bluuebunny/crossref_metadata_2025_split huggingface dataset:
A New Approach of Predicting Fractured Tight Sandstone Reservoir Permeability Based on Electrical Image Logging
Authors: Li Gaoren , Yan Ronghui , Liu Tianding , Sun Xiaoping , Li Jiaqi , Xiao Liang 
Published: March 2024

Abstract
Permeability is an important input parameter in Tight reservoir characterization and evaluation, precisely predicting formation permeability is indispensable. However, permeability prediction faces great challenge in tight sandstone reservoirs, empirical statistical methods, and nuclear magnetic resonance (NMR) based models lose their role due to complicated pore structure and the effect of methane gas (CH4) or hydrocarbon to NMR responses. In addition, fractures also play important role in improving tight reservoir permeability, whereas current logging responses cannot be used to characterize this improvement besides electrical image logging. In this study, to quantitatively characterize the improvement of fractures to filtration capacity in tight sandstone reservoir and accurately predict permeability, the Triassic Chang 63 Member of Jiyuan Region, Northwestern Ordos Basin is used as an example, a novel model of predicting permeability from electrical image logging is raised. In this model, the porosity frequency spectra are first extracted to characterize the pore structure of fractured tight sandstones. Afterwards, two parameters, which are defined as the logarithmic geometric mean value (φmv) and the golden section point variance (σg) of porosity frequency spectrum, are extracted to characterize the contribution of fractures to permeability. Comparing with the shape of porosity frequency spectrum, permeability φmv and σg, the quality of our target fractured tight sandstone reservoirs is quantified, and relationships among permeability, φmv and σg are established. High-quality reservoirs exhibit wide porosity frequency spectrum, high values of φmv and σg, and vice versa. Three parameters, which are formation total porosity, φmv and σg, are chosen to establish a novel fractured tight sandstone reservoir permeability prediction model. The involved input parameters in this model are calibrated by using the routine experiments of 35 core samples. Finally, we apply this model into field applications to consecutively calculate permeability in the intervals with which electrical image logging is acquired. Comparison of predicting permeability with core derived results illustrate that our raised model is usable in the Chang 63 Member of Jiyuan Region. The average relative errors between these two kinds of permeabilities is only 16.54% in 12 wells. This research gives a novel technique of calculating permeability in fractured tight reservoirs. It can avoid the effect of CH4 or hydrocarbon on conventional and NMR logging responses, and will play a great important role in unconventional reservoirs permeability prediction and formation characterization.
Production Forecast for Multistage Hydraulically Fractured Shale Gas Well Based on Integration of Domain Knowledge and Deep Learning Algorithm
Authors: Luo Yang , Kang Bo , Guo Jianchun , Feng Yan , Jiang Liping , He Wei , Cheng Yi , Xiao Yong , Zhao Xing , Shi Daju , Lu Cong 
Published: March 2024

Abstract
Accurate production forecast of multistage hydraulically fractured wells is crucial for the development of shale gas reservoir. While several data-driven production models have been proposed, few of them take into account the physical mechanism and production process.
In this paper, we present an innovative approach that combines domain knowledge with a deep learning algorithm to establish an accurate and interpretable production model. Integrated production influencing factors were extracted from four main aspects: geological reserve, fracture network shape, fracture conductivity and production control. Instead of treating the entire horizontal well as an average, features from individual stages were utilized as the model inputs. To account for the sequential gas aggregation from bottom to top stages, the gated recurrent unit (GRU) algorithm was applied, and an additional Mask layer was introduced to accommodate varying stage numbers among different wells.
The production model was trained with real data from 119 wells in Weiyuan shale gas field, China. The hyper-parameters were optimized using Bayesian optimization method, resulting in a robust performance with an average relative error (MRE) of 11.7%. This MRE is 77.4% lower than that of the traditional multilayer perceptron model. Furthermore, our model outperformed the simple GRU model by 37% in terms of MRE, demonstrating the significance of the Mask layer in avoiding data redundancy and improving information transmission efficiency. The results in this paper indicate the importance of considering input variables at the stage level and highlight the benefits of incorporating domain knowledge into production forecast.
Unlike conventional models that are solely data-driven, the approach proposed in this paper faithfully aligns with the actual production process of multistage hydraulically fractured wells, leading to significantly improved prediction performance. This study shows the potential of integrating domain knowledge and deep learning algorithm for production forecast in shale gas reservoirs.
A novel volatile staphyloxanthin biosynthesis inhibitor
Authors: Singha Joydeep , Dutta Nipu , Saikia Jyoti Prasad 
Published: March 2024

