bluuebunny/crossref_metadata_2025_split huggingface dataset:
Completion Design Optimization as a Function of Reservoir Quality in Tight Reservoirs: A Big Data Approach
Authors: Moussa Tamer , Dehghanpour Hassan 
Published: December 2024

Summary
Over the past decade, more than 40,000 multifractured horizontal wells (MFHWs) were completed in the Western Canada Sedimentary Basin (WCSB), making Canada the third largest oil exporter in 2022. However, this process consumed more than 56 billion gallons of water, with more than 30 billion gallons unrecovered—equivalent to the annual water consumption of a city of 1 million for nearly 5 years. This raises concerns about water use efficiency in fracturing operations. Can big data mining reveal the relationship between reservoir quality, fracturing design parameters, and process efficiency? This research aims to develop a hybrid analytical and machine learning (ML) workflow to optimize completion design as a function of reservoir quality in tight reservoirs.
To achieve this objective, we analyze data from more than 14,000 wells in the Montney formation. Using core analysis and well log data, we develop a support vector machine (SVM) to predict permeability and a fuzzy clustering model to estimate fracturability. We categorize Montney’s lithology through hierarchical clustering. With 3D kriging interpolation, we fill missing data and create high-resolution 3D petrophysical maps, which help derive a reservoir quality index (RQI) map to identify the sweet spots for completing new wells. We introduce a stage placement efficiency (SPE) metric to evaluate fracture stage placements in-line with the RQI. Finally, we develop neural network–based proxies that predict well performance based on reservoir quality, geomechanical properties, and completion design, incorporating more than 40 completion parameters, the RQI, and historical production data.
The results reveal a higher degree of homogeneity in the upper Montney compared to the middle and lower segments. Generally, completion design parameters significantly impact MFHW productivity more than formation characteristics. Applying the proposed proxy to Montney-oil MFHWs could increase fracturing water recovery by 94.4%, reduce injected water volume by 22%, and boost cumulative oil production by 37.9%. The proxy aims to enhance fracturing water efficiency. A 1% reduction in freshwater consumption in the WCSB could save more than 100 million gallons of fresh water and cut CO2 emissions by up to 2,000 tons, equivalent to removing more than 1,000 gasoline cars from Canadian roads.
Numerical Simulation Study of 3D Crosswell Measurement for Hydraulic Fracture Zone Diagnostics in Steel-Cased Boreholes
Authors: Wu Shiwei , Liu Dejun , Li Yang , Meng Jin 
Published: December 2024

Summary
Electrical signals in the vicinity of excited steel-cased borehole sources offer significant potential for monitoring fracture zones filled with highly conductive proppant. However, despite this potential, it is difficult to accurately monitor fracture zones in steel-cased boreholes due to various challenges, such as interference from background noise and the complexity of the geological environment. To address these challenges, we propose a novel crosswell measurement method specifically designed for diagnosing hydraulic fracture zones in steel-cased boreholes. During dynamic monitoring of fracturing, high-power direct current (DC) is applied to the steel-cased borehole, and the potential on the other open borehole is measured. This method uses a 3D finite element algorithm to establish a fracture detection model, and its accuracy has been verified by comparing the results with a benchmark model. Furthermore, the relationships between the geometric parameters of both fracture zones and boreholes, and the obtained measurement signals, are investigated. To evaluate the effectiveness of our proposed method in complex underground conditions, a case study is conducted. Numerical results indicate that the measurement signals are highly sensitive to a fracture’s size, thickness, and conductivity but less so to its shape. Moreover, whenever feasible, minimizing the distance between the measurement line and the asymmetrical fracture zone is essential for improving signal quality. In a case study focusing on segmented-fracturing monitoring, the signal difference observed before and after hydraulic fracturing clearly reveals the orientation of fracture zones during the fracturing process. This study demonstrates that the crosswell measurement method is an effective technique for dynamically monitoring hydraulic fracturing in steel-cased boreholes and holds promising applications.
Anisotropic Response Characteristics of Array Induction Logging in Laminated Shale and Its Correction Methods
Authors: Zhao Jun , Pei HaoChen , Luo Li , Huang Yi , Wu ZhenGuan , Jia Jiang 
Published: December 2024

