bluuebunny/crossref_metadata_2025_split huggingface dataset:
Опыт преподавания дисциплины «Проектирование информационных систем» в техническом вузе
Authors: Гутгарц Р.Д. 
Published: March 2023

Выделены факторы организации образовательной деятельности, которые необходимо учитывать согласно концепции изучения дисциплины «Проектирование информационных систем» (направление 09.03.01 – Информатика и вычислительная техника, профили «Автоматизированные системы обработки информации и управления» и «Информационные системы и технологии») в техническом вузе. Рассмотрена интерпретация данных факторов применительно к созданию автоматизированных информационных систем организационно-управленческого типа. Показаны и проанализированы современные тенденции методического и прикладного характера в представлении учебных материалов на примере реальных учебников, учебных пособий и учебнометодических работ по рассматриваемой дисциплине, особенности взаимосвязей ФГОС ВО, учебного плана и Рабочей программы дисциплины «Проектирование информационных систем». Отражены аспекты обучения в традиционных аудиторных условиях и в условиях обучения в дистанционном формате. Приведены практические примеры содержания отдельных заданий, выполняемых студентами в рамках самостоятельных работ, ориентированных на развитие аналитических компетенций.
The factors of organizing educational activities that must be taken into account according to the concept of studying the discipline “Design of information systems” (direction 09.03.01 – Informatics and computer technology, profi les “Automated systems for processing information and control” and “Information systems and technologies”) at a technical university are identifi ed. The interpretation of these factors in relation to the creation of automated information systems of organizational and managerial type is considered. Modern trends of a methodological and applied nature in the presentation of educational materials are shown and analyzed using the example of real textbooks, teaching aids and educational and methodological works in the discipline under consideration, the features of the relationship between the Federal State Educational Standards of Higher Education, the curriculum and the Work Program of the discipline “Information Systems Design”. Aspects of learning in traditional classroom conditions and in conditions of distance learning are refl ected. Practical examples of the content of individual tasks performed by students as part of independent work focused on the development of analytical competencies are given.
Postawy Polaków wobec szczepień przeciwko COVID-19
Authors: Mika Magdalena 
Published: March 2023

Pandemia COVID-19 wpłynęła na życie społeczne i gospodarcze, zaburzając normalny rytm funkcjonowania niemal każdego człowieka. Nadzieją na powrót do normalności było wynalezienie szczepionki i jej działania prewencyjne. Niniejsza praca ma na celu zidentyﬁ kowanie, w jaki sposób przebieg pandemii koronawirusa wpłynął na postrzeganie wakcynacji w społeczeństwie.
Niniejsza praca została napisana na podstawie wykonanych badań wtórnych, to jest analizy danych statystycznych dostępnych w bazach światowych (WHO, Our World In Data) oraz krajowych (CBOS, dane Ministerstwa Zdrowia), obejmujących okres 2019–kwiecień 2022. Ponadto przeprowadzono badania pierwotne, których celem była identyﬁ kacja postaw Polaków wobec szczepień. Badania zostały zrealizowane na próbie 152 respondentów w maju 2022 roku. Zgromadzone wyniki pozwoliły na sformułowanie wniosków. Badania wykazały, że przed pandemią obowiązkowym szczepieniom poddawało się 92 % ankietowanych. Z kolei 76% przyjęło szczepienia przeciw wirusowi SARS-CoV-2. Oznacza to, że 16% było negatywnie nastawionych do szczepienia covidowego. Zaszczepiło się 60% Polaków, czyli o 8 punktów procentowych poniżej średniej europejskiej, a wśród już zaszczepionych ankietowanych tylko 42% planuje przyjąć trzecią dawkę. Ponadto ponad połowa (51%) uważa, że ich wiedza na temat szczepień nie jest wystarczająca.
Substytucja leków w aptece ogólnodostępnej podczas pandemii COVID-19
Authors: Szpala Magdalena 
Published: March 2023

