bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using new chemical methods to control water production in oil reservoirs: comparison of mechanical and chemical methods
Authors: Seifi Fatemeh , Haghighat Farshad , Nikravesh Hamed , Kazemzadeh Yousef , Azin Reza , Osfouri Shahriar 
Published: July 2024

AbstractEffective water management in oil reservoirs is crucial for maximizing hydrocarbon recovery while minimizing environmental degradation. This paper investigates the potential of innovative chemical techniques to control water production in oil reservoirs and compares these methods with traditional mechanical strategies. By reviewing over 70 case studies extensively, this research provides a detailed evaluation of different approaches to managing water cut. The study reveals that chemical methods, particularly those utilizing advanced polymer-based gels, are generally more effective than mechanical techniques. These methods are especially advantageous in settings with high water cuts and geologically complex reservoirs. Chemical treatments provide greater adaptability and cost-efficiency, significantly reducing the environmental impact compared to mechanical approaches. The primary aim of this research is to analyze the sources of water cut and evaluate common water shutoff operations to enhance reservoir management based on specific challenges, reservoir characteristics, and economic considerations. Our findings suggest using a two-step strategy: starting with mechanical control methods and then applying chemical treatments specifically designed for the reservoir’s unique physical properties. This not only improves oil recovery rates but also enhances economic efficiency by extending the reservoirs’ lifespan. Future research should focus on developing cost-effective, environmentally friendly chemical solutions suitable for various geological settings. Such advancements could significantly refine water management practices in oil fields, leading to better economic and environmental outcomes.
Psychobiological responses to choir singing and creative arts activities in children and adolescents with mental disorders: results of a pilot study
Authors: Grebosz-Haring Katarzyna , Thun-Hohenstein Leonhard 
Published: July 2024

Summary
Background
Children and adolescents living with mental health problems often experience stress and poor mood states, which may influence their quality of life and well-being. Arts interventions may improve mood and well-being and reduce physiological stress in this vulnerable population.

Methods
A cohort of patients in child and adolescent psychiatry (N = 42; age range: 12–18 years) participated in one of four arts activities including choir singing (n = 11), textile design (n = 9), drama (n = 16), and clownery (n = 6). They were led by professional artists and delivered through five consecutive 90-min daily afternoon sessions over the course of 1 week. Questionnaires of mood and saliva samples before and after each session served to assess short-term psychobiological changes. In addition, patients reported their quality of life and well-being at the beginning and at the end of the 1‑week program.

Results
Results showed that alertness was significantly enhanced after textile design (∆post–pre = 4.08, 95% CI [0.77, 7.39]) and after singing (∆post–pre = 2.20, 95% CI [−0.55, 4.94]). Moreover, mood tended to be positively affected by textile design (∆post–pre = 2.89, 95% CI [−0.39, 6.18]). Quality of life increased significantly after singing (∆post–pre = 5.49, 95% CI [1.05, 9.92]). Arts participation except singing was associated with significant reductions in salivary cortisol (sCort) (textile design ∆post–pre = −0.81 ng/mL, 95% CI [−1.48, −0.14]; drama ∆post–pre = −0.76 ng/mL, 95% CI [−1.28, −0.24]; clownery ∆post–pre = −0.74 ng/mL, 95% CI [−1.47, −0.01]). No significant changes were observed for well-being over the whole program and salivary immunoglobulin A (sIgA) after any of the arts activities.

Discussion
These results suggest that arts participation can improve mood state and reduce stress in young people with mental disorders, but there is a need for further studies.
Combining 3D printing of copper current collectors and electrophoretic deposition of electrode materials for structural lithium-ion batteries
Authors: Martinez Ana C. , Maurel Alexis , Yelamanchi Bharat , Talin A. Alec , Grugeon Sylvie , Panier Stéphane , Dupont Loic , Aranzola Ana , Schiaffino Eva , Sreenivasan Sreeprasad T. , Cortes Pedro , MacDonald Eric 
Published: July 2024

