a simplistic hypothesis, I know, especially in its failure to address the fact that some humans are more implicated than others in creating and perpetuating the mess. But in the context of questioning the viability of the species, it is not one to be lightly dismissed. [...]
A Straightforward Philosophical Thought About Virtual Reality and Environmentalism
Authors: Wood Brent 
Published: February 2025

The world, not the planet, is becoming virtual. Our idea of 'the planet' is already a virtual one, as the currently multiplying photos of the globe from space wordlessly attest. When we try to conceive of a 'global system' of any kind, our imaginations prove inadequate to the task. Hence the sublime experience aroused when we attempt. to contemplate our earth in its entirety in one of our more peaceful, less procedural moments, as when a young adult cries at the beach on a summer evening over the fate of humanity. [...]
Formation-Dependent Tectonic Lateral Strain Calibration for CCUS Operations Applying Microfrac Tests
Authors: Ighodalo E. , Berkane M. , Franquet J. , Chakrabarti P. 
Published: February 2025

Abstract
Obtaining a consistent workflow to determine the tectonic lateral stress boundary conditions is a critical subsurface input for building reliable 3D geomechanical models. These models are used to predict cap-rock integrity and seal assessment in CO2 injection projects. This paper compares multiple workflows and tectonic calibration techniques using constant and variable lateral strain values across several formations from Late-Cretaceous to Middle-Triassic.
Tectonic lateral strains are obtained from multiple microfrac tests conducted across different bore-hole sections of a single well drilled. The rock mechanical properties are derived from density, neutron porosity, and acoustic cross-dipole logging data acquired before the downhole formation testing run. Formation breakdown, fracture reopening, and closure pressures are measured on each straddle packer microfrac station across both clastic and carbonate formations. The minimum and maximum horizontal strains are fine-tuned to back-calculate the magnitude of the minimum and horizontal stress until the predicted fracture closure and formation breakdown match the result of the multiple microfrac tests.
Cross-plot correlation coefficients are calculated between log-predicted and microfrac-obtained fracture closure and formation breakdown to compare different methods of tectonic strain derivation. One method uses a constant value for the minimum and maximum strains while a second method uses variable strain values with depth allowing different tectonic lateral conditions on each lithologic formation. Model sensitivity analysis on the methodology of assuming constant poroelastic Biot coefficient values versus estimating Biot from formation porosity logs is also reviewed. The average horizontal strain values obtained have a satisfactory match with the microfrac subsurface measurements. The variable strain method obtains better correlation coefficients for both fracture closure and formation breakdown producing a more accurate match with the multiple in-situ measurements.
This study reveals a very useful methodology to derive accurate and formation-dependent lateral strain tectonic boundary conditions for calibrating geomechanical models across the field in subsurface CO2 injection projects. Accurate prediction of formation breakdown pressure is fundamentally required to constrain the CO2 injection rate and downhole pressure for safe and contained carbon sequestration and storage.
An Integrated Approach to Enhancing Reservoir Property Prediction in a Clastic Reservoir: A Case Study from Acacus Formation, Ghadames Basin, NW Libya
Authors: Alshaafi H. , Elakuri A. , Albrouki M. , Arfaad F. 
Published: February 2025

Abstract
The ultimate goal of this study is to investigate the reservoir architecture in the northern part of Ghadames Basin, Libya, which is known for its highly complex reservoir with multiple layers, using precise 3D modeling with low uncertainties. To overcome the associated facies changes and reservoir complexity of the Acacus formation, the reservoir architecture, petrophysical parameters, structural characteristics, and facies distribution must be understood and recognized. A comprehensive methodology was applied in this study which incorporated facies interpretation, sequence stratigraphy, and machine learning, Embedded Model Estimator (EMBER) to enhance the accuracy of 3D porosity and permeability modeling. Facies interpretation involved core analysis, log signatures, and dip meter data to determine paleocurrents. Seismic data was also utilized, with the root mean square (RMS) attribute proving to be particularly effective in defining different depositional trends. Truncated Gaussian simulation (TGS) was used for facies modeling, enabling population and shoreline delineation. The facies and rock types were populated using the hierarchical modeling approach, using the Sequential Indicator Simulation (SIS) algorithm. The results of this study verified that the lower part of the Lower Acacus can be interpreted as progradational regressive fluvial-deltaic bodies, which primarily trend in the NW-SE direction, with a minor influence from the ENE to WSW. On the other hand, the upper part of the Lower Acacus represents a transgressive wedge, bounded by a surface comprising transgressive. Moreover, the complexity and the interplay between shoreline of this nature poses challenges for traditional 3D porosity and permeability modeling, hindering the accuracy of results. However, the Sand ratio map and Isopach maps confirm the lateral variations of the depositional sequences and the extent of the sand bodies in the target reservoir. The petrophysical model showed that the Lower Acacus Formation had excellent reservoir characteristics in terms of effective porosity and water saturation. To better exploit the most favorable sectors in the Lower Acacus reservoir for accumulation and production of hydrocarbons are likely at the Eastern and southeastern parts of the studied area. The study findings show a strong correlation with established trends, improving the reliability of the models and enabling informed decision-making, including prospective wells.
Use of Natural Language Processing and Computer Vision in Deep Learning for Equipment Failure Investigation on Drilling Tools
Authors: Hutahaean Junko , Simon Kai 
Published: February 2025

