bluuebunny/crossref_metadata_2025_split huggingface dataset:
Regional changes in cerebral perfusion with age when accounting for changes in gray‐matter volume
Authors: Hu Jian , Craig Martin S. , Knight Silvin P. , De Looze Celine , Meaney James F. , Kenny Rose Anne , Chen Xin , Chappell Michael A. 
Published: November 2024

AbstractPurposeOne possible contributing factor for cerebral blood flow (CBF) decline in normal aging is the increase in partial volume effects due to brain atrophy, as cortical thinning can exacerbate the contamination of gray‐matter (GM) voxels by other tissue types. This work investigates CBF changes in normal aging of a large elderly cohort aged 54 to 84 and how correction for partial volume effects that would accommodate potential changes in GM might affect this.MethodsThe study cohort consisted of 474 participants aged 54 to 84 years using pseudo‐continuous arterial spin labeling MRI. A volumetric pipeline and a surface‐based pipeline were applied to measure global and regional perfusion. Volumetric regions of interest (ROIs) included GM, cerebral white matter, vascular territories, and the brain atlas from the UK Biobank. The cortical parcellation was using Desikan–Killiany atlas. Non–partial volume effect correction (PVEc) and PVEc GM‐CBF changes with aging were modeled using linear regressions.ResultsGlobal GM CBF decreased by 0.17 mL/100 g/min per year with aging before PVEc (p < 0.05) and was 0.18 mL/100 g/min after PVEc (p < 0.05). All cortical parcels exhibited CBF decreases with age before PVEc. After PVEc, seven parcels retained decreasing trends. However, GM CBF demonstrated increase with age after PVEc in three parcels.ConclusionAlthough decreases in global perfusion are observed with aging before PVEc, perfusion variations appear to be more regionally selective after PVEc. This supports the understanding that variation in cerebral perfusion with age observed with imaging is influenced by regional changes in anatomy that can be accommodated with PVEc, but perfusion variation is still observable even after PVE is accounted for.
A signal model for fat‐suppressed T1‐mapping and dynamic contrast‐enhanced MRI with interrupted spoiled gradient‐echo readout
Authors: Wennen Myrte , Stehling Wilhelm , Marcus J. Tim , Kuijer Joost P. A. , Lavini Cristina , Heunks Leo M. A. , Strijkers Gustav J. , Coolen Bram F. , Nederveen Aart J. , Gurney‐Champion Oliver J. 
Published: November 2024

AbstractThe conventional gradient‐echo steady‐state signal model is the basis of various spoiled gradient‐echo (SPGR) based quantitative MRI models, including variable flip angle (VFA) MRI and dynamic contrast‐enhanced MRI (DCE). However, including preparation pulses, such as fat suppression or saturation bands, disrupts the steady‐state and leads to a bias in T1 and DCE parameter estimates. This work introduces a signal model that improves the accuracy of VFA T1‐mapping and DCE for interrupted spoiled gradient‐echo (I‐SPGR) acquisitions. The proposed model was applied to a VFA T1‐mapping I‐SPGR sequence in the Gold Standard T1‐phantom (3 T), in the brain of four healthy volunteers (3 T), and to an abdominal DCE examination (1.5 T). T1‐values obtained with the proposed and conventional model were compared to reference T1‐values. Bland–Altman analysis (phantom) and analysis of variance (in vivo) were used to test whether bias from both methods was significantly different (p = 0.05). The proposed model outperformed the conventional model by decreasing the bias in the phantom with respect to the phantom reference values (mean bias ‐2 vs. ‐35% at 3 T) and in vivo with respect to the conventional SPGR (‐6 vs. ‐37% bias in T1, p < 0.01). The proposed signal model estimated approximately 48% (depending on baseline T1) higher contrast concentrations in vivo, which resulted in decreased DCE pharmacokinetic parameter estimates of up to 35%. The proposed signal model improves the accuracy of quantitative parameter estimation from disrupted steady‐state I‐SPGR sequences. It therefore provides a flexible method for applying fat suppression, saturation bands, and other preparation pulses in VFA T1‐mapping and DCE.
Intent‐Based Network Configuration Using Large Language Models
Authors: Tu Nguyen , Nam Sukhyun , Hong James Won‐Ki 
Published: November 2024

