bluuebunny/crossref_metadata_2025_split huggingface dataset:
Overcoming Challenges in Technology Adoption: A Case Study in Fiber Optic Sensing
Authors: Hooper M. , Jalilian E. , Hull J. 
Published: March 2024

Abstract
Adoption of cutting-edge digitization tools in the energy sector is often challenged by an underestimation of value-in-use stemming from a lack of publicly available information regarding the breadth of technological capabilities and associated use-case economics. This paper seeks to address such challenges – as they pertain to advanced fiber optic sensing systems for monitoring of pipelines and other energy infrastructure - by providing readers with a comprehensive overview of the full range of operational applications and current economics for the state-of-the-art in the field, with a focus on case studies and value add benefits that have emerged more recently for many operators.
Distributed fiber optic sensing (DFOS) continues to see strong commercial growth in the Canadian energy sector, largely due to its exceptional suitability for real time detection of pinhole-level leaks along the full length of long-run pipeline assets. Combining the remarkable sensitivity and lightspeed transmission capabilities of DFOS with the analytical horsepower of the latest machine learning (ML) strategies allows pipeline operators to accurately detect and characterize even minute integrity events (like the pinhole leaks noted above) in real-time, regardless of when or where these occur within their vast asset networks. As a result, many operators have gained at least some familiarity with distributed fiber optic sensing (DFOS) systems and a basic understanding of their performance capabilities and general economics.
The downside of this singular focus on the leak detection capability and use case is, of course, that industry may elect not to adopt – or at a minimum fail to exploit the full potential of - this rapidly evolving technology, particularly as novel applications dramatically increase DFOS’ value in use. Rapid commercial growth has also driven down DFOS costs as deployment methods and system architectures are optimized over millions of pipeline meters, resulting in an often-substantial gap between perceived adoption cost and real project economics. This combination of capability underestimation and life-cycle cost overestimation presents a major challenge for many technology adoption scenarios, with analysis made all the more difficult by a general lack of publicly available project details.
This paper reviews case studies from recent DFOS deployments, with a focus on the operational value-in-use realized for a cross-section of commercial applications (i.e., pig tracking, real-time remediation support, temporary pipeline (‘layflat’) management, etc.) as well as the broader business case for life cycle technology costs (i.e., ROI metrics) aimed at providing an accurate understanding of both the costs and capabilities of advanced DFOS systems for integrity management of energy infrastructure. Ultimately the paper will help operators better understand the current state of DFOS technology and make informed decisions regarding its potential and business case to support their existing operations.
Construction of intelligent visual design system based on convolutional neural network under the background of big data
Authors: Geng Chunxia 
Published: March 2024

Abstract
In recent years, artificial intelligence has been initially applied to the visual design process, which has had a certain impact on the traditional design methods and working modes. Through the analysis of the working principle of the key technology of artificial intelligence design, the generation antagonism network (GAN), this paper summarizes the advantages and limitations of the existing automatic design methods, and puts forward the transformation path and specific methods of visual design working mode oriented to automation design efficiency optimization and new technology application form innovation under the background of new technology. With the rapid development of cloud computing and artificial intelligence, there are more and more applications in the cloud based on artificial intelligence as a service. Among them, artificial intelligence based on convolutional neural network is widely used. Convolution neural network endogenous control is the first fusion of endogenous security ideas in deep neural network model security control. Based on the core operation structure of convolutional neural network, the key control points of the endogenous control model are proposed; By tightly coupling the endogenous control unit at the control point, a convolutional neural network endogenous control model is designed and proposed.
X gene mutations of Hepatitis B virus and impact on chronic hepatitis B infection in CHB three-generations in the family
Authors: naderi Malihe , Hosseini Seyed Masoud , Behnampour Naser , Shahramian Iraj , Moradi Abdolvahab 
Published: March 2024