Substytucja leku w aptece polega na zamianie preparatu, pierwotnie zaordynowanego na recepcie przez osobę uprawnioną do jej wystawienia, przez osobę uprawnioną do wydawania produktu leczniczego. Proces ten zachodzi podczas zakupu leku w aptece ogólnodostępnej. Uczestniczą w nim pacjent oraz farmaceuta lub technik farmaceutyczny. Kwestie prawne zamiany leku reguluje ustawa refundacji leków, środków spożywczych specjalnego przeznaczenia żywieniowego oraz wyrobów medycznych z dnia 12 maja 2011 roku. W Polsce możliwa jest substytucja leku oryginalnego na lek generyczny, leku generycznego na oryginalny lub też leku generycznego na inny generyczny. Lek oryginalny to taki, który został wprowadzony na rynek jako pierwszy i podlegał początkowo ochronie patentowej. Leki generyczne są według Światowej Organizacji Zdrowia zamiennikami leku oryginalnego. Nie posiadają patentu i mogą zostać wprowadzone dopiero po wygaśnięciu ochrony patentowej leku oryginalnego. Proces dopuszczania ich do obrotu jest uproszczony w stosunku do leku oryginalnego.
Powodami zamiany leku w aptece są najczęściej względy ekonomiczne, czyli niższa cena zamiennika lub niedostępność pierwotnie zaordynowanego leku w aptece. Pandemia COVID-19 przyczyniła się do braków leków w aptekach, szczególnie na jej początku. Przyczyn deﬁcytów poza przewyższeniem podaży przez popyt upatruje się w tym, że zarówno leki, jak i surowce są w znacznym stopniu importowane z Chin i Indii. Niniejsze rozważania zawężono tylko do leków dostępnych na receptę.
Celem pracy jest przedstawienie zjawiska substytucji leków w aptece ogólnodostępnej, które to zjawisko można zaobserwować podczas pandemii COVID-19. Analizie poddano dane rynkowe, udostępnione na potrzeby niniejszej pracy przez PEX PharmaSequence Sp. z o.o.
Podczas pandemii COVID-19 nastąpił wzrost skali substytucji. W 2019 roku zamienionych zostało 3,73% wszystkich leków przepisanych na recepcie, podczas gdy w 2020 było ich 5,50%. Wnioski wynikające z publikacji wskazują na konieczność dalszej obserwacji zjawiska zamiany leku w aptece przez osoby upoważnione do wydawania produktów leczniczych i ciągłego podejmowania problemu z perspektywy różnych dyscyplin naukowych.
Troll Reservoir Simulation Development, From Well Long-Term Tests to Full FMU Simulations
Authors: Reiso Edel , Bjørke Kjetil , Ek Torbjørn , Nybø Roger , Rivenæs Jan C. 
Published: March 2023

Abstract
Reservoir simulation studies of the Troll field, from the start with single realization full field simulation models and well simulation models in 1991 until today's complex and large ensemble models, have given important input to the Troll field development, reservoir management and well planning. The main focus in this paper is on Troll Oil simulation model. The effects of hardware and software technology developments are discussed. This includes challenges due to field size, geology, communications, thin oil zone, horizontal wells, gridding, numerics, CPU etc. Troll reservoir simulation has always pushed the limits of the hardware and the software, and this has initiated new solutions in modelling and simulators.
The following topics are addressed:
General information about the Troll field Troll Oil – how did it start Model size, grid resolution and hardware capacity – pushing the limits Grid construction Well modelling Geological reservoir model From Reference Model to Multiple Realizations
The Hybrid-Dimensional Darcy's Law: A Non-Conforming Reinterpreted Discrete Fracture Model (RDFM) for the Compressible Miscible Displacement and Multicomponent Gas Flow in Fractured Media
Authors: Xu Ziyao , Yang Yang 
Published: March 2023