Abstract
In the present research volatile organic compounds (VOCs) of garlic/mustard oil macerate (GMM) (garlic clove and mustard oil in the ratio of 1:4, heated at 80 OC for 4 h) was found to enhance the antibacterial activity of antibiotics (gentamycin, 41.17%; kanamycin, 38.89%, and streptomycin, 43.75%) against S. aureus. The mechanism behind the enhancement of S. aureus's sensitivity to antibiotics may be due to reduction of antibiotics resistance. On evaluating one of the well-known antibiotic resistance mechanisms of S. aureus, the ability to produce staphyloxanthin, it has been observed that the VOCs of GMM alone can decrease staphyloxanthin (44.23 ± 0.14%) production. This decrease of staphyloxanthin production and thereby increasing sensitivity to antibiotic, may be assigned to the compounds present in the VOCs of GMM. The major VOCs present in the of GMM were identified as allicin, ajoene, vinyl dithiin, allyl isothiocynate and sinigrin. The order of binding of VOCs with dehydroxysqualene synthase (crtM) protein, which is important in staphyloxanthin production of S. aureus, was found to be sinigrin > ajoene > allicin > dithiin > AITC. Further, decrease in staphyloxanthin production found to increase the membrane fluidity of S. aureus as validated by fourier transformed infrared spectroscopy and scanning electron microscopy and this may allow antibiotics to enter inside the bacterial cell more rapidly.
A Feasible Solution for Image Encryption, Restoration, and Colorization Based on the Methods of Weighted Conjugate Gradient, RSA Encryption, and Deep Learning.
Authors: Yuan Gonglin , Zhang Zhao 
Published: March 2024

Abstract

In contemporary society, people are increasingly aware of environmental issues. Coinciding with this development is the arrival of the era of big data, accompanied by significant advances in artificial intelligence. These technologies are increasingly used to collect, systematize and review data to facilitate informed decision-making processes. Ecological image processing stands out as a critical application in this technological field. In the rapid development of deep learning methods, challenges still exist due to the impact of training models on machine performance. In some cases, machine performance is still not ideal. This paper introduces a novel weighted conjugate gradient (WCG) algorithm based on the classic conjugate gradient method, which has better performance in image restoration tasks. Meanwhile, this paper extends the RSA encryption method to the encrypted transmission of the matrix framework to ensure data security during the transmission process. In addition, under the supervision of established machine learning vision models, this paper adopts a penalty function strategy combined with the p-Laplacian operator and manual methods to provide users with enhanced control over manual intervention in grayscale image colorization, thereby enriching Visual fidelity and interpretability of images. The numerical calculation method adopts the WCG algorithm innovatively proposed in this article. Based on the above, the framework proposed in this paper describes a quasi-automatic method for image encryption, transmission, recovery, and colorization. This framework not only ensures that users can intervene and adjust but also maximizes machine execution speed. The framework bridges the gap between fully automated systems and fully manual operating systems, trying to find a balance between convenience and accuracy. At the same time, the Matrix RSA encryption method ensures security during transmission. This framework has significant advantages in applications in professional fields that have specific requirements for accuracy, convenience, and security.
Validity and Power of the Case-Only Approach in Prospective Cohort and Case-Cohort Studies with Time-to-Event Endpoints
Authors: Freitag-Wolf Sandra , Akinloye O Mercy , Dempfle Astrid 
Published: March 2024