Abstract
This study focused on detecting mutational patterns in the X-gene of the HBV genome in three-generations of CHB patients. Ninety CHB patients were analyzed, revealing the highest similarity in X-gene sequences between mothers and children in two-generations (79.3%). The N-terminal of the X-gene showed frequent mutations, with notable occurrences at positions C1491G (25%), C1500T (43.4%), G1613T (23.9%), and G1658T (33.4%). Mutations were more prevalent in HBeAg-negative patients, indicating a significant difference (P-value = 0.03). A1762T/G1764A mutations were present in 15.6% of patients, demonstrating significant relevance. These mutational patterns may aid in predicting clinical outcomes and identifying susceptibility to hepatocellular HCC in patients.
The status of academic interventional radiologists in Germany with focus on women: How can we do better?
Authors: Blum Sophia Freya Ulrike , Dewald Cornelia Lieselotte Angelika , Becker Lena , Staudacher Emona , Franke Mareike , Katoh Marcus , Hoffmann Ralf-Thorsten , Rohde Stefan , Paprottka Philip Marius , Wacker Frank , Westphalen Kerstin , Bruners Philipp , Gebauer Bernhard , Das Marco , Uller Wibke 
Published: March 2024

Abstract
Purpose
The aim was to characterize the framework conditions in academic interventional radiology (IR) in Germany with focus on differences between genders.
Materials and Methods
After IRB approval, all members of The German Society for Interventional Radiology and Minimally Invasive Therapy (n = 1,632) were invited to an online survey on work conditions in clinical and academic practice. The academic practice subset contained questions about research challenges: networking, funding, working hours and time spent with research. Statistical comparisons were undertaken with the Fisher's exact test, Wilcoxon rank sum test or Pearson's Chi-squared test.
Results
267 questionnaires were available resulting in a general response rate of 16.4%. Two-hundred of them were fully completed. 40% of these (78/200) were involved in academic IR (71% men vs. 29% women, p < .01) and were therefore eligible for further analysis. Of these, 6% worked part-time (2% vs. 17%, p < .05). 90% of them spent less than 25% of their research during their paid working hours, and 41% performed more than 75% of their research during leisure time. 28% received exemption for research. 88% were (rather) satisfied with their career. One in two participants successfully applied for funding, with higher success rates among male applicants (90% vs. 75%) and respondents with protected research time (93% vs. 80%). Compared to men, women rated their entrance in academic IR as harder (p < .05), their academic IR-career as more important (p < .05), felt less noticed at congresses (93% vs. 53%, p < .01), less confident (98% vs. 71%, p < .01), and not well connected (77% vs. 36%, p < .01).
Conclusion
Women and men did research under the same framework conditions; however, women were underrepresented. Future programs should generally focus on protected research and gather female mentors to advance academic IR in Germany.
Growth Differentiation Factor 15 (GDF15) Expression in the Heart After Myocardial Infarction and Cardioprotective Effect of Pre-Ischemic rGDF15 Administration
Authors: Dogon Geoffrey , Rigal Eve , Potel Eliot , Josse Marie , Rochette Luc , Bejot Yannick , Vergely Catherine 
Published: March 2024