AbstractServing as a proof of concept, additive manufacturing and electrophoretic deposition are leveraged in this work to enable structural lithium-ion batteries with load-bearing and energy storage dual functionality. The preparation steps of a complex 3D printed copper current collector, involving the formulation of a photocurable resin formulation, as well as the vat photopolymerization process followed by a precursors-based solution soaking step and thermal post-processing are presented. Compression and microhardness testing onto the resulting 3D printed copper current collector are shown to demonstrate adequate mechanical performance. Electrophoretic deposition of graphite as a negative electrode active material and other additives was then performed onto the 3D printed copper collector, with the intention to demonstrate energy storage functionality. Half-cell electrochemical cycling of the 3D multi-material current collector/negative electrode versus lithium metal finally demonstrates that structural battery components can be successfully obtained through this approach.
The virtual stress boundary method to impose nonconforming Neumann boundary conditions in the material point method
Authors: Given Joel , Liang Yong , Zeng Zhixin , Zhang Xiong , Soga Kenichi 
Published: July 2024

AbstractThe material point method (MPM) is a popular and powerful tool for simulating large deformation problems. The hybrid Eulerian–Lagrangian nature of the MPM means that the Lagrangian material points and the Eulerian background mesh are often nonconforming. Once the material and mesh boundaries become misaligned, imposing boundary conditions, such as Neumann boundary conditions (i.e., traction), becomes a challenge. The recently developed virtual stress boundary (VSB) method allows for imposing nonconforming Neumann boundary conditions without explicit knowledge of the boundary position. This is achieved through a problem transformation where the original boundary traction problem is replaced by an equivalent problem featuring a virtual stress field. This equivalent problem results in updated governing equations which are ultimately solved using a combination of particle-wise and cell-wise quadrature. In the current work, a modification to the VSB method is proposed to eliminate the need for cell-wise quadrature. Despite removing cell-wise quadrature, the modified VSB method maintains the accuracy observed in the original approach. Several numerical examples, including 1D and 2D benchmark problems, as well as a 3D demonstration problem, are presented to investigate the accuracy and illustrate the capability of the modified VSB method. Mesh refinement studies are included to show the method’s good convergence behavior.
Tree Branch Characterisation from Point Clouds: a Comprehensive Review
Authors: Hartley Robin J. L. , Jayathunga Sadeepa , Morgenroth Justin , Pearse Grant D. 
Published: July 2024

Abstract
Purpose of Review
Since the late 1990s, researchers have been increasingly utilising digital methodologies to assess the branch structure of trees. The emergence of commercial terrestrial laser scanners during this period catalysed an entirely new domain focused on point cloud-based research. Over the years, this field has transformed from a complex computational discipline into a practical tool that effectively supports research endeavours. Through the combined use of non-destructive remote sensing techniques and advanced analytical methods, branch characterisation can now be carried out at an unprecedented level.

Recent Findings
While terrestrial laser scanning has traditionally been the dominant methodology for this research domain, the increased use of mobile laser scanners and unmanned aerial vehicles indicates a transition towards more mobile platforms. Quantitative structural modelling (QSM) has been pivotal in advancing this field, enhancing branch characterisation capabilities across diverse fields. The past five years have seen increased uptake of 2D and 3D deep learning techniques as alternatives.

Summary
This article presents a comprehensive synthesis of approximately 25 years of research in the field of digital branch characterisation, reviewing the data capture technologies and analytical methods, along with the forest types and tree species to which these technologies have been applied. It explores the current trends in this dynamic field of research, research gaps and some of the key challenges that remain within this field. In this review, we placed particular emphasis on the potential resolution of the significant challenge associated with occlusion through the utilisation of mobile technologies, such as mobile laser scanners and unmanned aerial vehicles. We highlight the need for a more cohesive method for assessing point cloud quality and derived structural model accuracy, and benchmarking data sets that can be used to test new and existing algorithms.
Rdfinet: reference-guided directional diverse face inpainting network
Authors: Chen Qingyang , Qiang Zhengping , Zhao Yue , Lin Hong , He Libo , Dai Fei 
Published: July 2024