ABSTRACTThe increasing scale and complexity of network infrastructure present a huge challenge for network operators and administrators in performing network configuration and management tasks. Intent‐based networking has emerged as a solution to simplify the configuration and management of networks. However, one of the most difficult tasks of intent‐based networking is correctly translating high‐level natural language intents into low‐level network configurations. In this paper, we propose a general and effective approach to perform the network intent translation task using large language models with fine‐tuning, dynamic in‐context learning, and continuous learning. Fine‐tuning allows a pretrained large language model to perform better on a specific task. In‐context learning enables large language models to learn from the examples provided along with the actual intent. Continuous learning allows the system to improve overtime with new user intents. To demonstrate the feasibility of our approach, we present and evaluate it with two use cases: network formal specification translation and network function virtualization configuration. Our evaluation shows that with the proposed approach, we can achieve high intent translation accuracy as well as fast processing times using small large language models that can run on a single consumer‐grade GPU.
The Relationship Between Attitudes Towards Academic Self‐Efficacy and Self and Peer Assessment in Turkish Nursing Students: A Cross‐Sectional Study
Authors: İncesu Olga , Ulupınar Sevim 
Published: November 2024

ABSTRACTObjectivesAcademic self‐efficacy (ASE), as well as self (SA) and peer assessment (PA), is associated with the subjective judgements of the individual. The correlation among these concepts merits further research. This study aims to examine the correlation between nursing students' attitudes towards ASE and SA and PA.DesignThis is a correlational cross‐sectional study.MethodsThe sample consisted of 1401 nursing students from five universities in Istanbul, Turkey. The study employed the proportional quota sampling method. The data were collected using a Personal Information Form, View Scale for Peer and Self‐Assessment and ASE Scale. Descriptive statistics and multiple linear regression model (stepwise) tests were used to analyse the data.ResultsDescriptive statistics revealed that 82.2% of the participants were female and their Academic Grade Point Average was 3.00 ± 0.48. As a result of the regression analysis, it was determined that students' age, gender, perception of academic achievement, status of receiving PA training and attitudes towards doing PA and self‐assessment significantly predicted their ASE score.ConclusionsStudents' ASE was found to be medium‐level, their attitudes towards peer and self‐assessment were high and SA and PA attitudes was associated with ASE.Patient or Public ContributionA total of 1401 undergraduate nursing students from five undergraduate universities participated in the study and responded to questions on ASE, peer assessment, self assessment, etc.
Synthesis and Structural Characterization of SiO2 Nanoparticles Using Extract of Gracilaria Crassa Via Green Chemistry Approach
Authors: Palanimuthu Vanathi , Periakaruppan Rajiv , Romanovski Valentin , Bharathi Ayyarappan , Vijai Selvaraj Karungan Selvaraj , Anukeerthana Somasundaram , Nishanthi Rajendran , Vanajadevi Gurumoorthy 
Published: November 2024

AbstractBiologically synthesized nanoparticles via biological entities are produced with less negative impact on the environment and without expensive chemicals, which have biocompatibility and are eco‐friendly. Gracilaria crassa is a well‐known marine red alga that is edible and unique and is the commercial source of agar and agarose production. In this work, Gracilaria crassa‐mediated SiO2 NPs were synthesized by the green synthesis method. In order to characterize the physicochemical properties of the synthesized SiO2 NPs, a variety of microscopic and spectroscopic approaches were used, including imaging with Field emission scanning electron microscopy, Energy‐dispersive X‐ray analysis, UV spectrophotometry, X‐ray diffraction analysis, Fourier‐transform infrared spectroscopy, Zeta potential, and Thermo gravimetric analysis. These results shown that Gracilaria crassa‐mediated SiO2 NPs were amorphous nature, negatively charged −15.5 mV and spherical shape in size of 20–50 nm. The antioxidant capacity of synthesised SiO2 NPs was examined by 2,2‐Diphenyl‐1‐picrylhydrazyl assay and it observed as IC50 value of 49.4 μg/mL denotes that could counteract the production of free radicals and oxidative stress. The characteristics of the synthesized Gracilara crassa‐mediated SiO2 NPs suggest their application as potential antioxidant agents.
Influence of different types of SiO2 nanoparticles in polyamic acid for enhanced dielectric and mechanical performance at room temperature
Authors: Singh Amit Kumar , Xue Wei 
Published: November 2024