Abstract
In this work, we develop a non-conforming reinterpreted discrete fracture model for the compressible miscible displacement and multicomponent gas flow in porous media containing high-permeability fractures and/or low-permeability barriers based on the hybrid-dimensional Darcy's law established in our previous work.
The key idea of the model is to describe the permeability of codimension-one fractures and barriers by the Dirac-delta functions. When there are only fractures, delta functions are added to the permeability tensor on the right-hand side of the Darcy's law. In contrast, when there are only barriers, delta functions are added to the inverse of the permeability tensor, which represents the resistance to fluids, on the left-hand side of the Darcy's law. When both appear, delta functions are contained on both sides by the principle of superposition. Thereby, we establish partial differential equations (PDEs) to model fluid flow in fractured porous media, which exempts any requirements on meshes.
We adopt the discontinuous Galerkin (DG) method to discretize the model in space and the second order implicit pressure explicit concentration (SIMPEC) method to march in time. The resulting non-conforming discrete fracture model is local mass conservative, flexible for complex geometry and easy to implement. The good performance of the method is demonstrated by several numerical examples.
Resolving Ambiguity in 2008-2015 Irving-Dallas Seismicity by Coupling Geomechanical Models at Fort Worth Basin and Barnett Reservoir Scales
Authors: Bubshait Abdulrahman , Jha Birendra 
Published: March 2023

Abstract
The activation mechanism of Irving-Dallas events is not well understood as it is shrouded in ambiguity due to many earthquakes located relatively far (&gt;15 km) from production and injection wells. This requires a modeling approach that can quantify spatiotemporal propagation of production- and injection-induced stresses from wells to the faults while resolving fault geometry, stratigraphy, and well activity. However, constructing one such detailed model for the entire basin is computationally prohibitive due to the millions of grid cells needed to discretize the basin at that resolution. Based on our analysis of the data on well activity and fault position, we employed a novel two-model approach that exploits the disparity in scales between the basin-scale injection analysis and the well-scale fault reactivation analysis. We construct a coarse-scale model of Ellenburger injection in the Fort Worth basin and a fine-scale flow-geomechanics model of the Dallas-Irving region containing the faults that hosted the seismicity and the production/injection wells in the region. We use the coarse model to provide time-dependent pressure boundary conditions to the fine-scale model. We analyze the spatiotemporal evolution of pressure fields at both basin and reservoir scales. Analysis of the results provides evidence for interaction between Barnett's production and Ellenburger's injection as well as pressure diffusion from Ellenburger into the basement along the through-going faults. It allows us to test the hypothesis of injection-induced reactivation as the causative mechanism for the Irving seismic events. Almost all injection-induced seismicity studies in the literature show how injection near a fault (well-to-fault distance &lt; 10 km) can induce seismicity. We provide evidence of far-field injection-induced seismicity (well-to-fault distance &gt; 80 km) by coupling basin-scale and reservoir-scale models and a multi-physics approach.
An Integrated Modeling Framework for Simulating Complex Transient Flow in Fractured Reservoirs with 3D High-Quality Grids
Authors: Liu Hui , Liao Xinwei , Lie Knut-Andreas , Klemetsdal øystein , Bao Kai , Zhao Xiaoliang , Johansson August , Raynaud Xavier 
Published: March 2023

Abstract
Modeling near-well transient flow with complex 3D fracture networks poses several challenges: the multiscale nature (millimeters to kilometers), long and deviating well trajectories, intricate fracture networks with fracture-fracture and fracture-well intersections, and high level of reservoir heterogeneities. We address these difficulties by proposing a comprehensive methodology for meshing, discretizing, and simulating transient flow in complex 3D fracture networks based on discrete fracture-matrix models.
Our framework consists of three parts: (i) Given deviating wells and planar or nonplanar fractures and faults, we construct highquality 3D grids conforming to wells, hydraulic fractures, faults, and dominating natural fractures. We ensure sufficient mesh quality near important features using transfinite interpolation near wells and hydraulic fractures, combined with adaptive refinement in regions of interest. (ii) With the generated grid, we discretize the governing equations with a fully implicit finite- volume formulation with an inner-boundary well model and discrete fracture model. (iii) Finally, we analyze the results using suitable visualization tools, both for pressure-transient curves and 3D matrix/fracture data.
The framework enables high-resolution numerical modeling of transient flow with complex fracture networks in 3D. We demonstrate the capacities through simple validation cases with comparisons against an industry-standard commercial well-testing software but also present highly complex cases with long and deviating well trajectories and highly detailed fracture networks. We present and analyze flow-transient behavior coupling the wellbore, the fracture network, and the matrix. We also present an approach to reliably diagnose complex multiple flow regimes on the pressure-transient curves combined with different-scale spatial pressure distribution. Comparison against the commercial software indicates that our framework does not introduce adverse grid-orientation effects for non-K-orthogonal grids which is able to robustly handle the details for fracture-network heterogeneities in 3D reservoirs.
Overall, our framework is robust for simulating and analyzing realistic second-level transient effects and short-term well performance with complex fracture networks and heterogeneities. Detailed description of the 3D fracture networks, and accurate simulation of the near-well transient flow behavior can be achieved, which provides confidence to interpret the dynamic flow data at different scales and observe transport mechanisms in unconventional fractured reservoirs with multiple levels of heterogeneity.
Formation Fracturing by High-Energy Impulsive Mechanical Loading
Authors: Cao Wen , Younis Rami M. 
Published: March 2023

