bluuebunny/crossref_metadata_2025_split huggingface dataset:
Monocyte response in myocardial infarction in patients with type 2 diabetes
Authors: Kukharchik G. A. , Lebedeva O. K. , Gaykova L. B. 
Published: March 2023

Aim. To reveal the features of monocyte response in myocardial infarction (MI) in pa­­tients with type 2 diabetes (T2D).Material and methods. The study included 121 patients with MI and T2D as follows: 76 — with target glycated hemoglobin (HbA1c), 45 — with elevated HbA1c values. In addition to the standard examination, all patients underwent a blood test for HbA1c on day 1 of MI, while on days 1, 3, 5, and 12±1, monocyte subpopulations were assessed by flow cytometry.Results. Patients with target HbA1c were older than patients with elevated HbA1c levels. In the group with target HbA1c, the number of CD16(+) monocytes on the 1st day of MI was significantly higher: 61,38 (39,2; 100,08) cells/µl vs 35,7 (28,98; 40,33) cells/µl, p=0,03; on the 3rd day of MI, the number of "intermediate" CD14(+)CD16(+) monocytes was higher: 74,82 (71,78; 83,2) cells/µl vs 25,90 (14,04; 57,12) cells/µl, p=0,03, while the CD16(-) to CD16(+) monocyte ratio on the 3rd day of MI was lower: 8,32 (6 ,87; 10,03) vs 10,81 (8,90; 21,10), p=0,04. At the same time, in the group of patients with target HbA1c values, the level of CD16(+) monocytes on the 3rd day of MI was significantly higher in patients aged <71 years compared with patients ≥71 years: 104,55 (63,64; 149,7) cells/µl vs 55,20 (36,92; 76,59) cells/µl, p=0,03.Conclusion. In patients with T2D and target HbA1c values, compared with patients with elevated HbA1c, the inflammatory response in MI is associated with higher levels of CD16(+) monocytes on days 1 and 3 of MI, which is more typical for people aged <71 years.
Un modelo ecológico de la intención de deserción en estudiantes universitarios durante la pandemia por covid-19
Authors: Navarro-Roldán Claudia Patricia , Mateus Gómez Sandra Milena , Avedaño Soto Helmer Andrés 
Published: March 2023

Objetivo: Analizar la intención deserción de los estudiantes universitarios tras seis meses de confinamiento en casa durante la pandemia por covid-19 a partir de un modelo ecológico.

Método: Estudio transversal no experimental con un muestreo intencional de 1011 estudiantes universitarios activos durante 2020. Con edades comprendidas entre los 18 y los 54 años (M = 22,6; DE = 4,8; mujeres = 438). Los estudiantes respondieron el cuestionario de abandono universitario para estudiantes, la Escala de Depresión, Ansiedad y Estrés, la Escala de Miedo de covid-19, la Escala de Síndrome de Ansiedad de covid-19 y el cuestionario de Satisfacción con los cambios académicos. Se realizó un análisis descriptivo y multivariante de los datos.

Resultados: El modelo explica el 28 % de la varianza de la intención de deserción entre los estudiantes universitarios durante el confinamiento por covid-19 (sensibilidad = 86,8 %). La insatisfacción ante los cambios académicos es el principal predictor del modelo (OR = 0,960; IC 95 % [0,950, 0,959). Otros predictores significativos son las interacciones positivas y negativas (i.e., en el entorno familiar, social y académico), los síntomas emocionales negativos, la ansiedad ante la covid-19, ser mayor, estudiar en una universidad privada y tener un familiar diagnosticado con covid-19.

Conclusiones: Los cambios en el macrosistema (i.e., el confinamiento en el hogar y las clases en línea) durante los primeros seis meses de la pandemia por covid-19 modificaron la interacción de los estudiantes con sus sistemas proximales y surgieron nuevos predictores de la intención de abandono (e.g., ansiedad ante la covid-19 y tener un familiar diagnosticado con covid-19), asociados al contexto de confinamiento.
THE MECHANISM OF STUDYING PRAGMATIC COMPETENCE
Authors: Pavlova Anna V. 
Published: March 2023