Abstract

For genetic epidemiological studies with binary outcomes, the case-only (CO) approach has been shown to be powerful for examining statistical interactions, in particular gene-environment interactions. For time-to-event outcomes, the CO approach has been extended in the context of randomized clinical trials (RCT), but has not yet been investigated in prospective observational data. We explore the CO approach for time-to-event outcomes in scenarios with main effects of different strength (small, moderate) and compare its results with classical Cox proportional hazard and logistic regression models. We use only the earliest observed events (as ‘cases’) in the CO approach and also consider censored events (as ‘controls’ in logistic regression) by a restricted follow-up scheme in a cohort design or a random subsample of these in a case-cohort design. In our simulation study, the CO approach was consistently valid in the cohort settings and had a similar power as the benchmark analyses. In contrast, in the case-cohort design, the CO approach was valid and more powerful only in the scenario with just one main effect. However, in the presence of two moderate main effects, estimators may be biased, with a moderately inflated type I error rate. In a real-world example of a cohort study, the CO design represents an efficient approach that can be applied at an early follow-up time. Under a variety of circumstances, the CO approach is as powerful as the standard models for time-to-event data in the cohort framework, but can be biased in the presence of two main effects in the case-cohort framework.
Alert generation and Vehicle Authenticationin fog environment
Authors: singh Sunakshi , Chaurasiya Vijay Kumar 
Published: March 2024

Abstract
Be it the advancement of infrastructure or the impact of the pandemic, more and more vehicles are added to the system. This has significantly increased traffic density, resulting in traffic jams and sometimes leading to collisions. Therefore concern for effective strategies systems and safety mechanisms for proper traffic management is more indispensable than ever. This paper introduces a lightweight alerting system that functions as a collision identification system, acquiring information about the vehicle. The framework will leverage the advantages of fog computing and notify other on-road vehicles about the collision only after proper authentication. For reducing the false alarm, we will use the sensor to know the level of impact. Additionally, a quick, immediate response is included in the framework, which is intended to call emergency services in order to provide medical aid at the earliest.
Coal Structure Evaluation and Morphological Properties That Affect the Coal Usage in Industries.
Authors: Gaesenngwe Gaesenngwe , Danha Gwiranai , RAGHUPATRUNI PRASAD , MAMVURA TIRIVAVIRI 
Published: March 2024

Abstract
The contemporary research article is central to understanding coal structure evaluation and the morphological development impacting its utilization in different applications. Through Mineral Liberation Analysis (MLA) designs high content phyllosilicates minerals and swelling clay minerals were rationalized to provides a novel insight into enhanced coal beneficiation and the benefits of coal by-product re-utilization progressions that encourage safer environments and economic sustainability. This work commences with collection of five (5) different coal samples from the central district mine in Botswana and chemical characterization via Thermogravimetric coal analysis, x-ray fluorescence spectroscopy, x-ray diffraction, scanning electron microscopy and the Hardgrove Grindability Index testing that quantify coal material hardness and fracture toughness. The results showed sulfur and phosphorus inclusions in all samples complemented through sphalerite mineral phases (Zn, Fe)S and the coal morphology stimulated the material fracture toughness and hardness properties by influential mineral amalgams intrinsic to the Botswana central district coal maceral such as aluminum oxides (Al2O3), silicate (SiO2), calcites (CaO), Iron oxide (Fe2O3), potassium feldspars (K−AlSi3O8), albite (Na−AlSi3O8), and anorthite (Ca−Al2Si2O8) compounds in alkali feldspars which are predominantly group I and II carriers were perceived in substantial quantities. The coal industry has attracted much industrial attention by supply of high energy potent coal material and coal-by products to manufacturing foundations producing cement, ceramic tiles, paving bricks and material synthesis and will continue to supply other economic sectors in the conceivable future. Nevertheless, environmental concerns consequential to coal beneficiation are pressing issues requiring transdisciplinary innovations through investigations and technological practices that encourage the elimination of toxins and hazardous compounds from coal products therefore holistically generating sustainable and renewable resource for the future.
Highly Efficient Circularly Polarized Near-infrared Phosphorescence in Both Solution and Aggregate
Authors: Tang Ben Zhong , Liu Dan , Wang Wenjin , Alam Parvej , Yang Zhan , Wu Kaiwen , Zhu Lixun , Xiong Yu , Chang Shuai , Liu Yong , Wu Bo , Wu Qian , Qiu Zijie , Zhao Zheng 
Published: March 2024