AbstractThe majority of existing face inpainting methods primarily focus on generating a single result that visually resembles the original image. The generation of diverse and plausible results has emerged as a new branch in image restoration, often referred to as “Pluralistic Image Completion”. However, most diversity methods simply use random latent vectors to generate multiple results, leading to uncontrollable outcomes. To overcome these limitations, we introduce a novel architecture known as the Reference-Guided Directional Diverse Face Inpainting Network. In this paper, instead of using a background image as reference, which is typically used in image restoration, we have used a face image, which can have many different characteristics from the original image, including but not limited to gender and age, to serve as a reference face style. Our network firstly infers the semantic information of the masked face, i.e., the face parsing map, based on the partial image and its mask, which subsequently guides and constrains directional diverse generator network. The network will learn the distribution of face images from different domains in a low-dimensional manifold space. To validate our method, we conducted extensive experiments on the CelebAMask-HQ dataset. Our method not only produces high-quality oriented diverse results but also complements the images with the style of the reference face image. Additionally, our diverse results maintain correct facial feature distribution and sizes, rather than being random. Our network has achieved SOTA results in face diverse inpainting when writing. Code will is available at https://github.com/nothingwithyou/RDFINet.
Identification of sliding surface and classification of landslide warning based on the integration of surface and deep displacement under normal distribution theory
Authors: Wang Dong , Wang Yanting , Li Guanghe , Wang Laigui , Zhou Zhiwei , Du Yongzhi , Ding Chunjian 
Published: July 2024

AbstractAdvanced identification of the potential sliding surface of a slope and accurate early warning are crucial prerequisites for effective management of landslides and timely and prevention of catastrophic accidents. This study analyzes the statistical characteristics of landslide displacement evolution. Based on the normal distribution theory, random variables of displacement velocity and acceleration with random errors are introduced into the analysis of surface displacement information, and random variables of relative displacement with random errors are introduced into the analysis of deep displacement information. When the random variables do not follow the normal distribution, the warning time can be obtained. Therefore, an advanced landslide classification warning method is established. The analysis results showed that analysis results from the April 30 landslide project at an open pit mine indicate that the earliest warning time for landslide initiation is 2020/2/19, while the earliest warnings for acceleration occur on 2020/4/15 and the fast acceleration on 2020/4/25. These three-level warning times align with reality, and the inferred slip surface position corresponds to the actual weak layer range. The primary power source driving landslide originates from behind the sliding body which subsequently pushes rock mass along weak layers near the south wing, north wing, and front in succession. Research findings can enhance landslide warning accuracy, facilitate advance identification of sliding surface, provide scientific basis for open-pit slope engineering design, as well as mitigate casualties and property losses.
A Survey of Controller Placement Problem in SDN-IoT Network
Authors: Abderrahmane Amel , Drid Hamza , Behaz Amel 
Published: July 2024

AbstractThe Internet of Things (IoT) refers to the billions of intelligent physical devices connected to the Internet for collecting and sharing data. However, implementing IoT in large-scale industrial applications presents numerous challenges, including network management and scalability. These challenges encompass: complex network management tasks that are increasingly difficult to maintain, increased network resource usage, mobility, and high energy consumption. Software-defined networking (SDN) addresses these limitations by enforcing centralized control of all devices and leveraging a global network view. SDN is a networking paradigm that separates the control plane from the data plane, allowing managers to centralize the control of the network infrastructure. For large networks, such as IoT networks, multiple controllers are needed to manage the network efficiently. The Controller Placement Problem (CPP) involves the challenge of deploying the optimal number of controllers in a network while satisfying specific performance requirements such as latency, load balancing, and computation time. This paper provides an overview of recent research efforts addressing CPP issues in the SDN-IoT domain.
Process science: the interdisciplinary study of socio-technical change
Authors: Brocke Jan vom , van der Aalst Wil M. P. , Berente Nicholas , van Dongen Boudewijn , Grisold Thomas , Kremser Waldemar , Mendling Jan , Pentland Brian T. , Roeglinger Maximilian , Rosemann Michael , Weber Barbara 
Published: July 2024