Summary
The lamination characteristics of shale are one of the sources of anisotropy in shale reservoir resistivity, with significant differences in horizontal and vertical resistivity, and usually with vertical resistivity greater than horizontal resistivity. Therefore, the resistivity anomaly caused by anisotropy in horizontal wells of shale reservoirs seriously interferes with the logging evaluation of shale reservoirs. Based on the 3D finite element method, the electromagnetic field distribution of array induction logging was simulated, and the influence of resistivity, anisotropy, and well inclination angle on resistivity in laminated shale formations was analyzed. A resistivity correction chart was constructed using the sensitivity differences of each subarray of array induction logging in anisotropic formations. Finally, resistivity anisotropy correction is achieved based on actual logging data. Research has shown that in anisotropic formations of horizontal wells, the effects of formation resistivity, anisotropy, and well inclination angle on each subarray of array induction logging are different, resulting in significant deviations between the measured resistivity values and the actual formation resistivity values. Through the construction of resistivity correction charts with different sensitivities of each subarray, anisotropy correction was performed on the actual well data. The corrected resistivity can approximately represent the horizontal resistivity of the reservoir, laying the foundation for evaluating shale reservoirs using resistivity data.
Flavonoid GL-V9 suppresses development of human hepatocellular cancer cells by inhibiting Wnt/β-Cantenin signaling pathway
Authors: Gu Ye , He Qiaoxian , Xie Lu , Chen Fangfang , Jin Hangbin , Lou Lilan , Zhang Xiaofeng 
Published: December 2024

Abstract

Distant metastasis and post-operative recurrence of tumours are the main causes of death in patients with liver cancer. In recent years, flavonoids have been found to achieve effective anticancer effects by inhibiting cancer cell proliferation and inducing apoptosis, inhibiting cancer cell invasion and metastasis and neovascularization. GL-V9 is a newly synthesized flavonoid that has demonstrated anticancer effects in a variety of tumors[1, 2, 3], but its anticancer effects in HCC and its related mechanisms are still unclear. In this study, we investigated the anti-proliferative, anti-invasive and anti-migratory activities of GL-V9 in HCC cells by MTT method cell proliferation assay, plate cloning assay, transwell invasion assay and cell scratching assay. Based on the results, we found that GL-V9 inhibits the EMT process through a pathway that inhibits Wnt/β-Cantenin pathway signaling,thereby reducing the proliferation, migration and invasion ability of HCC cells. Therefore, GL-V9 may be a novel potential therapeutic agent to inhibit HCC cell metastasis.
Comparison of MRI findings for predicting massive hemorrhage during cesarean section in patients with placental malposition: partial placental volume of lower uterine segment is an accurate and objective indicator
Authors: Kuwamura Hiroshi , Terayama Takero , Hamabe Fumiko , Edo Hiromi , Matsuda Kenta , Miyamoto Morikazu , Takano Masashi , Shinmoto Hiroshi 
Published: December 2024