Abstract

Circularly polarized phosphorescence (CPP) is a spin-forbidden radiative process with chiroptical activity. The CPP mechanism is far from comprehensively understood, mainly due to the limited examples of efficient triplet emission from small chiral organic molecules with well-defined structures. Herein, a pair of chiral enantiomers R/S-BBTI is reported, featuring the highly distorted spiral ring-locked heteroaromatics with heavy iodine atoms. These chiral molecules emit NIR phosphorescence and exhibit considerable high dissymmetry factors up to 0.013 with an efficiency of 4.2% and a lifetime of 119 µs in dimethyl sulfoxide (DMSO) solution after ultraviolet irradiation. Their crystals show efficient CPP with 7.0% quantum efficiency and a lifetime of 166 µs. Extensive experimental chiroptical investigations combined with theoretical calculations reveal an efficient spin-flip process that modulates the electron and magnetic transition dipole moments to enhance CPP performance. Moreover, the phosphorescence of R/S-BBTI is oxygen-sensitive and photoactivated in DMSO. Therefore, R/S-BBTI can be applied for hypoxia imaging in cells and tumors, expanding the scope of CPP applications.
The Effect of Sand-Crumb Rubber Mixture Treatment on the Seismic Response of a Low-Rise Building Located on Liquefiable Soil
Authors: Tareghian Benyamin , Baradaran Mohammad Saleh , Akhtarpour Ali 
Published: March 2024

Abstract
One of the most effective measures to reduce earthquake risks in high-seismic areas is to reduce the input forces caused by earthquakes to the structure. The properties of rubber materials in geotechnical projects are energy absorption, dynamic deformation change as well as damping of latent energy in loads, high shear modulus and damping ratio, easy access and their economic nature. In this research, with finite difference modeling, the effect of using sand- crumb rubber layer on the seismic behavior of the model has been obtained. In the following, by changing the thickness and depth of the sand-crumb rubber layer, the seismic behavior such as floor displacement and internal forces have been investigated. This research numerically models liquefaction (UBCsand with FLAC) and predicts the effects of the sand-crumb rubber layer of different thicknesses under the foundation and evaluates the structure's damage and settlement interacting with the soil by validating the numerical model with the laboratory model and calibrating it with different ratios. The results show that liquefaction, pore water pressure excess ratio and soil settlement will be significantly reduced with the presence of sand-crumb rubber layer, and also the base shear has shown an increase, but the structural damage is reduced.
Phthalocyanine Aggregates as “Semiconductor-like” Photocatalysts for Hypoxic-Tumor Photodynamic Immunotherapy
Authors: Li Xingshu , Liu Hao , Li Ziqing , Zhang Xiaojun , Xu Yihui , Tang Guoyan , Wang Zhaoxin , Zhao Yuan-Yuan , Ke Mei-Rong , Zheng Bi-Yuan , Huang Shuping , Huang Jian-Dong 
Published: March 2024

Abstract

Photodynamic immunotherapy (PIT) has emerged as a promising approach for efficient eradication of primary tumors and inhibition of tumor metastasis. However, most of photosensitizers (PSs) for PIT exhibit notable oxygen dependence. Herein, a concept emphasizing on transition from molecular PSs into “semiconductor-like” photocatalysts is proposed, which converts the PSs from type II photoreaction to efficient type I photoreaction. Detailed mechanism studies reveal that the nanostructured phthalocyanine aggregate (NanoNMe) generates radical ion pairs through a photoinduced symmetry breaking charge separation process, achieving charge separation through a “self-substrate” approach and leading to exceptional photocatalytic charge transfer activity. Additionally, a reformed phthalocyanine aggregate (NanoNMO) is fabricated to improve the stability in physiological environments. NanoNMO showcases outstanding photocytotoxicities under both normoxic and hypoxic conditions and exhibits remarkable tumor targeting ability. Notably, the photodynamic effect mediated by NanoNMO not only triggers the systemic anti-tumor immune response but also synergizes with PD-1 antibodies to enhance the infiltration of cytotoxic T lymphocytes into tumor sites, leading to the effective inhibition of tumor growth.
Going global: An Analysis of UK Medical Schools’ International Collaborations
Authors: Haruna-Cooper Lois , Rashid Mohammed Ahmed , Kelly James , Gardee Ameerah 
Published: March 2024