AbstractProcess science is the interdisciplinary study of socio-technical processes. Socio-technical processes involve coherent series of changes over time, entailing actions and events that include humans and digital technologies. The ubiquitous availability of digital trace data, combined with advanced data analytics capabilities, offer new and unprecedented opportunities to study such processes through multiple data sources. Process science is concerned with describing, explaining, and intervening in socio-technical change. It is based on four key principles; it (1) puts socio-technical processes at the center of attention, (2) investigates socio-technical processes scientifically, (3) embraces perspectives of multiple disciplines, and (4) aims to create impact by actively shaping the unfolding of socio-technical processes.
Pattern of diseases in medical wards of a tertiary care hospital of Lahore: a retrospective study
Authors: Rahim Arzoo , Khurshid Nadia , Mukhtar M. Umer 
Published: July 2024

Abstract
Aim
The study was conducted to determine the frequency of different diseases encountered in a medical ward of a tertiary care hospital.

Subject and methods
This was a cross-sectional study carried out in the Department of Medicine at Mayo Hospital Lahore using medical records of admitted patients from September to November 2021.

Results
A total of 381 patients were included in the study. The age group with the highest admission was 56–60 years. Decompensated Chronic Liver Disease was the most common disease (19.4%), followed by Ischemic Heart Disease (17.3%), Septic shock/Septicemia (9.4%), Cerebrovascular Accident (8.4%), Meningoencephalitis (7.3%) & Chronic Kidney Disease (6.6%).

Conclusion
Knowledge about the most prevalent diseases in medical wards can help guide future policy making & better management of diseases on a day to day basis.
Convergence of hybrid slice sampling via spectral gap
Authors: Łatuszyński Krzysztof , Rudolf Daniel 
Published: July 2024

AbstractIt is known that the simple slice sampler has robust convergence properties; however, the class of problems where it can be implemented is limited. In contrast, we consider hybrid slice samplers which are easily implementable and where another Markov chain approximately samples the uniform distribution on each slice. Under appropriate assumptions on the Markov chain on the slice, we give a lower bound and an upper bound of the spectral gap of the hybrid slice sampler in terms of the spectral gap of the simple slice sampler. An immediate consequence of this is that the spectral gap and geometric ergodicity of the hybrid slice sampler can be concluded from the spectral gap and geometric ergodicity of the simple version, which is very well understood. These results indicate that robustness properties of the simple slice sampler are inherited by (appropriately designed) easily implementable hybrid versions. We apply the developed theory and analyze a number of specific algorithms, such as the stepping-out shrinkage slice sampling, hit-and-run slice sampling on a class of multivariate targets, and an easily implementable combination of both procedures on multidimensional bimodal densities.
Assessing Subsurface Gas Storage Security for Climate Change Mitigation and Energy Transition
Authors: Pan Ziqing , Jin Zhijun , Li Gensheng , Zhang Kaiqiang 
Published: July 2024

AbstractSubsurface gas storage is crucial for achieving a sustainable energy future, as it helps to reduce CO2 emissions and facilitates the provision of renewable energy sources. The confinement effect of the nanopores in caprock induces distinctive thermophysical properties and fluid dynamics. In this paper, we present a multi‐scale study to characterize the subsurface transport of CO2, CH4, and H2. A nanoscale‐extended volume‐translated Cubic‐Plus‐Association equation of state was developed and incorporated in a field‐scale numerical simulation, based on a full reservoir‐caprock suite model. Results suggest that in the transition from nanoscale to bulk‐scale, gas solubility in water decreases while phase density and interfacial tension increase. For the first time, a power law relationship was identified between the capillary pressure within nanopores and the pore size. Controlled by buoyancy, viscous force and capillary pressure, gases transport vertically and horizontally in reservoir and caprock. H2 has the maximum potential to move upward and the lowest areal sweep efficiency; in short term, CH4 is more prone to upward migration compared to CO2, while in long term, CH4 and CO2 perform comparably. Thicker caprock and larger caprock pore size generally bring greater upward inclination. Gases penetrate the caprock when CH4 is stored with a caprock thickness smaller than 28 m or H2 is stored with a caprock pore size of 2–10 nm or larger than 100 nm. This study sheds light on the fluid properties and dynamics in nanoconfined environment and is expected to contribute to the safe implementation of gigatonne scale subsurface gas storage.
Radial and Vertical Structures of Plasma Disk in Jupiter's Middle Magnetosphere
Authors: Wang Jian‐Zhao , Bagenal Fran , Wilson Robert J. , Nerney Edward , Ebert Robert W. , Valek Philip W. , Allegrini Frederic 
Published: July 2024