Abstract

Purpose
To comprehensively compare the diagnostic ability and inter-reader agreement of magnetic resonance imaging (MRI) findings for predicting massive hemorrhage after cesarean section in patients with placental malposition, aiming to identify the most reliable and objective indicators.
Methods
Totally, 148 consecutive patients with placental malposition underwent MRI and cesarean section at our hospital between January 2014 and July 2021. The patients were divided into massive and non-massive hemorrhage groups. MRI findings of placenta accreta, placental position, and placental volume were evaluated by two radiologists, and inter-reader agreement was calculated. Diagnostic ability for predicting massive hemorrhage was evaluated using receiver operating characteristic analysis.
Results
Intraplacental T2 dark bands (100% vs. 58.2%, p = 0.001), placental bulge (50% vs. 3.7%, p < 0.001), loss of retroplacental T2 hypointense line (100% vs. 67.2%, p = 0.01), myometrial thinning (92.9% vs. 57.5%, p = 0.009), total placenta previa (64.3% vs. 23.9%, p = 0.033), and anterior placenta (35.7% vs. 10.5%, p = 0.02) were significantly observed in massive hemorrhage group. Partial placental volume of lower uterine segment (PVpartial) was larger in massive hemorrhage group (166 [108–214] cm3 vs. 70 [43–112] cm3 p < 0.001), had the second highest intraclass correlation coefficient (0.84), and had the highest area under the curve (0.81) for diagnosing massive hemorrhage.
Conclusion
This study revealed PVpartial is an accurate and objective indicator for massive hemorrhage, independent of radiologists’ experience. This indicator potentially enables prediction of massive hemorrhage, improving pre-operative planning in high-risk pregnancies.
Air pollution control measures improved photosynthesis in urban trees while the COVID-19 pandemic did not
Authors: Matsuura Takumi , Okamoto Yousuke , Matsumoto Mayu , Kiyomizu Takashi , Kumpitsch Luisa , Kume Atsushi , Hanba Yuko T. 
Published: December 2024

Abstract

One of the major stresses affecting tree photosynthesis in urban areas is phytotoxic air pollutants such as atmospheric nitrogen dioxide (NO2). We clarified the relationship between NO2 concentrations and photosynthetic function for three major urban trees in Kyoto and surrounding cities. High NO2 increased long-term water use efficiency and decreased photosynthesis in two urban trees, Prunus × yedoensis and Rhododendron pulchrum. We then focused on the decrease in NO2 due to (1) air pollution control measures in the years from 2005 to 2023 and (2) the economic recession caused by the COVID-19 pandemic, and examined whether these factors improved photosynthesis in urban trees. The historic decrease in NO2 improved leaf photosynthesis, while the COVID-19 pandemic reduced NO2 by only 0.3 ppb and did not further improve photosynthesis in the two urban tree species. This report shows that air pollution control measures improved photosynthesis in urban trees over several years in Japan, and is valuable because it demonstrates that air pollution control measures can increase CO2 uptake by urban trees.
The effect of circuit training on muscle synthesis’s indices, neurotrophic factors, and physical fitness in elderly women: A randomized controlled trial
Authors: Baharavar Fatemeh , Vakili Javad , Sari-Sarraf Vahid , Pourmanaf Hadi 
Published: December 2024

Abstract

Background
Regular physical activity can improve muscle synthesis, cognitive function, and physical fitness and consequently delay the side effects of aging. However, the effect of circuit training, which improves multiple components of physical fitness, is still unknown. Therefore, this study aimed to evaluate the effect of 8 weeks of a mixed circuit training on serum levels of muscle synthesis indices, neurotrophic factors, and physical fitness in elderly women.
Methods
A total of 24 healthy elderly females (age 65 ± 3 years) were recruited and randomly divided into two groups as follows: Mixed Circuit Training (MCT, n = 12) and Control (C, n = 12). Participants in the MCT group performed circuit training (three times a week at an intensity of 40–60% of 1 repetition maximum) for 8 weeks. Participants in the C group did not received any intervention. Serum levels of growth hormone (GH), Insulin-like growth factor-1 (IGF_1), brain derived neurotrophic factor (BDNF), nerve growth factor (NGF), and physical fitness (cardiovascular fitness, muscular endurance, and balance) were measured before and after the eight weeks of intervention.
Results
Serum levels of GH, IGF-1, BDNF, and, NGF were increased in the MCT group after eight weeks (p ˂0.001). Cardiovascular fitness, muscular endurance, and balance were also improved in the MCT group after eight weeks of intervention (p ˂0.001).
Conclusions
A mixed circuit training could improve muscle synthesis, neurotrophic factors, and physical fitness in elderly women. To confirm these results, further studies are recommended.
Trial registration
Retrospectively registered. IRCT20240108060648N1. Registration date: 2024/02/12. URL: https://irct.behdasht.gov.ir/search/result?query=IRCT20240108060648N1
SN2-Mediated Decoupled Precursor Provision Enables Large-Scale Production of Monodisperse Lead Halide Perovskite Quantum Dots in a Single Reactor
Authors: Kim Jigeon , Kim Woongchan , Jang Jin Il , Kim Wooyeon , Yoo Doheon , Choi Min-Jae , Choi Jongmin , Kim Hyung Min , Cho Sung Beom , Ko Min Jae , Kim Younghoon 
Published: December 2024

