bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Phase-State-Radius-Based Multiphase-State Identification Acceleration Approach of the Hydrocarbons-CO2-H2O System for Compositional Reservoir Simulation
Authors: Yuan Bin , Huang Gang , Zhang Wei , Dindoruk Birol 
Published: December 2024

Summary
The CO2-enhanced oil recovery (CO2-EOR) technique could increase the oil recovery factor and achieve subsurface CO2 storage. To evaluate the feasibility of CO2-EOR operation, an equation-of-state-based (EOS-based) compositional simulation is inevitable. However, time-consuming multiphase flash calculations limit the application of the conventional EOS-based compositional simulation in large-scale reservoir simulations. Therefore, there is an urgent need to accelerate the EOS-based compositional simulation by reducing the time spent on the multiphase flash calculations.
In this study, we develop a fast, multiphase-state identification approach to achieve high computational efficiency of the compositional simulation. First, taking one given point in the compositional space composed by pressure and the overall composition as the original point, the phase-state radius (PSR) is defined as a radius inside which all points have the same phase state as the given point. Subsequently, the results of the multiphase flash calculations of the points in the compositional space are stored. Finally, when a new point is inside the PSR of one calculated point, the stored results are used to accelerate the new multiphase flash calculations of the new point by omitting the phase stability analysis (PSA) and possible additional multiphase split (MS) calculations. Case studies show a 6–10% reduction in multiphase flash computation time compared with two existing methods when the fluid is far from the phase boundary and a reduction of at least 17.5% when the fluid is near the phase boundary.
True Triaxial Laboratory Study of the Strain Patterns Measured by Distributed Fiber Optics for Hydraulic Fracturing of Multilevel Horizontal Wells
Authors: Guo Tiankui , Zhang Yuanhang , Chen Ming , Liu Yongzan , Qu Zhanqing , Dai Caili , Zhang Bo , Hu Zunpeng , Xue Linrui 
Published: December 2024

Summary
As the exploitation of oil and natural gas has progressed, hydraulic fracturing has become a primary method for increasing oilfield production. Simultaneous hydraulic fracturing of several perforation clusters, by employing limited-entry methods, has become standard in horizontal well stimulation. However, challenges such as unclear fracture identification and limited monitoring methods persist in hydraulic fracturing. This study integrates an optical frequency domain reflector with true triaxial fracturing of multilevel horizontal wells to develop a physical simulation system for monitoring fractures in a laboratory setting via distributed fiber optics. By employing fiber optics, dynamic monitoring of fractures during the fracturing process of multilevel horizontal wells can be achieved. The results indicate that monitoring with distributed fiber optics can clearly record data and accurately determine the initiation points of fractures. The strain data induced by the fractures on the fibers can be interpreted to deduce the fracture width. If a fracture deflects upon encountering a fiber, the fiber will exhibit tensile strain within an abnormal range. When using distributed fiber optics for monitoring fractures in multilevel horizontal wells, it is crucial to optimize the placement of fractures to ensure that the signals detected by the fibers are complete and avoid signal loss. In this paper, we demonstrate the feasibility of using distributed fiber optics for fracture monitoring in multilevel horizontal well fracturing experiments, overcoming the limitations of current single-method approaches to monitoring laboratory true triaxial hydraulic fractures.
Secure in the Dark? An In-Depth Analysis of Dark Web Markets Security
Authors: Wang Yichao , Arief Budi , Hernandez-Castro Julio 
Published: December 2024