AbstractThe Juno mission flew through the plasma disk near the equator in Jupiter's magnetosphere frequently. We identify 274 plasma disk crossings of Juno between 10 and 40 RJ from PJ5 to PJ44. Using a forward modeling method that combines the JADE‐I time‐of‐flight and SPECIES data sets, we perform a survey of ion properties in the plasma disk. Ions are heated from 1.5 to 6 keV between 15 and 30 RJ. Density and temperature are locally anti‐correlated. Assumed to be related to centrifugal instabilities, cold, dense plasma are commonly observed near midnight. Plasma corotates around Jupiter and the rigid corotation breaks down outside 15–20 RJ. The plasma bulk velocity increases from the post‐dusk sector to the pre‐dawn sector featuring injection flows in the pre‐dawn sector, which is consistent with the Vasyliunas cycle. Strong outflows (>100 km/s) are commonly observed outside 20 RJ and the average radial velocity increases with radial distance. The ion abundance changes between 10 and 18 RJ and that might indicate plasma sources and/or sinks near Europa and Ganymede. The vertical distribution of ions is controlled by the balance between centrifugal, pressure gradient, and ambipolar electric field forces. An example near the M‐shell of 13.5 shows that average plasma temperature increases by a factor of 10 from the disk center to edge, because cold ions are more confined near the equator. Lighter ions with higher charge states have more mobility along the field line and have larger scale heights. The observations are compared with multi‐species diffusive equilibrium model.
A Novel Model of Hydraulic Aperture for Rough Single Fracture: Insights From Fluid Inertial and Fracture Geometry Effects
Authors: Zhang Shuai , Liu Xiaoli , Wang Enzhi , Qian Ruipeng , Wang Mingyang , Ma Qing 
Published: July 2024

AbstractPrevious studies pointed out that the hydraulic aperture (bh) is solely dependent on the geometric features of a fracture, independent of fluid inertia effects. Here we present an inertial hydraulic aperture (bih) that considers the fluid inertial effect and fracture geometry effect by massive direct numerical simulations of fluid flow in real and artificial 3‐D fractures. Simulation results indicate that with an increase in Reynolds number (Re), the evolution eddy volume ratio exhibits three distinct stages: stable stage (Re < 1), fluctuating stage (1 ≤ Re ≤ 10), and increasing to stable stage (Re > 10). These stages correspond to the transition of flow regimes from the viscous Darcy regime to the weak inertia regime, and further developing into the strong inertia regime. Among them, Re = 1 can be considered as the critical point for the onset of the non‐Darcy flow. Furthermore, As Re increases, the evolution of bih exhibits four stages influenced by fluid inertia effects and main flow width in the fracture: stability, slight increase, slight decrease, and rapid increase. Then, based on 892 sets of simulation results (Re ≥ 1), the expression of bih was obtained using Gene Expression Programming. Compared to the four existing empirical models of bh, the present bih exhibits the highest accuracy and the lowest errors (R2 = 0.994, MAE = 0.008, RMSE = 0.013). Finally, the proposed bih is further employed to modify the Forchheimer equation. This study enhances the understanding of hydraulic conductivity in 3‐D rough single fractures.