Aim. To analyze linguistic politeness strategies of artificial bilinguals in the implementation of the speech act of refusal.Methodology. In the course of the study, a linguistic experiment was carried out on the basis of written discursive test methodology.Results. The experiment has revealed that artificial bilinguals use a great variety of politeness strategies in their discourse. These strategies are reflected in the head act and the supportive speech acts of refusal.Research implications. The submitted methodology allows to analyze the strategies of linguistic politeness which is a part of pragmatic competence. The latter one should be obtained by artificial bilinguals who are learning a foreign language. The results of the experiment can be used in courses on Theory of Intercultural Communication and Pragmalinguistics.
A Review of Soft Electronic Devices Based on Flexible and Stretchable Materials for Cardiac Monitoring
Authors: Sung Minkyung 
Published: March 2023

Purpose of the study: The number one killer, cardiovascular disease, has sharply increased in recent years. For early diagnosis and prevention, continuous cardiac monitoring is crucial, and flexible, stretchable electronic devices have become essential instruments to record cardiac activity. Bioelectronics has greatly improved from recent developments in soft, ultrathin bioelectronics that have been made possible by breakthroughs in soft materials and novel device designs.
Methodology: This study focuses on flexible and stretchable materials as well as design strategies for current developments in soft electronics-based wearable and implantable devices for cardiac monitoring.
Main Findings: The mechanical deformability in soft bioelectronics has enabled researchers to obtain high-quality bio-signals and reduce long-term negative effects in vivo. They provide close, long-term integration with cardiac tissues due to their thin and soft characteristics, allowing for continuous, high-quality, and wide coverage in cardiac monitoring.
Applications of this study: This review is anticipated to provide timely and significant information for prospective audiences in the fields of material science and biomedical engineering, who seek a concise summary of key technologies, as well as biomedical fields who may be interested in the clinical implications of soft bioelectronics for cardiac healthcare.
Novelty/Originality of this study: The materials, fabrication techniques, and device designs for flexible and stretchable electronics are reviewed with a particular emphasis on flexible and soft materials.
Sport jako zjawisko polityczno-tożsamościowe na Litwie w XX wieku. Działalność Michała Sienkiewicza na Wileńszczyźnie
Authors: Jung Rafał 
Published: March 2023

Artykuł traktuje o roli sportu w budowaniu i podtrzymywaniu tożsamości narodowej w skomplikowanych warunkach etniczno-politycznych. Rzecz dotyczy historii Litwy w XX wieku, gdzie relacje między zamieszkującymi ten obszar Litwinami i Polakami w dużej mierze określał polsko-litewski spór o przynależność Wileńszczyzny z okresu międzywojennego. Odmienne tradycje sportowe przyczyniły się do zachowania odrębności narodowej obu nacji w okresie sowieckiego zniewolenia, jednocześnie sukcesy sportowe Litwinów w latach 1947–1988, zwłaszcza koszykarzy w ramach ekip reprezentujących Związek Sowiecki, stanowiły element ich emancypacji politycznej. Doprowadził on wraz z innymi czynnikami do odzyskania niepodległości przez Litwę i jednocześnie warunkował potrzebę zdefiniowania na nowo stosunków między Litwinami i Polakami na Litwie. Sport odgrywał w tym procesie zazwyczaj rolę łączącą obie społeczności. Zaświadcza o tym postać Michała Sienkiewicza, sportowca, później niezwykle aktywnego działacza na rzecz sportu Polaków na Wileńszczyźnie, uczestnika życia sportowego w czasach sowieckich, między innymi sędziego lekkoatletycznego podczas legendarnego dla Polaków konkursu skoku o tyczce z udziałem Władysława Kozakiewicza, odbywającego się w ramach Igrzysk XXII Olimpiady w Moskwie w 1980 r. W okresie zaś wznoszenia fundamentów litewskiej niepodległości – inicjatora i uczestnika odbudowy Litewskiego Narodowego Komitetu Olimpijskiego i polskiego Towarzystwa Gimnastycznego „Sokół” na Litwie.
PENGARUH KEBIASAAN BELAJAR DAN MINAT BELAJAR TERHADAP PRESTASI SISWA MTs. ALMAARIF 01 SINGOSARI
Authors: Mariani Alfa Aulia , Hidayat Imam Wahyu 
Published: March 2023