Abstract

Objectives: Given that the existing literature on international medical education collaborations is dominated by North American case studies, this study sought to identify and describe such collaborations hosted by UK medical schools.
Methods: UK medical school webpages were identified from the General Medical Council (GMC) and were methodically searched for any information about international collaborations focussed on undergraduate medical education.
Results: Of 37 medical schools formally listed by the GMC, 12 provided information about their international collaborations, which broadly fitted into three main categories: knowledge exchange collaborations focussed on medical school capacity building; joint study programmes where students complete part of their medical studies in the UK; offshore medical campuses or joint medical degrees with an overseas university.
Conclusion: This study describes the current landscape of international collaborations that UK medical schools are engaged in, demonstrating that these collaborations vary from comprehensive partnerships to much more limited relationships. Despite the sparse academic literature about international collaborations in medical schools, especially in the UK context, this study highlights a significant degree of activity that warrants further investigation to examine consequences for students, teachers, and institutions involved on both sides of these relationships.
The Impact of Leadership Member Exchange on Innovation Behaviour Perceived by University Lecturers: The Mediation Roles of Psychological Empowerment and Psychological Safety
Authors: ZHU Yanheng , TSAI Kuan-Chun , Gao Yuan 
Published: March 2024

Abstract

This study delves into the influence of Leadership-Member Exchange (LMX) on innovation behaviour among university lecturers in Chengdu, a key educational and urban development hub in Western China. It particularly scrutinises the mediating roles of psychological empowerment and psychological safety within this context. With its blend of traditional and contemporary educational practices amid rapid urbanisation, Chengdu offers a distinctive backdrop for exploring the dynamics of academic leadership and its impact on innovation. Employing a quantitative methodology, the research utilises structural equation modelling and regression analysis to dissect data gathered from lecturers across various universities in Chengdu. The aim is to unravel how LMX, defined by the quality of leader-member interactions and relationships, affects lecturers’ propensity for innovation. The study probes the extent to which psychological empowerment and psychological safety serve as mediators in this relationship. By situating the research in Chengdu’s dynamic environment, notable for its unique educational landscape, the study substantially contributes to the literature on leadership and innovation in higher education settings. The findings are poised to offer critical insights for university administrators and policymakers and emphasise leadership approaches that nurture innovation through empowerment and a sense of safety among academic staff.
Cbl-b E3 ligase-mediated neddylation and activation of PARP-1 induces vascular calcification
Authors: Kook Hyun , Kwon Duk-Hwa , Shin Sera , Nam Yoon Seok , Choe Nakwon , Lim Yongwoon , Jeong Anna , Lee Yun-Gyeong , Kim Young-Kook 
Published: March 2024

Abstract

Aims: Vascular calcification (VC) refers to the accumulation of mineral deposits on the walls of arteries and veins, and it is closely associated with increased mortality in cardiovascular disease, particularly among high-risk patients with diabetes and chronic kidney diseases (CKD). Neuronal precursor cell-expressed developmentally downregulated protein 8 (NEDD8) is an ubiquitin-like protein that plays a pivotal role in various cellular functions, primarily through its conjugation to target proteins and subsequent relay of biological signals. However, the role of NEDDylation in VC has not been investigated.
Methods and Results: In our study, we observed that MLN4924, an inhibitor of the NEDD8-activating E1 enzyme, effectively impedes progress of VC. By LC-MS/MS analysis, we identified that poly(ADP-ribose) polymerase 1 (PARP-1) is subjected to NEDD8 conjugation, leading to an increase in PARP-1 activity during VC. Subsequently, we uncovered that the PARP-1 NEDDylation is mediated by the E3 ligase Cbl proto-oncogene B (Cbl-b) and is reversed by the NEDD8-specific protease 1 (NEDP-1) during VC. Furthermore, Cbl-b C373 peptide effectively mitigates the inactive form of E3 ligase activity of Cbl-b, ultimately preventing VC.
Conclusions: These findings provide compelling evidence that the NEDD8-dependent activation of PARP-1 represents a novel mechanism underlying vascular calcification and suggests a promising new therapeutic target for VC.