Abstract

As the name implies, dark web markets – also commonly known as anonymous markets – have put in place measures for protecting the privacy of its users, both sellers and buyers, as this is a key priority that can attract users worldwide. With the rapid growth of dark web markets, competition between them has become more intense. In this environment, malicious attacks targeting competitors – for instance, aimed at reducing the availability of rivals' services – have also become more common. These attacks not only affect other services' availability and accessibility, but they may also lead to personal and private information being leaked. As such, it is understandable that dark web markets may want to implement strong security mechanisms to protect themselves and their users both from law enforcement and other operators. This is particularly true as good security can bea matter of survival but also help to gain a competitive edge over rivals. Although the literature has analysed and described dark web markets from multiple perspectives, there is still a gap in understanding the different security mechanisms they deploy. Furthermore, data collection – which is often considered a challenge in this research area – may be hindered by these very security mechanisms. Therefore, and in order to cover this gap, the study presented in this paper aims to investigate in depth the security mechanisms of various dark web markets. This will hopefully help to shed a brighter light on their operation. To achieve this, we performed data collection and experiments in twelve dark web markets. Although data collection practices may need to vary slightly for each market, all the data was collected over the span of four months, between May and August 2023. We found there are three main groups of security mechanisms in dark web markets: (i) those aimed towards increasing web security, (ii) those mostly aimed at improving account security, and (iii) those related to financial security. In addition, it is interesting to note that different types of security mechanisms on a given market may reflect the operator's business philosophy, technical knowledge and security posture, which in turn could have a big impact on the longevity, profitability and overall success of a particular market . The results of this study can help the academic and security research communities to understand the operation and evolution of dark web markets, hopefully to combat the crimes facilitated by these dark web markets more effectively. Additionally, findings in this study may provide some clues on how to improve the efficiency of data collection in this particularly hostile environment.
Finite Element Analysis of Pullout Resistance and Progressive Failure of Strip Anchors in Strain-Softening Soils based on the Cosserat Continuum Method
Authors: Ye Xiangji , Wei Wencheng , Zhang Heng , Ji Zezhou , Tang Hongxiang , zhao Xin 
Published: December 2024

Abstract

Given the limited research on regularization mechanisms in finite element analysis of the ultimate pullout resistance of plate anchors, particularly considering soil strain softening, this paper employs a Cosserat continuum regularization mechanism combined with a Mohr-Coulomb matched Drucker-Prager constitutive model (MC-matched DP model) to address this issue. Implementing the User-Defined Element (UEL) function in ABAQUS, the numerical solution was developed and validated against existing literature to verify the accuracy of the MC-matched DP model for analyzing plate anchor pullout resistance. This study demonstrates that the Cosserat continuum model effectively resolves common issues such as numerical convergence difficulties and mesh dependency encountered in finite element calculations for softening soils. Subsequently, the model was applied to conduct a detailed analysis of the ultimate pullout resistance of plate anchors and the progressive failure process of the soil. Parametric analyses were performed to explore the combined effects of plate anchor inclination, burial depth, and degree of strain softening on ultimate resistance and failure mechanisms. Based on these analyses, an expression for the ultimate resistance coefficient Nc, incorporating the influences of plate anchor inclination, burial depth, and strain softening, was formulated, providing a valuable reference for geotechnical engineers in practical applications.
Performances of cement-based materials incorporating new SCMs produced by the co-calcination of construction wastes with waste dolomite powder
Authors: chen deng , Lu Ji-da , Mo Li-wu , Liu Kai-wei , Wang Ai-guo , Yang Tao 
Published: December 2024

Abstract

In this study, new types of supplementary cementitious materials (SCMs) were manufactured by the calcination of construction wastes such as engineering muck (EM) and waste brick (WB) in the presence of waste dolomite powder (WDP). The impacts of calcined dolomite-muck (CDM) and calcined dolomite-brick (CDB) on the performances of Portland cement were investigated, the reaction mechanism of CDM and CDB in pastes was also analyzed. Results showed that the mineral compositions of CDM and CDB are β-C2S, periclase, quartz and merwinite. The incorporations of CDM and CDB decreased obviously the hydration heat and strengths of cement-based materials at early stages. However, the blended cement mortars with 10-20% CDM and CDB obtained similar or higher strengths at later stages compared to the control mortar. This is attributed to the hydration of β-C2S in CDM and CDB, resulting in the pore structure densification and the lower porosity at later ages. In addition, the mortars with CDM and CDB also produced gentle expansions attributed to the hydration of periclase in CDM and CDB, which is beneficial for mitigating the shrinkage.
Exploring the Antimicrobial Potential of New Selenium- N-Heterocyclic Carbene Complexes and Their Benzimidazolium Salts: Synthesis, Characterization, Biological Evaluation, and Docking Insights
Authors: BOUALIA Boutheina , SANDELI Abd elkrim , BOULEBD Houssem , KARCI Hüseyin , DUNDAR Muhammed , ÖZDEMIR İlknur , Gürbüz Nevin , Koç Ahmet , MENACER Rafik , ÖZDEMIR İsmail 
Published: December 2024