Abstract

Quantum-confined lead-halide perovskite nanocrystals (QPNCs) are a promising optoelectronic semiconductor owing to their exceptional fluorescence and the size- and dimension-tunable optical properties. QPNCs having low formation energy encounter challenges in accurately regulating the nucleation and crystal growth stages during injection-based syntheses using lead halide reagents. Here, we introduce a non-injection, one-pot synthetic approach based on bimolecular nucleophilic substitution (SN2) and thermolysis reactions of the decoupled metal and halide precursors for the large-scale production of monodisperse CsPbX3-QPNCs (X = Cl, Br, I). This approach facilitates a homogeneous supply of halide anions and metal cations, enabling the precise control over the nucleation and crystal growth stages in the isolated size-focused region. Monodisperse CsPbX3-QPNCs achieve high color purity across the RGB color gamut by adjusting size, dimensionality, and halide composition, and can be produced on an ultra-large scale.
Federated Learning for Sustainable IoT Appliance Load Monitoring at the Edge Devices
Authors: Wadhwa Gitanjali , Natarajan Yuvaraj , Pree ⁠K.R. Sri , Gopinath M.P. , Devi M. Shyamala 
Published: December 2024

Abstract

Non-intrusive Appliance Load Monitoring (NALM) is an essential technique that enables tracking of household appliances' electricity usage, promoting eco-friendly practices and reducing energy monitoring costs. However, NALM implementation can be challenging due to privacy concerns, particularly in real-world applications. Federated learning is a promising solution that enables load monitoring model training and sharing while ensuring data security. Nevertheless, federated learning for NALM still faces various challenges, such as limited resources, edge model personalization, and scarcity of training data. In this paper, we propose a practical federated learning framework for NALM that addresses these challenges. Our approach utilizes collaborative data aggregation over federated learning, cloud-based model compression through filter pruning, and personalized edge and multi-task learning model building with unsupervised transfer learning techniques. Our experimental results, conducted using real energy data, demonstrate that our proposed load monitoring model achieves highly accurate personalized energy disaggregation, making it a state-of-the-art approach for non-intrusive appliance load monitoring at the edge client. By using our federated learning-based load monitoring model, we can minimize energy consumption while maintaining high learning performance and preserving user privacy. Future research could focus on further development and research to improve the efficiency of federated learning implementation and address remaining challenges in real-world NALM applications.
Generative Adversarial Networks for High Degree of Freedom Metasurface Designs
Authors: Wang Jiayun , Yao Boyi , Niu Yuanyuan , Ma Jian , Wang Yuanhui , Qu Zeng , Duan Junping , Zhang Binzhen 
Published: December 2024

Abstract

Due to the continuous development of microwave technology and the gradually expanding demand, attention has turned to free-form metasurfaces capable of realizing complex electromagnetic responses. Recent studies have shown that metasurface design can be accelerated and improved with the aid of deep learning methods. Here, we propose a generative adversarial network with raw network framework (RGAN) for realizing inverse design from a given response to a metasurface pattern. With the proposed approach, a metasurface design meeting requirements can be obtained immediately without the need for complex, repetitive iterative processes. Moreover, guided by the agent model within the network, the network is able to maximize exploration of the parameter space, ultimately generating novel designs completely distinct from those in the training set. Simulations demonstrate good spectral response matching. The feasibility of the proposed method is verified through experiments. The RGAN-based inverse prediction framework shows potential in the field of metasurface engineering and can be easily extended to other metasurface application areas, such as optical metamaterials and nanophotonic devices.
Electrospinning Encapsulation of Chlorophylls Microwave-Extracted from Spinach Waste and Utilization as Colouring Agent in Yoghurt
Authors: Isik Beyza Sukran , Bayram Sinan , Altay Filiz 
Published: December 2024