Abstract
Recent technological advances to trigger high-energy seismic waves from within the wellbore have spurred interest in their application to induce fracturing. While a considerable body of recent experiments at the bench scale (on the order of 1 cubic foot) show promise, there remains considerable uncertainty in how the process scales. This work characterizes the scaling relationships between the extent and intensity of fracturing stimulation and stress-wave characteristics. Our approach leverages direct numerical simulation of the elastodynamic equations accounting for nonlinear fracture mechanics. We apply a hybrid Finite-Discrete Element Method (FDEM) where cohesive (elasto-plastic) laws hold mesh elements together until complete failure. Beyond failure, elements act as deformable free bodies that can interact via contact constraints. An infinite domain is modeled with a spherical inclusion within which an impulsive load is imposed. The dynamic load models a rise time to a peak pressure, followed by a decay period, and all occurring within micro- to milliseconds. The model is validated with experimental observations at the bench scale after mesh-refinement verification. Finally, the model is used to explore the dimensionless parameter space by varying loading characteristics (rise time, peak pressure, and impulse) to reveal the stimulated damaged bulk volume and the crack intensity within it. At the bench scale, the model reproduces a nearly linear trend between damage radius and peak stress. Beyond that, however, the model predicts that this scaling slows considerably to a fractional power law between the damaged radius and the peak stress. This limitation is coincident with a geometric increase in the intensity of damage within the stimulated volume.
A Unified Thermal-Reactive Compositional Simulation Framework for Modeling CO2 Sequestration at Various Scales
Authors: Wapperom M. , Lyu X. , Nichita D. V. , Voskov D. 
Published: March 2023

Abstract
In this work, we present a unified framework for the simulation of CO2 sequestration problems at various time and space scales. The parametrization technique utilizes thermodynamic state-dependent operators expressing the governing equations for the thermal-compositional-reactive system to solve the nonlinear problem. This approach provides flexibility in the assembly of the Jacobian, which allows straightforward implementation of advanced thermodynamics. We validate our simulation framework through several simulation studies including complex physical phenomena relevant to CCUS. The proposed simulation framework is validated against a set of numerical and experimental benchmark tests, demonstrating the efficiency and accuracy of the modeling framework for CCUS-related subsurface applications. Important physical phenomena resulting from the complex thermodynamic interactions of CO2 and impurities with reservoir fluids can be accurately captured now in detailed dynamic simulation. The investigated simulation scenarios include a reproduction of lab experiments at the core scale, investigation of macro-scale analog model and simulation of large-scale industrial application. The simulation time can also span from hours to years among various applications. Complex thermal-compositional-reactive phenomena can be addressed at each of these space and time scales. The unified thermodynamic description allows us to perform all these simulations for a reasonable CPU time due to advanced parametrization techniques and efficient GPU capabilities in our in-house reservoir simulator DARTS.
A GPU-Accelerated Simulator for Challenging Extreme-Scale Geomechanical Models
Authors: Frigo Matteo , Isotton Giovanni , Janna Carlo , Spiezia Nicolò , Ferronato Massimiliano , Franceschini Andrea , Filippini Annachiara , Scrofani Giovanni 
Published: March 2023