The aims of this study were to: 1) determine the effect of study habits on student achievement; 2) knowing the effect of interest in learning on student achievement; and 3) determine the effect of study habits and interest in learning on student achievement. This study uses a quantitative approach with a correlational type. The population in this study were class VIII students, totaling 358 students with a total sample of 189 students. The technique of collecting data on study habits and interest in learning is in the form of distributing questionnaires, while learning achievement is obtained through documentation of even semester PTS scores. The data analysis technique used included multiple linear regression analysis, T test, and F test. The results showed that 1) there was no effect between study habits on student achievement (p=0.610 > α=0.05); 2) there is an influence between learning interest on student achievement (p=0.003 < α=0.05); and 3) there is an influence between students' learning habits and students' learning interest on student achievement (p=0.003 > α=0.05).
Abstrak
Tujuan dari penelitian ini adalah untuk: 1) mengetahui pengaruh kebiasaan belajar terhadap prestasi belajar siswa; 2) mengetahui pengaruh minat belajar terhadap prestasi belajar siswa; dan 3) mengetahui pengaruh kebiasaan belajar dan minat belajar terhadap prestasi belajar siswa. Penelitian ini menggunakan pendekatan kuantitatif dengan jenis korelasional. Populasi dalam penelitian ini adalah siswa kelas VIII yang berjumlah 358 siswa dengan jumlah sampel 189 siswa. Teknik pengumpulan data kebiasaan belajar dan minat belajar berupa penyebaran angket, sedangkan prestasi belajar diperoleh melalui dokumentasi nilai PTS semester genap. Teknik analisis data yang digunakan meliputi analisis regresi linear berganda, Uji T, dan Uji F. Hasil penelitian menunjukkan bahwa 1) tidak terdapat pengaruh antara kebiasaan belajar terhadap prestasi belajar siswa (p=0,610 > α=0,05); 2) terdapat pengaruh antara minat belajar terhadap prestasi belajar siswa (p=0,003 < α=0,05); dan 3) terdapat pengaruh antara kebiasaan belajar siswa dan minat belajar siswa terhadap prestasi belajar siswa (p=0,003 > α=0,05).
Accuracy Evaluation of a Novel Spinal Robotic System for Autonomous Laminectomy in Thoracic and Lumbar Vertebrae
Authors: Li Zhuofu , Wang Chengxia , Song Xiongkang , Liu Shanshan , Zhang Yonghong , Jiang Shuai , Ji Xuquan , Zhang Tianyang , Xu Fei , Hu Lei , Li Weishi 
Published: March 2023

Background:The main function of robots in spine surgery is to assist with pedicle screw placement. Laminectomy, which is as important as pedicle screw placement, lacks a mature robot-assisted system. The aims of this study were to introduce the first autonomous laminectomy robot, to explore the feasibility of autonomous robotic laminectomy, and to validate its accuracy using a cadaveric model.Methods:Forty vertebrae from 4 cadavers were included in the study; 7 thoracic and 3 lumbar vertebrae were randomly selected in each cadaver. The surgeon was able to plan the laminectomy path based on computed tomographic (CT) data before the surgical procedure. The robot performed the laminectomy autonomously, and a postoperative CT scan was made. The deviation of each cutting plane from the plan was quantitatively analyzed, and the accuracy and safety were qualitatively evaluated. The time required for the laminectomy was also recorded.Results:Cuts were performed in 80 laminectomy planes (56 for thoracic vertebrae and 24 for lumbar vertebrae). The mean time for 1-sided laminectomy was 333.59 ± 116.49 seconds, which was shorter for thoracic vertebrae (284.41 ± 66.04 seconds) than lumbar vertebrae (448.33 ± 128.65 seconds) (p < 0.001). The mean time for single-level total laminectomy was 814.05 ± 302.23 seconds, which was also shorter for thoracic vertebrae (690.46 ± 165.74 seconds) than lumbar vertebrae (1,102.42 ± 356.13 seconds) (p = 0.002). The mean deviation of the cutting plane from the plan was 0.67 ± 0.30 mm for the most superior cutting point and 0.73 ± 0.31 mm for the most inferior point. There were no significant differences in the deviation between thoracic vertebrae (0.66 ± 0.26 mm) and lumbar vertebrae (0.67 ± 0.38 mm) at the superior cutting point (p = 0.908) and between thoracic vertebrae (0.72 ± 0.30 mm) and lumbar vertebrae (0.73 ± 0.33 mm) at the inferior cutting point (p = 0.923). In the qualitative analysis of the accuracy of the 80 laminectomy planes, 66 (83%) were classified as grade A, 14 (18%) were grade B, and none was grade C. In the safety analysis, 65 planes (81%) were considered safe and the safety of the other 15 planes (19%) was considered uncertain.Conclusions:The results confirmed the accuracy of this robotic system, supporting its use for laminectomy of thoracolumbar vertebrae.Level of Evidence:TherapeuticLevel V. See Instructions for Authors for a complete description of levels of evidence.
A Mineral-Composition Dependent Fracture Numerical Model of Thermally Treated Shale Gas Reservoirs
Authors: Ji Dongqi , Lei Zhengdong , Liu Jiandong , Han Xu , Ge Chenqi , Li Zhiping , Chen Zhangxing 
Published: March 2023