Abstract
Clinical data consider growth differentiation factor-15 GDF15 as a prognostically unfavourable biomarker in cardiovascular diseases, while experimental studies suggest its cardioprotective potential. This study focuses on the direct cardiac effects of GDF15 during ischemia-reperfusion (I/R) injury in Wistar male rats, employing concentrations relevant to patients at high cardiovascular risk. Initially, we examined circulating levels and heart tissue expression of GDF15 in rats subjected to I/R and Sham operations in vivo. Subsequently, we evaluated the cardiac effects of GDF15 both in vivo and ex vivo, administering recombinant GDF15 either before ischemia (preconditioning) or at the onset of reperfusion (postconditioning). We compared infarct sizes and recovery of cardiac contractile parameters between control and rGDF15 treated rats. Contrary to our expectations, I/R did not elevate GDF15 plasma levels compared to Sham-operated rats. However, cardiac expression at both protein and mRNA levels increased in the infarcted zone of the ischemic heart after 24 hours of reperfusion. Notably, preconditioning with rGDF15 exhibited a cardioprotective effect, reducing infarct size both in vivo and ex vivo, while enhancing the recovery of cardiac contractile parameters ex vivo. However, postconditioning with rGDF15 did not alter infarct size or the recovery of contractile parameters either in vivo or ex vivo. These findings reveal, for the first time, that short-term exogenous administration of rGDF15 before ischemia, at physiologically relevant levels, protects the heart against I/R injury in both in vivo and ex vivo settings. The latter situation suggests that rGDF15 can operate independently of the inflammatory, endocrine and nervous systems, presenting GDF15 as a direct and potent cardioprotective properties against ischemia-reperfusion injury.
From Data to Action: Flood Forecasting Leveraging Graph Neural Networks and Digital Twin Visualization
Authors: Roudbari Naghmeh Shafiee , Punekar Shubham Rajeev , Patterson Zachary , Eicker Ursula , Poullis Charalambos 
Published: March 2024

Abstract

Forecasting floods encompasses significant complexity due to the nonlinear nature of hydrological systems, which involve intricate interactions among precipitation, landscapes, river systems, and hydrological networks. Recent efforts in hydrology have aimed at predicting water flow, floods, and quality, yet most methodologies overlook the influence of adjacent areas and lack advanced visualization for water level assessment. Our contribution is twofold: firstly, we introduce a graph neural network model equipped with a graph learning module to capture the interconnections of water systems and the connectivity between stations to predict future water levels. Secondly, we develop a simulation prototype offering visual insights for decision-making in disaster prevention and policy-making. This prototype visualizes predicted water levels and facilitates data analysis using decades of historical information. Focusing on the Greater Montreal Area (GMA), particularly Terrebonne, Quebec, Canada, we apply our model and prototype to demonstrate a comprehensive method for assessing flood impacts. By utilizing a digital twin of Terrebonne, our simulation tool allows users to interactively modify the landscape and simulate various flood scenarios, thereby providing valuable insights into preventive strategies. This research aims to enhance water level prediction and evaluation of preventive measures, setting a benchmark for similar applications across different geographic areas.
Does Perceived Media Values Affect Customers' Trust in Media-based Brands?
Authors: Liao Wenfang , Tian Ziqi , imeni Mohsen , Edalatpanah S. A. 
Published: March 2024

Abstract

This study aimed to investigate the effect of the Perceived Media Value (PMV) on Trust in Media-based Brands (TMB). The study population consisted of all customers of Digikala's online store. The number of samples (n = 384) chosen through a random sampling process was obtained using Cochran's sample size formula. The data were collected using the PMV scale. The questionnaire reliability was confirmed by applying Cronbach's alpha. Structural Equation Modeling (SEM) was utilized in the data analysis with the help of AMOS and SPSS software. The PMV and its components (including information, entertainment, networking, and social status value) significantly positively affected TMB. In addition, social status, networking, information, and entertainment value had the strongest relationships with TMB, respectively.
Distinct contributions of microbial and plant residues to SOC during ecosystem primary succession in a Tibetan glacier foreland
Authors: Liu Yongqin , Liu Yang , Ji Mukan , Li Saifei , Ao Deng , An Shaoshan , Liang Chao 
Published: March 2024