Abstract

Natural colorants have become a developing market because of consumer preferences, and more cost-effective and stable production is necessary. In the present study, a natural green colorant was obtained via microwave-assisted extraction from spinach waste to produce affordable, environmentally-friendly and innovative colorants. The extracts were encapsulated with zein via uniaxial and coaxial electrospinning techniques to overcome the stability issues associated with their natural green color. The encapsulation efficiencies of uniaxially encapsulated chlorophyll extracted from spinach waste by microwave and coaxially encapsulated chlorophyll extracted from spinach waste by microwave were 63.50 and 49.53% for chlorophyll a and 57.18 and 88.58% for chlorophyll b, respectively. The microwave-assisted extraction and addition of eumelanin significantly improved the antioxidant activity and thermal stability of chlorophylls. The stability test against light revealed that 61% of chlorophyll a could be preserved by uniaxial electrospinning. In addition, when chlorophyll-loaded nanofibers were incorporated into yogurt, a more stable green color was achieved during storage.
Research on image steganography based on conditional Invertible Neural Network
Authors: Liang Menghua , Zhao Hongtu 
Published: December 2024

Abstract

To improve the security of image steganography, an image steganography method based on conditional Invertible Neural Network is proposed in this paper. First, we design a conditional Invertible Neural Network to obtain high-quality stego images with rich high-level semantic information and clear spatial details. Based on the conditional directivity of conditional Invertible Neural Network, we can accurately adjust the semantic information of stego image and ensure the controllability of stego image content. We introduce a dual cross-attention module into the network structure. The integration of dual cross-attention modules enhances feature extraction and captures complex image details to improve steganographic accuracy. In addition, the introduction of the convolutional block attention module in the convolutional layer direct the model's focus to key image regions, refining stego image quality. We increase the number of convolutional blocks, which improves the efficiency of feature extraction and reuse. A large number of experiments are carried out on the datasets. For cover and stego image pairs, the PSNR value reached 43.62dB, and for secret and recovery image pairs, the PSNR value reached 46.48dB. Experimental results show that the image quality and security of this method are better than other state-of-the-art image steganography methods.
Effectiveness of vitrectomy with inverted internal limiting membrane flap in the treatment of macular hole retinal detachment in high myopia
Authors: Phan Nguyen Thuy Linh , Nguyen Cong Kiet , Ngo Thanh Tung , Nguyen Lam Vuong , Ho Doan Trang , Le Viet Tung 
Published: December 2024

Abstract

Purpose: This study evaluates the effectiveness of the inverted internal limiting membrane (ILM) flap technique during vitrectomy for treating macular hole-induced retinal detachment (MHRD) in high myopia patients, a challenging complication for vitreoretinal surgeons due to its treatment complexity.
Methods: We conducted a prospective study analyzing 92 eyes diagnosed with MHRD, all undergoing vitrectomy using the inverted ILM flap technique between February 2022 and September 2024. Successful surgery was defined as achieving retinal reattachment, macular hole closure, and improvement in visual acuity by the 12-month postoperative follow-up. Microstructural recovery was assessed using spectral domain optical coherence tomography. Logistic regression analysis was performed to identify prognostic factors of surgical outcome.
Results: Of the 92 eyes, 94.6% achieved retinal reattachment, and 93.5% experienced macular hole closure. Visual acuity significantly improved in 91.3% of cases, with a mean improvement of 0.95 logarithm of the minimum angle of resolution. Recovery rates for the external limiting membrane, the ellipsoid zone, and the cone outer segment tip were 76.1%, 66.3%, and 66.3%, respectively. Larger retinal detachments and macular holes were important predictors of lower surgical success (p < 0.001; p = 0.015, respectively). There was a significant correlation between vision improvement and the recovery of structural integrity and foveal microstructures.
Conclusions: The ILM coverage technique represents a breakthrough in the treatment of MHRD, promoting both anatomical and functional recovery. This approach enhances the management of this complex condition, ultimately improving the quality of life for affected individuals.