Abstract

The present work, describes the synthesis and antimicrobial evaluation of new selenium-NHC adducts (3a-e) and their corresponding benzimidazolium salts (2a-e). Specific synthetic approaches were employed, resulting in compounds with satisfactory stability under humid and aerated conditions. Characterization by spectroscopic methods confirmed structural changes upon selenium incorporation. Biological evaluations revealed varying antimicrobial and antifungal activities among the synthesized compounds. The results indicated that the benzimidazolium salts exhibited significantly enhanced antimicrobial and antifungal activities compared to reference agents. For instance, compound 2a demonstrated an IC50 value of 6.25 µg/mL against Candida albicans, which was comparable to the reference Caspofungin (6.25 µg/mL).
Similarly, compound 2e demonstrated strong antibacterial activity against Staphylococcus aureus, with an IC50 value of 0.8 µg/mL, significantly outperforming the reference Ampicillin (1.56 µg/mL). In contrast, the selenium-NHC adducts exhibited moderate to minimal activity, with compound 3e showing the highest IC50 value of 25 µg/mL against Staphylococcus aureus, but failing to surpass the activity of the reference agent. To explore the potential mechanism of action, molecular docking studies were conducted against E. coli DNA gyrase and CYP51. The molecular docking results demonstrate that synthesized compounds exhibit significant binding affinity against both enzymes, indicating antibacterial and antifungal potential. These binding affinities suggest that these molecules could be effective dual-action antimicrobial agents.
Clinical Utility of Comprehensive Genomic Profiling for Advanced Pancreatic Cancer: Insights from Real-World Data Analysis
Authors: So Eiichiro , Hayashi Hideyuki , Shimozaki Keitaro , Horie Sara , Kishimoto Shotaro , Chida Akihiko , Saito Yuki , Tsugaru Kai , Hirata Kenro , Tanishima Shigeki , Nishihara Hiroshi , Kanai Takanori , Hamamoto Yasuo 
Published: December 2024

Abstract

Background
Precision medicine is a promising therapeutic strategy for pancreatic cancer. However, only a few patients are eligible for genotype-matched treatments because of the low detection rate of actionable genomic alterations, and the clinical application of comprehensive genomic profiling (CGP) in pancreatic cancer has not been completely investigated. CGP provides considerable information, such as data on prognosis and future eligibility of patients for genotype-matched clinical trials, and can eventually guide physicians’ treatment strategies. This study aimed to investigate the contribution of CGP to patient outcomes.
Methods
This single-center retrospective cohort study enrolled patients diagnosed with recurrent or metastatic pancreatic cancer with adenocarcinoma or adenosquamous carcinoma who underwent systemic chemotherapy between April 2018 and April 2022. We reviewed medical records and collected data on patient characteristics, survival, and genomic information. We compared overall survival (OS) between patients who received CGP (CGP group) and those who did not (non-CGP group).
Results
Overall, 111 patients were eligible, of which 59 underwent CGP. No significant differences were observed in patient characteristics between the groups. The median OS was significantly longer in the CGP group than in the non-CGP group (25.2 vs. 11.8 months; hazard ratio, 0.49; 95% confidence interval, 0.31–0.76; P = 0.0013). Actionable genomic alterations were detected in 24 patients (40.7%), and six patients (10.2%) underwent genotype-matched treatments.
Conclusions
OS was extended in patients with pancreatic cancer who underwent CGP, possibly due to its influence on physicians’ treatment strategies. This result highlights the need for proactive and timely CGP for patients with pancreatic cancer.
Long non-coding RNA MALAT1 promotes the proliferation and metastasis of lung cancer by regulating FUT4 and α1,3-fucosylated glycans mediated via the PI3K/Akt signaling pathway
Authors: Alshwmi Mohammed , Li Shijun , Saleem Muhammad , Ahmed Faisal , Yingxin Wang , Juebin Gu , Badheeb Mohamed 
Published: December 2024