Abstract

Soil organic carbon (SOC) rapidly accumulates during ecosystem primary succession in glacier foreland. This makes it an ideal model for studying soil carbon sequestration and stabilization, which are urgently needed to mitigate climate change. Here, we investigated SOC dynamics in the Kuoqionggangri glacier foreland on the Tibetan Plateau. The study area along a deglaciation chronosequence of 170-year comprising three ecosystem succession stages, including barren ground, herb steppe, and legume steppe. We quantified amino sugars and lignin phenols to assess the contributions of microbial and plant residues to SOC, and used FT-ICR mass spectroscopy to analyze the composition of dissolved organic matter. We found that herbal plant colonization increased SOC by enhancing ecosystem gross primary productivity, while subsequent legumes development decreased SOC, due to increased ecosystem respiration from labile organic carbon inputs. Plant residues were a greater contributor to SOC than microbial residues in the vegetated soils, but they were susceptible to microbial degradation compared to the more persistent and continuously accumulating microbial residues. Our findings revealed the organic carbon accumulation and stabilization process in early soil development, which provides mechanism insights into carbon sequestration during ecosystem restoration under climate change.
2D graphene oxide films expand functionality of photonic chips
Authors: Moss David , Wu Jiayang , Zhang Yuning , Hu Junkai , Yang Yunyi , Jin Di , Liu Wenbo , Huang Duan , jia baohua 
Published: March 2024

Abstract
On-chip integration of two-dimensional (2D) materials with unique structures and properties endow integrated devices with new functionalities and improved performance. With high flexibility in ways to modify its properties and compatibility with integrated platforms, graphene oxide (GO) is an exceptionally attractive 2D material for hybrid integrated photonic chips. Here, we demonstrate novel functionalities beyond the capability of photonic integrated circuits, by harnessing unique property changes induced by photo-thermal effects in 2D GO films. These include all-optical control and switching, optical power limiting, and non-reciprocal light transmission. The 2D layered GO films are integrated onto photonic chips with precise control of their thickness and size. Benefitting from the broadband optical response of 2D GO films, all three functionalities feature a very wide operational optical bandwidth. By fitting the experimental results with theory, we determine the changes in GO film properties induced by the photo-thermal effects, revealing interesting insights about the physics of 2D GO films. These results highlight the versatility of 2D GO films in implementing new functions for integrated photonic devices for a wide range of applications.
Association between dietary vitamin C intake and migraine in adults: A cross-sectional study of the National Health and Nutrition Examination Survey
Authors: Zhao Dehua , Long Xiaoqing , Wang Jisheng 
Published: March 2024

Abstract
Objective:This study aim to evaluate the association between dietary vitamin C intake and the risk of migraine in adult individuals.
Methods: This cross-sectional study utilized data from the National Health and Nutrition Examination Survey (NHANES) conducted between 1999 and 2004. Logistic regression models, restricted cubic spline (RCS) regression, and stratified analyses were employed to assess the association between dietary vitamin C intake and migraine.
Results: This study included 4101 participants, of whom 702 (17.12%) experienced migraine. The study revealed an inverse association between dietary vitamin C intake and migraine risk (OR=0.89, 95% CI: 0.83-0.96, P=0.002) after adjusting for all covariates. When vitamin C intake was categorized, the adjusted OR (95% CI) for migraine risk in Q 4 (highest vitamin C intake ) was 0.64 (95% CI: 0.49-0.84, P=0.001) compared with Q1 (lowest vitamin C intake). The RCS regression showed a linear inverse relationship between dietary vitamin C intake and migraine risk (P for non-linearity=0.449). The findings remained consistent, and no significant interactions were found among different groups.
Conclusion: Dietary vitamin C intake was independently associated with migraine, and a linear negative relationship was found betweenvitamin C intake and the risk of migraine.
Characterization of the bZIP Family Transcription Factors in Astragalus membranaceus and Their Expression under Drought Stress
Authors: Wang Jiemin , Rong Zhengpu , Shi Weihong , Zhao Jingqiao , Wang Wenshuai , Ma Donglai , Zheng Yuguang , Sun Huigai , Han Xiaowei 
Published: March 2024