AbstractIn power transmission applications, there is an increasing demand for insulating materials capable of maintaining high dielectric and mechanical strength across a broad temperature range. However, achieving effective insulating properties with a single polymer is challenging. Therefore, thin films of polymer‐based nanocomposites are under investigation. This study investigates the effects of three types of SiO2 nanoparticles, one as non‐coated and the other two with different surface coatings, in polyamic acid (PAA) utilizing four different solvents for SiO2 dispersion within the matrix, in achieving high dielectric and mechanical strength at room temperature. High‐voltage breakdown and tensile tests were performed to determine the dielectric and mechanical properties of nanocomposites, respectively. The breakdown structures were characterized using scanning electron microscopy. The characterization shows that both the nanoparticles and processing solvents have direct impact on the dielectric and mechanical performance of the samples. The combination of 3‐aminopropyl triethoxysilane (APTES) surface‐coated SiO2 and dimethyl sulfoxide solvent resulted in the highest performing dielectrics, with dielectric strengths of 141.15 kV/mm (alternating current, AC) and 184.60 kV/mm (direct current, DC) as well as superior mechanical properties with ultimate tensile strength of 64.34 MPa, yield strength of 43.11 MPa, and elastic modulus of 2405.05 MPa. These values represent a significant improvement of both dielectric and mechanical properties from the pure polymer by 13%–20%. The enhanced performance can be attributed to the surface functionalization of SiO2 nanoparticles with APTES that promotes molecular interactions, facilitates charge redistribution, and strengthens the interfacial adhesion when they are incorporated into PAA.Highlights
Performance of composite‐based dielectrics can be improved by material design.
Nanoparticles with surface functional groups enhance properties of composites.
Solvent to disperse nanoparticles plays a significant role in film quality.
Dielectric/mechanical properties of polymer nanocomposites are quantified.
Colombian natural fibers: Potential applications in sustainable natural fiber reinforced composites materials
Authors: Hidalgo‐Salazar Miguel A. , Correa‐Aguirre Juan P. , Román Allen J. , Gonzalez Ronalds , Vera Ramon , Osswald Tim A. 
Published: November 2024

AbstractUsing natural fibers in bio‐based product development offers a promising path toward an environmentally sustainable future. This study aims to characterize natural fibers obtained from food processing companies and artisans across Colombian regions, employing a methodology that can be extended to natural fibers characterization worldwide and supporting research focused on sustainable product development based on natural fibers. The thermal, mechanical, morphological, and surface properties of the fibers were measured using advanced techniques such as dynamic mechanical analysis‐DMA, thermogravimetry‐TGA, computed microtomograph, and 3D‐microscopy. The chemical composition was analyzed using Van Soest methodology and TGA thermogram deconvolution. Thermal characterization reveals that natural fibers start their degradation between 227 and 258°C, defining a safe thermal processing range for natural fiber‐reinforced polymer composites (NFRPC) products. Mechanical properties were measured at temperatures ranging from −50 to 150°C. Among the tested fibers, pineapple leaf fibers, hemp fibers, and toquilla straw exhibited superior mechanical performance up to 100°C suggesting their potential for developing bioproducts across various applications. In contrast, banana and coir coconut fibers showed lower tensile strength and tensile modulus. Surface roughness differs in the longitudinal and transverse directions, suggesting that chambira straw (Ra 0.067 mm), fique fibers (Ra 0.03 mm), and hemp and pineapple leaf fibers (Ra 0.021 mm) may be of interest for further investigation in NFRPC production. This research highlights the progress and challenges in utilizing natural fibers to develop sustainable products. It positively impacts regional economies, drives technological advancements, and expands the potential applications of natural fiber‐reinforced composites.Highlights
Novel micro‐CT technique reveals accurate cross‐sectional areas of natural fibers
Colombian natural fibers maintain stable tensile properties from −50 to 125°C
Toquilla straw shows highest strength‐to‐density ratio among studied fibers
Thermal analysis offers rapid verification of natural fiber chemical composition
Ashby charts allow comparison of natural fibers and their uses in composites.
Portal hypertension as an independent risk factor for cirrhotic cardiomyopathy: An investigation on its mechanism based on bioinformatics analysis
Authors: Hu Youwen , Yi Jing , Xiao Yangyang , Guo Li , He Bo , Degejirifu  , Wen Zhili 
Published: November 2024