Abstract
Simulation software is a very common tool to model geomechanical problems since direct measurements are extremely expensive and usually unfeasible. In addition, there is an increasing interest in simulating past events and forecasting future ones. Very fine meshes are needed to provide a realistic representation of complex stratigraphy. Hence the full exploitation of modern HPC infrastructure is mandatory. In this work, a fully parallel GPU-accelerated simulator for extreme-scale models is presented and its performance is assessed through a real basin scale model that is used as benchmark.
A Physics-Informed Neural Network for Temporospatial Prediction of Hydraulic-Geomechanical Processes
Authors: Zhang Chi , Wang Shihao , Wu Yu-Shu 
Published: March 2023

Abstract
This work aims to quantify the temporal and spatial evolution of pressure and stress fields in poroelastic reservoirs by replacing the conventional reservoir-geomechanical simulators with a novel convolutional-recurrent network (CNN-RNN) proxy. The proposed convolutional-recurrent neural network uses the governing equations of the coupled hydraulic-geomechanical process as the loss function. Initial conditions and spatial rock property fields are taken as inputs to predict the variation of pressure and stress fields. A customized convolutional filter mimicking the higher-order finite difference approach is adopted to improve the solution accuracy of the network.
We apply the neural network to solve one synthetic 2D hydraulic-geomechanical problem. The pressure and stress fields predicted from our neural network are compared with the reference numerical solutions derived from the finite difference method. The performance exhibits the potential of the proposed deep learning model for hydraulic-geomechanical processes simulation. The predicted pressure field displays a high degree of accuracy up to 95%, while the error in stress prediction is slightly higher due to the limitation of the current adopted neural network. In particular, our model outperforms the traditional second-order finite difference method in both speed and accuracy. Overall, the work shows the capability of the neural network to capture temporospatial prediction in hydraulic-geomechanical processes.
Pressure Jump Stabilization for Compositional Poromechanics on Unstructured Meshes
Authors: Aronson Ryan , Hamon Francois , Castelletto Nicola , White Joshua , Tchelepi Hamdi 
Published: March 2023

Abstract
While commonly used in practice for large-scale simulation of coupled subsurface flow and displacement, discretizations in which the solid matrix displacement is represented using linear, nodal elements and flow variables are represented as piecewise constants over each cell are not inherently inf-sup stable. This means that when undrained and incompressible conditions are approached, spurious pressure oscillations will appear in the numerical solution. This is particularly relevant in simulations of carbon sequestration, where the caprock above the injection location should be nearly impermeable. In this work we extend the idea of pressure jump stabilization to the compositional poromechanics setting in order to suppress these spurious oscillations. We apply this method to simulations of CO2 injection into a synthetic aquifer which is represented using a fully unstructured mesh. The results show that the stabilization is effective at smoothing the pressure field without adversely affecting the prediction quality of other quantities of interest.
Efficient Adaptation and Calibration of Ad	joint-Based Reduced-Order Coarse-Grid Network Models
Authors: Krogstad S. , Klemetsdal Ø. A. , Lie K. -A. 
Published: March 2023

Abstract
Network models have proved to be an efficient tool for building data-driven proxy models that match observed production data or reduced-order models that match simulated data. A particularly versatile approach is to construct the network topology so that it mimics the intercell connection in a volumetric grid. That is, one first builds a network of "reservoir nodes" to which wells can be subsequently connected. The network model is realized inside a fully differentiable simulator. To train the model, we use a standard mismatch minimization formulation, optimized by a Gauss-Newton method with mismatch Jacobians obtained by solving adjoint equations with multiple right-hand sides. One can also use a quasi-Newton method, but Gauss-Newton is significantly more efficient as long as the number of wells is not too high. A practical challenge in setting up such network models is to determine the granularity of the network. Herein, we demonstrate how this can be mitigated by using a dynamic graph adaption algorithm to find a good granularity that improves predictability both inside and slightly outside the range of the training data.