Abstract
Astragalus membranaceus has important medicinal and ecological values, but with global changes, its growth is often negatively affected by abiotic stresses such as drought stress. The bZIP family transcription factors (TF) play important roles in plant growth and development, and the response to abiotic stresses. However, systematic identification of the bZIP gene family in A. membranaceus and their expressions under drought stress have not been reported. In the present study, genome-wide identification, chromosome localization, phylogenetic analysis, motif analysis and domain prediction of the bZIP family genes in A. membranaceus were performed. A total of 74 bZIP family members were identified in A. membranaceus, which are divided into 13 subfamilies, and members in each subfamily have similar gene structures and conserved motifs. The bZIP family members were unequally distributed on the 9 chromosomes of A. membranaceus. Four bZIP genes were generated via tandem duplication, including Am01G021190 and Am01G021150, and 45 were formed though segmental duplication. Compared with Zea mays and Oryza sativa, the bZIP genes of A. membranaceus have more collinearity with that of Medicago truncatula. The promoter analysis showed that the bZIP transcription factor family was rich in plant hormone response elements and abiotic stress response elements. The analysis of transcriptome data and qRT-PCR indicated that several bZIP TFs including AmZIP46 was involved in the response to drought stress. Further experiments showed that AmbZIP46 is only localized in the nucleus and has transcriptional activation activity. This study provided important data for understanding the biological functions of the bZIP family transcription factors in A. membranaceus.
Anaesthetic Challenge in an Infant with Achondroplasia who Developed Tetraparesis after Whiplash Injury: A case report
Authors: Nedomová Barbora , Tichá Ľubica , Zahradníková Petra , Jakešová Salome , Hanko Martin , Chrenko Robert 
Published: March 2024

Abstract

Background: This report presents the case of an infant with dwarfism due to achondroplasia who experienced acute tetraparesis after a cervical whiplash injury. We describe the considerations in the anaesthetic management of this patient, including the potential risks associated with this rare disease.
Case presentation: A 1-year-old boy with achondroplasia presented with acute tetraparesis after a whiplash injury. The initial craniocervical computed tomography showed a small posterior fossa, narrow foramen magnum, and ventriculomegaly without any fractures or dislocations.However, magnetic resonance imaging revealed foramen magnum stenosis, signal changesrepresenting myelopathy in the spinal cord extending from the craniocervical junction to the C2 level, oedema of the medulla oblongata, and traction injury of the posterior atlantoaxial ligament. Initial conservative therapy resulted in partial remission of tetraparesis. The patient underwent microsurgical decompression of the craniocervical junction under general anaesthesia, which was performed by a paediatric anaesthesiologist. For airway management, the spontaneously breathing patient underwent fibreoptic-guided nasal intubation under deep inhalation anaesthesia. Ultrasound navigation facilitated venous access. Surgery was performed with the patient in the prone position with careful monitoring. The patient showed complete remission of neurological symptoms at 3 months postoperatively.
Conclusions: Herein, we discuss the specifics of anaesthesia and its role in the optimal management of an infant with dwarfism due to achondroplasia and an injured upper cervical myelon and lower brain stem. The role of paediatric anaesthesiologists in the management of this rare condition has been highlighted.
DAEPK:Domain-Adaptive Text Feature Enhancement Technology Integrating Prior Knowledge Domain In Text Classification
Authors: Yang Jie , Nyima Tashi , Qi Jindong 
Published: March 2024

Abstract
The scarcity of resources, lack of labeled texts, and insufficient corpora pose significant challenges to many specialized classification problems. It increases the difficulty of small language and domain-specific classification problems. In this paper, we propose a new approach to address this problem: by assigning multi-dimensional additional weights to words using external knowledge, thereby enhancing text features in low-resource domains. This is achieved by introducing the concepts of 'prior domains' and 'Adjusted Term Frequency Vectors (Adjust-TFs). Then, we propose a Domain Adaptive Text Feature Enhancement Method that combines prior domains and utilizes knowledge transfer to solve the classification problem. We conducted experiments across various data sizes on multilingual text categorization datasets. Experimental results demonstrate that our method notably enhances classification accuracy across diverse sample conditions, particularly in low-resource scenarios. This method still performs well in the few-shot setting, which, to some extent, alleviates the training problem of DNNs under this condition. Furthermore, we identify conditions that lead to improved performance in low-resource settings, providing valuable insights for future research.