Abstract
Incident investigation analysis within the oil and gas industry is a critical process to ensure operational safety, minimize downtime, and improve asset management. However, the sheer volume and heterogeneous nature of data sources (including structured and unstructured text and visual information) present significant challenges to traditional methods of incident classification and contextual understanding and are labor-intensive and error-prone. This paper addresses these challenges by proposing an approach that harnesses natural language processing (NLP) and computer vision techniques in deep learning for equipment failure investigation analysis in drilling tools.
The first component of our approach focuses on leveraging NLP for automated incident classification from a mixture of structured and unstructured text data within the oil and gas industry. With vast volumes of data generated from maintenance logs, technician reports, and incident summaries, manual incident classification becomes impractical and error-prone. By applying advanced NLP algorithms, including text mining and sentiment analysis, we automate the process of categorizing incidents, enabling real-time prioritization and deeper semantic analysis. The second component introduces a novel application of computer vision, where we employ deep learning-based techniques to detect and extract textual information from images captured on various electronic boards. By training models on annotated image datasets, our methodology facilitates the extraction of textual content from diverse electronic boards, enriching the incident investigation process with valuable insights.
Our NLP methodology analyzes the textual content of diverse data sources and enables rapid identification, categorization, and prioritization of critical incidents. By automating text detection from visual electronic board sources, the computer vision model built in this study enhances incident data collection, improves incident context understanding, facilitates efficient information extraction, and facilitates more accurate root cause analysis.
Through empirical validation and case studies, we demonstrate the efficacy and novelty of our integrated approach. Our methodology streamlines incident investigation analysis by automating incident classification and text extraction from visual sources, providing deeper insights into incident contexts, and enabling more informed decision-making. This scalable and effective solution improves incident response, enhances operational safety, and preserves asset integrity within the oil and gas sector, offering a transformative approach to complex incident analysis challenges.
Intelligent Identification of Formation Lithology While Drilling
Authors: Peng C. , Zhang H. L. , Fu J. H. , Li Q. F. , Li J. , Zhu B. , Peng J. P. , Zhang H. R. 
Published: February 2025

Abstract
During drilling engineering, the rate of penetration (ROP) is the basic index to measure the drill ability of various rocks, and drilling parameters are the main control factors that affect the ROP. Identifying formation lithology while drilling can promptly adjust drilling parameters and effectively improve drilling efficiency. In this paper, drilling parameters and intelligent models are combined to realize formation lithology identification while drilling. Different from previous research, this method uses K-means, Fuzzy C-means (FCM), and Mean Shift algorithms to cluster the data set after dimension reduction, uses support vector machine (SVM), random forests (RF), and extremely randomized trees (ET) algorithms to train multiple models to identify formation lithology according to the clustering results, and analyzes the identification accuracy of the models under different combinations of dimension reduction and clustering methods. The results indicate that: 1) without clustering, the accuracy of the model in identifying formation lithology is poor, and the final identification result is biased towards one or two types of lithology; 2) the linear kernel function is the best among the three kernel functions, and the classification results lead to high accuracy in identifying lithology. The classification results of the Gaussian kernel function and polynomial kernel function are biased towards a certain kind of lithology; 3) in the multi-model of linear kernel function + K-Means + SVM, the identification accuracies of sandstone, mudstone, limestone, and shale are 60%, 80%, 70%, and 90% respectively, with an average identification accuracy of 82.5%. This paper puts forward a method for identifying formation lithology while drilling by combining drilling parameters and intelligent models, and takes the YX block as an example to carry out application test. The results show that this method can effectively improve the accuracy of lithology identification while drilling.
Facies Interpretation of Deepwater Deposit in Offshore Sabah Basin
Authors: Charoensuk Jutamas , Centhonglang Chayarus 
Published: February 2025