Abstract
Thermal treatment of shale gas reservoirs can vaporize water, accelerate gas desorption, and induce micro-fractures in shale matrix, which is a potential method to enhance shale gas productivity. However, few studies are focused on the thermal micro-cracking behavior of shale, especially at the mineral-scale. Furthermore, the effect of mineral composition on micro-fracture generation and shale permeability alternations are not fully understood in the current research results. In this work, a mineral-dependent fracture numerical model of thermally treated shale gas reservoirs is proposed. This model couples thermally induced stress in minerals, permeability enhancement, fluids flow and energy conservations in shale. A novel constitutive model based on volumetric constraint to relate stress and strain of minerals in shale is applied in the numerical simulation process. Comparison to experimental results demonstrates the reliability and robustness of the presented computation model. The proposed simulation method in this work is a powerful tool to link the macro-scale characteristics and thermally induced micro-fracture of shale.
Successful Application of an Ensemble Modeling Workflow for a Deepwater Field in US Gulf of Mexico
Authors: Peraser Vivek , Shen Eugene , Dugat Will , Sweatman Mark , Cedillo Gerardo 
Published: March 2023

Abstract
A Deepwater field in the Gulf of Mexico is currently in its mid-production life and undergoing development optimization, which was underpinned by a robust evaluation using multiple geologic scenarios that were history matched to observed field data. This challenge was addressed using an ensemble modeling workflow that has been guided by BP's Top-Down Reservoir Modeling (TDRMTM) (1) principles. The ensemble contained 27 distinct geologic scenarios and was used to evaluate water injection, field expansion, and infills.
For a wide range of geologic scenarios covering alternate structural and stratigraphic models, a workflow called "forced boxing" was executed along with the assisted history matching algorithm, PSO-MADS (2, 3), to fully history match historical rates and pressures for more than 27 distinct combinations of geologic scenarios. These scenarios covered a wide range of oil-in place, connectivity, aquifer strength, and relative permeability behavior. The final calibrated ensemble of 1000s of models was then down sampled to ~100 distinct models to use for the probabilistic evaluation of water injection, field expansion, and infills.
The "forced boxing" technique was successful at finding high quality history matches for 25 of the 27 distinct geologic scenarios. The history matching workflow considered well-level production rates, including water cut, as well as reservoir pressure measurements (MDTs). A match quality acceptance workflow was set up to find acceptable models out of each geologic scenario. The resulting ensemble of models contained over 20,000 distinct simulation cases. A methodology was used to down sample those cases to a final ensemble of ~100 models covering the 25 geologic scenarios. This workflow is an improvement to conventional history matching and uncertainty workflows because this workflow ensures multiple geologic scenarios are matched and included in the ensemble and the final set of models gives a probabilistic view of the predictive outcomes. The ~100 model ensemble was then utilized to explore different field development opportunities and included the successful selection of an economic infill producer target.
The "forced boxing" approach, which entailed history matching distinct static parameter combinations, was built to ensure diversity of scenarios/outcomes as opposed to traditional workflows that focus on finding the best history matches. Given the importance of cross-fault communication between different reservoir sands, the parameterization of fault throws as a variable controlled in the optimization process was also a novel addition to the history matching workflow.
A Data-Driven Deep Learning Framework for Microbial Reaction Prediction for Hydrogen Underground Storage
Authors: Katterbauer Klemens , Al Shehri Abdallah , Qasim Abdulaziz , Yousif Ali 
Published: March 2023