AbstractAimsDespite being commonly found in patients with various etiologies of liver cirrhosis, cirrhotic cardiomyopathy (CCM) is often overlooked, and its mechanism remains unknown. This study aimed to illuminate the epidemiological data and risk factors of CCM and to explore its potential mechanisms through a bioinformatics analysis.MethodsClinical data were collected from January 2008 to December 2022 retrospectively, and patients were divided into the CCM and non‐CCM groups based on the criteria proposed by the 2005 World Congress of Gastroenterology. Independent risk factors for CCM were identified through a multivariate logistic regression analysis. CCM‐related genes were explored using the GeneCards database, and enrichment analysis was performed. Protein–protein interaction analysis was conducted using the Search Tool for the Retrieval of Interacting Genes (STRING) database, and hub genes were identified using Cytoscape software. The Transcriptional Regulatory Relationships Unraveled by Sentence‐based Text Mining (TRRUST) database was utilized to explore transcription factors (TFs), and a network regulatory diagram of TF‐gene pathways was constructed. Finally, potential drugs were predicted using the Drug Gene Interaction Database.ResultsA total of 965 patients with liver cirrhosis were included, among whom 563 (58.3%) were diagnosed with CCM. Portal hypertension (PHT) was identified as the only independent risk factor for CCM. The hub genes included IL6, TNF, TGFB1, IL1B, MMP9, and IL10. Enrichment analysis revealed that Forkhead box O (FoxO), mitogen‐activated protein kinase (MAPK), hypoxia‐inducible factor (HIF‐1), phosphoinositide 3‐kinase‐protein kinase B (PI3K‐AKT), interleukin (IL)‐17, tumor necrosis factor (TNF), vascular endothelial growth factor (VEGF), mammalian target of rapamycin (mTOR), Janus kinase/signal transducers and activators of transcription (JAK‐STAT), and transforming growth factor (TGF)‐beta pathways were enriched. TFs such as CEBPB, NFKB1, STAT1, STAT3, and SP1 were also implicated. Potential drugs included pravastatin and atorvastatin.ConclusionsThe morbidity associated with CCM was high, and PHT was the only independent risk factor. The mechanism may be related to inflammation, and statins may hold therapeutic promise.
Clinicopathological Significance of Extranodal Adipose Tissue Invasion in Metastatic Lymph Nodes in Patients With Prostate Cancer
Authors: Nagasaka Hirotaka , Sato Shinya , Suzuki Atsuto , Terao Hideyuki , Nakamura Yoshiyasu , Yoshihara Mitsuyo , Okubo Yoichiro , Washimi Kota , Yokose Tomoyuki , Kishida Takeshi , Miyagi Yohei 
Published: November 2024

ABSTRACTBackgroundLymph node (LN) metastasis is a poor prognostic factor in patients with prostate cancer. Elucidating the mechanisms underlying cancer progression in the metastatic microenvironment of LNs is crucial to establishing novel therapies. Adipocytes interact with cancer cells and regulate cancer progression. In this study, we aimed to clarify the clinicopathological significance of extranodal adipose tissue invasion in metastatic LNs and preoperative adipokine concentration in patients with prostate cancer exhibiting metastatic LNs.MethodsWe examined the pathological findings of primary and metastatic nodes and clinical information of 66 specimens from 46 patients with prostate cancer. A sub‐analysis was performed to assess the relationship between preoperative adiponectin/leptin concentrations and clinical/pathological findings in the blood samples of 56 patients with prostate cancer who either did or did not show LN metastasis.ResultsThe number of metastatic LNs in patients correlated with the involvement of adipose tissue and lymphovascular invasion (p = 0.039 and < 0.001, respectively). Preoperative adiponectin concentration was lower in patients with resected margin‐positive and extraprostatic extension‐positive primary cancers (p = 0.0071 and 0.02, respectively). Preoperative adiponectin concentrations were significantly lower in patients with metastatic LNs than in patients without LN metastasis (p < 0.001). Moreover, leptin concentrations were significantly higher in patients with metastatic LNs than in patients without LN metastasis (p < 0.001). In patients with metastatic LNs, preoperative adiponectin concentrations were significantly lower in patients with biochemical recurrence than in patients without biochemical recurrence (p = 0.031). There was no correlation between biochemical recurrence and pathological findings.ConclusionsThis is the first report on the detailed histopathological characteristics of prostate cancer with LN metastases and the significance of preoperative adiponectin concentration in predicting the pathological features of primary cancers. Also, adipokines are a significant prediction factor of LN metastases for prostate cancer patients. Adipose tissue and adipose‐secreting factors may be involved in the progression of metastatic and primary prostate cancer.
Population pharmacokinetics of selexipag for dose selection and confirmation in pediatric patients with pulmonary arterial hypertension
Authors: Axelsen Lene Nygaard , Kümmel Anne , Perez Ruixo Juan Jose , Russu Alberto 
Published: November 2024