Abstract

In this study, we investigate the role of MALAT1 in NSCLC and its potential interactions with FUT4 in promoting the progression, proliferation, and metastasis of NSCLC cell lines. MALAT1 expression was assessed using quantitative PCR (qPCR) while FUT4 expression was measured using qPCR, enzyme-linked immunosorbent assay (ELISA), and Western blotting in both serum and tissue samples. To confirm the regulatory role of MALAT1 in FUT4 expression, Western blotting, qPCR, and immunofluorescence techniques were employed in A549 and H1299 cell lines. LeY in the epidermal growth factor receptor was detected using Immunoprecipitation. We found that MALAT1 and FUT4 expressions were higher in the serum and tissues of NSCLC patients. MALAT1 led to increasing FUT4 expression and tumor growth as well as metastasis in A549 and H1299 cells. Our findings indicated that MALAT1 upregulated FUT4 expression through the PI3K/Akt signaling pathway, increasing tumor growth, and metastasis in lung cancer. MALAT1 knockdown in lung cancer cells inhibited FUT4 expression, suppressing cell proliferation and metastasis. Our study suggested that LncRNA MALAT1 promotes proliferation and metastasis via targeting FUT4 by enhancing α1,3-fucosylation and LeY biosynthesis of glycoproteins. MALAT1 and FUT4 can therefore be potential diagnostic and therapeutic targets in lung cancer.
Development and validation of a predictive model for intravesical recurrence after radical nephroureterectomy： a multi-center study
Authors: wang cheng , zhang biao , kang ziming , ou shuzhen , li pingheng , wan jianghou , shang panfeng 
Published: December 2024

Abstract

Purpose The high incidence of incurrence recurrence(IVR) after radical nephroureterectomy (RNU) is a characteristic of upper urinary tract urothelial carcinoma (UTUC), which has a significant impact on the survival outcome of patients. This study aimed to construct nomogram using data from multicenter data to predict IVR in patients with UTUC.Methods Clinical data of 515 UTUC patients after RNU were gathered from three medical centers between 2012 and 2022. The factors associated with IVR were analyzed by univariate and multivariate Cox proportional risk models in one center as training cohort, and included independent risk factors into nomogram models predicting IVR-free survival (IVRFS). Another two centers were collected as the external cohort to validate the predictive accuracy and discriminative ability of the nomogram.Results Ureteroscopy, hydronephrosis, the history of bladder cancer, surgical margin and tumor grade were associated with IVR after UTUC (P < 0.05). The C-index of the nomogram in the training cohort were 0.722. The C-index of the nomograms in the external validation cohort were 0.767.Receiver operating characteristic (ROC) curves, calibration curves, and survival curves all demonstrated good predictive performance of the nomogram.Conclusion Ureteroscopy, hydronephrosis, the history of bladder cancer, surgical margin and tumor grade can be used to independently predict IVR after RNU. The nomogram was built based on these factors had good differentiation and conformity, which can assist clinicians in assessing individualized IVR rates and making optimal treatment decisions.
Parental Perceptions of Developmental Care Rounds in a Pediatric Heart Center
Authors: Pande Chetna , Burns Joseph , Schwab Sarah , Medchill Michelle , Rizk Claire , Schlosser Robin , Davis Kelly , Carretero Sofia , Kimbrough Danielle , Elhoff Justin 
Published: December 2024

Abstract

Background Infants requiring surgery for congenital heart disease (CHD) are at an increased risk of neurodevelopmental delay. Developmental Care Rounds (DCR) has been implemented widely to support the neurodevelopment of children with CHD while admitted to the hospital.Objectives This study aims to describe caregiver perceptions of DCR at a quaternary academic children’s heart center.Methods Over 17 months, caregivers were asked to evaluate DCR by responding to Likert-scale statements by level of agreement as well as free-form text responses. The Likert scales were analyzed and free-form responses were manually reviewed to identify key themes.Results Forty-nine families participated in the assessment. One hundred percent of caregivers reported that they “Agree” or “Strongly Agree,” to the surveyed questions. These included queries regarding the benefit and utility of DCR. In the qualitative assessment, responses identified themes surrounding feeling more empowered to be active members of the care team, an increased awareness of the importance of regular developmental care during hospitalization, as well as education regarding available resources to promote appropriate developmental care. Some of the specific tools parents reported learning include reading, speaking aloud to children, limiting screen time, and engaging in skin-to-skin contact.Conclusions This is one of the first descriptions of caregiver perceptions of DCR in pediatric patients with CHD. Our results indicate parental satisfaction with DCR with the identification of specific tools to aid in their children's development. DCR may offer an opportunity to improve neurodevelopmental outcomes in hospitalized children with CHD.
A Digital Twin Framework for Real-Time Healthcare Monitoring: Leveraging AI and Secure Systems for Enhanced Patient Outcomes
Authors: Jameil Ahmed K , Al-Raweshidy Hamed 
Published: December 2024