Abstract
As the use of hydrogen gas (H2) as a renewable energy carrier experiences a major boost, one of the key challenges for a constant supply is safe and cost-efficient storage of surplus H2 to bridge periods with low energy demand. For this purpose, underground gas storage (UGS) in salt caverns, deep aquifers and depleted oil-/gas reservoirs has been proposed, which provide suitable environments with potentially high microbial abundance and activity. Subsurface microorganisms can use H2 in their metabolism and thus may lead to a variety of undesired side effects such as H2 loss into formation, H2S build up, methane formation, acid formation, clogging and corrosion.
We present a new AI framework for the determination of metabolism processes of subsurface microorganisms in hydrogen underground storage. The AI framework enables to determine the potential microbial related processes and reactions in order to optimize storage strategies as well as incorporate potential remediating actions to ensure efficient and safe underground hydrogen storage and minimize related side effects.
We evaluated the framework on investigating potential microbial reactions for hydrogen storage in the Pohokura gas field in New Zealand. The framework evaluates reservoir parameters, such as temperature, pressure, salinity and hydrogen injection volumes as well as duration, and then classifies which reactions may take place as well as indicates the likelihood of the reaction taking place. For the deep learning framework, an optimized random forest algorithm was implemented and compared to other multi-class classification problems. The results demonstrated the ability to determine the microbial reactions that may take place with hydrogen storage reservoir as well as its severity, which enhances the optimization of injection strategy as well as suitability of a reservoir.
This framework represents an innovative approach to microbial reaction prediction for underground hydrogen storage. The framework allows potential reservoirs to be efficiently evaluated and optimization strategies to be utilized in order to maximize the efficiency of underground hydrogen storage.
A Fast History Matching and Optimization Tool and its Application to a Full Field with More than 1,000 Wells
Authors: Ren Guotong , Wang Zhenzhen , Lin Yuanbo , Onishi Tsubasa , Guan Xiaoyue , Wen Xian-Huan 
Published: March 2023

Abstract
In this work, we study a waterflood field containing over 1,000 wells and the modern field management techniques with full-fidelity 3D geo-cellular reservoir models become computationally prohibitive. To overcome the difficulty, we developed a novel flow-network data-driven model, GPSNet, and used it for rapid history matching and optimization. GPSNet includes physics, such as mass conservation, multiphase flow, phase changes, etc., while maintaining a good level of efficiency. To build such a model, a cluster of 1-D connections among well completion points are constructed and form a flow network. Multi-phase fluid flow is assumed to occur in each 1-D connection and the flow in the whole network is simulated by our in-house general-purpose simulator. Next, to effectively reduce the uncertainty, a hierarchical history-matching workflow is adopted to match the production data. Ensemble Smoother with Multiple Data Assimilation (ESMDA) is utilized to reduce the error at each step of the history matching. Next, a best-matched candidate is selected for numerical optimization to maximize oil production rates with constraints satisfying field conditions. Excellent history-matching results have been achieved on the field level and good matches have also been observed for key producers. In addition, the history matching consumes mere 4 hours to finish 1,100 simulation jobs. The successful application of the GPSNet to this waterflood field demonstrates a promising workflow that can be used as a fast and reliable decision-making tool for reservoir management.
An Adaptive Newton–ASPEN Solver for Complex Reservoir Models
Authors: Lie K. -A. , Møyner O. , Klemetsdal Ø. A. 
Published: March 2023

Abstract
Standard Newton methods that are used to advance fully implicit or adaptive implicit schemes in time often suffer from slow or stagnant convergence when natural initial guesses are too far from the solution or the discrete flow equations contain nonlinearities that are unbalanced in time and space. Nonlinear solvers based on local-global, domain-decomposition strategies have proved to be significantly more robust than regular Newton but come at a higher computational cost per iteration. The chief example of one such strategy is additive Schwarz preconditioned exact Newton (ASPEN) that rigorously couples local solves, which in sum have little cost compared with a Newton update, with a global update that has a cost comparable to a regular Newton solve.
We present strategies for combining Newton and ASPEN to accelerate the nonlinear solution process. The main feature is a set of novel monitoring strategies and systematic switching criteria that prevent oversolving and enable us to optimize the choice of solution strategy. At the start of each nonlinear iteration, convergence monitors are computed and can be used to choose the type of nonlinear iteration to perform as well as methods, tolerances, and other parameters used for the optional local domain solves. The convergence monitors and switching criteria are inexpensive to compute.
We observe the advantages and disadvantages of local-global domain decomposition for practical models of interest for oil recovery and CO2 storage and demonstrate how the computational runtime can be (significantly) reduced by adaptively switching to regular Newton's method when nonlinearities are balanced throughout the physical domain and the local solves provide little benefit relative to their computational cost.