AbstractSelexipag is an oral selective prostacyclin receptor agonist approved for the treatment of pulmonary arterial hypertension (PAH) in adults. To date, no treatment targeting the prostacyclin pathway is approved for pediatric patients. Our goal is to identify a pediatric dose regimen that results in comparable exposures to selexipag and its active metabolite JNJ‐68006861 as those shown to be efficacious in adult PAH patients. Extrapolation from the population pharmacokinetic (PK) model developed in adults (GRIPHON study; NCT01106014) resulted in the definition of three different pediatric body weight groups (≥9 to <25 kg, ≥25 to <50 kg, and ≥50 kg) with corresponding starting doses (100, 150, and 200 μg twice daily) and maximum allowed doses (800, 1200, and 1600 μg twice daily). The proposed pediatric dose regimen was subsequently tested in a clinical study (NCT03492177), including 63 pediatric PAH patients ≥2 to <18 years of age and a body weight range of 9.9–93.5 kg. The body weight‐adjusted dose regimen for selexipag resulted in comparable systemic exposures to selexipag and its active metabolite in pediatric patients as previously observed in adult PAH patients. Updating the adult selexipag population PK model provided overall consistent parameters and confirmed that the PK characteristics of selexipag and its active metabolite were comparable between pediatric and adult patients. The presented selexipag dose regimen for pediatric PAH patients is considered appropriate for continuing the clinical evaluation of the safety and efficacy of selexipag in pediatric patients ≥2 years of age.
Adaptive Fixed‐Time Sliding Mode Control for Trajectory Tracking of Uncertain Dynamical Systems
Authors: Yang Jianxiang , Fan Yiran , Mu Anle , Zhou Feihang , Li Nailu , Xiong Jianbin 
Published: November 2024

ABSTRACTThis paper introduces an innovative adaptive fixed‐time sliding mode control (SMC) method that eliminates chattering, enhancing trajectory tracking accuracy and robustness in nonlinear dynamical systems facing uncertainties and external disturbances. The proposed control scheme ensures fixed‐time convergence of system states to a predefined neighborhood around the origin, independent of initial conditions. An innovative adaptive tuning law is proposed to estimate the unknown upper bounds of synthetic uncertainties and disturbances without requiring prior knowledge. This law forces system states to trend to the sliding surface within a fixed time, achieving stabilization of tracking errors at the origin without undesirable chattering and while avoiding singularities. Comprehensive simulations and comparisons among four control strategies (C1, C2, C3, and C4) demonstrate that the proposed C1 control strategy outperforms others in terms of faster convergence speed, higher tracking accuracy, less chattering, and stronger robustness.
An Efficient 3D Point Cloud‐Based Place Recognition Approach for Underground Tunnels Using Convolution and Self‐Attention Mechanism
Authors: Ye Tao , Liu Ao , Yan Xiangpeng , Yan Xiangming , Ouyang Yu , Deng Xiangpeng , Cong Xiao , Zhang Fan 
Published: November 2024

ABSTRACTExisting place recognition methods overly rely on effective geometric features in the data. When directly applied to underground tunnels with repetitive spatial structures and blurry texture features, these methods may result in potential misjudgments, thereby reducing positioning accuracy. Additionally, the substantial computational demands of current methods make it challenging to support real‐time feedback of positioning information. To address the challenges mentioned above, we first introduced the Feature Reconstruction Convolution Module, aimed at reconstructing prevalent similar feature patterns in underground tunnels and aggregating discriminative feature descriptors, thereby enhancing environmental discrimination. Subsequently, the Sinusoidal Self‐Attention Module was implemented to actively filter local descriptors, allocate weights to different descriptors, and determine the most valuable feature descriptors in the network. Finally, the network was further enhanced with the integration of the Rotation‐Equivariant Downsampling Module, designed to expand the receptive field, merge features, and reduce computational complexity. According to experimental results, our algorithm achieves a maximum score of 0.996 on the SubT‐Tunnel data set and 0.995 on the KITTI data set. Moreover, the method only consists of 0.78 million parameters, and the computation time for a single point cloud frame is 17.3 ms. These scores surpass the performance of many advanced algorithms, emphasizing the effectiveness of our approach.