Abstract

Digital Twin (DT) technology in healthcare is relatively new and faces several challenges, e.g., real-time data processing, secure system integration, and robust cybersecurity. Despite the growing demand for real-time monitoring frameworks, further improvements remain possible. In this study, an architecture has been introduced that utilises cloud computing to create a DT ecosystem. A group of 20 participants has been monitored continuously using high-speed technology to track key physiological parameters, i.e., diabetes risk factors, heart rate (HR), oxygen saturation (SpO2) levels, and body temperature (BT). The DT model functions as a tool, storing both real-time sensor data and historical records, to effectively identify health risks and anomalies. An MLP model was combined with XGBoost, resulting in a 25% reduction in training time and a 33% reduction in testing time. The model demonstrated reliability with an accuracy of 98.9% and achieved real-time accuracy of 95.4%, alongside an F1 score of 0.984. Meticulous attention has been paid to cybersecurity measures, ensuring system integrity through end-to-end encryption and compliance with health data regulations. The incorporation of DT and AI within the healthcare sector is seen as having the potential to overcome existing limitations in monitoring systems, while workloads are relieved and data-driven diagnostics and decision-making processes are improved, e.g., through enhanced real-time patient monitoring and predictive analysis
AI-based analysis of fetal growth restriction in a prospective obstetric cohort quantifies compound risks for perinatal morbidity and mortality and identifies previously unrecognized high risk clinical scenarios
Authors: Zimmerman Raquel M. , Hernandez Edgar J. , Yandell Mark , Tristani-Firouzi Martin , Silver Robert M. , Grobman William , Haas David , Saade George , Steller Jonathan , Blue Nathan R. 
Published: December 2024

Abstract

Background
Fetal growth restriction (FGR) is a leading risk factor for stillbirth, yet the diagnosis of FGR confers considerable prognostic uncertainty, as most infants with FGR do not experience any morbidity. Our objective was to use data from a large, deeply phenotyped observational obstetric cohort to develop a probabilistic graphical model (PGM), a type of “explainable artificial intelligence (AI)”, as a potential framework to better understand how interrelated variables contribute to perinatal morbidity risk in FGR.
Methods
Using data from 9,558 pregnancies delivered at ≥ 20 weeks with available outcome data, we derived and validated a PGM using randomly selected sub-cohorts of 80% (n = 7645) and 20% (n = 1,912), respectively, to discriminate cases of FGR resulting in composite perinatal morbidity from those that did not. We also sought to identify context-specific risk relationships among inter-related variables in FGR. Performance was assessed as area under the receiver-operating characteristics curve (AUC).
Results
Feature selection identified the 16 most informative variables, which yielded a PGM with good overall performance in the validation cohort (AUC 0.83, 95% CI 0.79–0.87), including among “N of 1” unique scenarios (AUC 0.81, 0.72–0.90). Using the PGM, we identified FGR scenarios with a risk of perinatal morbidity no different from that of the cohort background (e.g. female fetus, estimated fetal weight (EFW) 3-9th percentile, no preexisting diabetes, no progesterone use; RR 0.9, 95% CI 0.7–1.1) alongside others that conferred a nearly 10-fold higher risk (female fetus, EFW 3-9th percentile, maternal preexisting diabetes, progesterone use; RR 9.8, 7.5–11.6). This led to the recognition of a PGM-identified latent interaction of fetal sex with preexisting diabetes, wherein the typical protective effect of female fetal sex was reversed in the presence of maternal diabetes.
Conclusions
PGMs are able to capture and quantify context-specific risk relationships in FGR and identify latent variable interactions that are associated with large differences in risk. FGR scenarios that are separated by nearly 10-fold perinatal morbidity risk would be managed similarly under current FGR clinical guidelines, highlighting the need for more precise approaches to risk estimation in FGR.