Abstract
One of the key challenges in deep-water fields offshore Sabah Basin is differentiating turbidite reservoirs from non-reservoir Mass Transport Complexes (MTC). This study integrates seismic and well data to enhance the accuracy of reservoir identification, a critical factor in hydrocarbon resource estimation.
The study began by establishing the geological framework of deep-water deposits through regional basin studies and literature. Facies analysis of turbidites and MTCs was conducted using conventional core data, which was then calibrated with wireline log data (Quadcombo, Dipmeter, and Image logs). The identified facies were tied to 3D seismic data to delineate sequence boundaries, characterize seismic facies, and extract geobodies. Additional inputs from formation pressure tests and field production data further refined reservoir connectivity.
A well-level investigation of core, wireline, and image log data successfully distinguished MTC from turbidite reservoirs. Dipmeter data from image logs provided a clear distinction between the two depositional environments, and density logs highlighted the rapid deposition and de-watering processes associated with MTC, which showed higher density trends compared to turbidite layers. MTCs were characterized by chaotic seismic reflectors and discontinuities, while turbidites exhibited parallel, continuous reflectors. The analysis revealed that low-amplitude, chaotic seismic reflectors, and discontinuous patterns signify MTC, whereas high-amplitude, continuous reflectors correspond to turbidite reservoirs. However, seismic resolution in highly faulted zones posed challenges in separating thin MTC layers from turbidites.
This project offers a robust workflow for distinguishing turbidite deposits from MTC in deep-water settings, significantly improving reservoir model inputs and enhancing resource estimation accuracy. The study also underscores PTTEP's technical capability in addressing complex subsurface challenges in the Sabah Basin.
Adopting Hybrid Cloud Architecture to Enhance Bohai Digital Oilfield
Authors: Wen Xin , Lin Yang , Li Man , Gao Jing , An ChuangFeng 
Published: February 2025

Abstract
Since 2019, with the rise of cloud computing, traditional oil field production management systems have progressively shifted to the cloud. However, this transition encounters various hurdles, including rigid structure, isolated data, scalability issues, and obstacles in technology adoption. To address these challenges, Bohai oilfield has successfully built an intelligent oil field management system using hybrid cloud architecture. This system not only ensures flexibility and expandability but also establishes mechanisms for data integration and sharing, enabling flexible scaling, ensuring compatibility across diverse platforms and devices. Additionally, the intelligent oil field management system adopts a multi-tenant architecture, allowing a single application to serve multiple users or organizations, breaking down data silos, and improving resource utilization.
This paper provides a detailed introduction to the construction of the intelligent oil field platform based on hybrid cloud architecture, including the characteristics of this architecture and its advantages in software development, the design and implementation process of the intelligent oil field platform, and elucidates the interaction mechanism among modules like data collection, real-time monitoring, and intelligent analysis. Furthermore, it describes the application advantages of hybrid cloud architecture in the intelligent oil field platform and validates the effectiveness and feasibility of this solution through some case studies of our intelligent oil field management system, demonstrating its potential in improving oil field production management efficiency and reducing costs. This research not only provides practical references and guidance for the digital transformation of the oil field industry but also offers valuable experience and suggestions for the construction of intelligent oil field platforms.
Perforation Spacing Optimization for Well Integrity
Authors: Younessi A. 
Published: February 2025

Abstract
Small spacings between the perforation tunnels may exacerbate the failure behind the completion by connecting the failure zones in adjacent perforations. These instabilities threaten the integrity of the perforated intervals of the wellbore. It is common to evaluate the stability of perforation tunnels to optimize the perforation orientation, interval and planned drawdown pressure to avoid solid production, but the effect of the perforation spacing is usually ignored. Here, a workflow is presented for optimizing the phasing and shot density of the perforation tunnels to minimize the risk of formation failure in the completion zone. This is done using a series of numerical simulations designed to calculate the zone of impact developed around a single perforation with different orientations and downhole pressure and temperature conditions. Thereafter, a pragmatic approach is used to compare the simulation results against the calculated minimum spacing correspondent to different perforation designs (phasing and shot density). The proposed workflow introduces a practical approach to optimize the perforation phasing and shot density from the formation stability and completion integrity point of view. This geomechanical approach combined with the classic perforation design conducted by production and completion engineers reduces the risks of well integrity failure for its expected life span.