bluuebunny/crossref_metadata_2025_split huggingface dataset:
Adaptive Visual-Inertial Odometry Using SuperGlue and Dynamic EKF with Information-Based Confidence Estimation
Authors: ASIL Ufuk , Nasibov Efendi 
Published: September 2024

Abstract

This study presents an innovative Visual-Inertial Odometry (VIO) approach for Unmanned Aerial Vehicles (UAVs). The proposed system integrates the modern deep learning-based SuperGlue algorithm with an information based adaptive Extended Kalman Filter (EKF). The system establishes a dynamic confidence estimation mechanism using image entropy, intensity variation, and motion blur metrics, thereby providing robust pose estimation even in challenging environmental conditions. Thanks to the superior performance of advanced transformer-based feature matching methods like SuperGlue, the proposed loosely-coupled sensor fusion technique approaches the accuracy of traditional tightly-coupled approaches, potentially offering an alternative to these methods. Comprehensive experiments conducted on the EuRoC MAV dataset demonstrate that the proposed method provides significant improvements compared to conventional approaches. Particularly in challenging scenarios, an improvement of approximately 50% was observed in the estimation of quaternions and Euler angles. This study reveals that loosely-coupled sensor fusion, when combined with advanced feature matching techniques and adaptive filtering strategies, can offer a robust alternative to tightly-coupled approaches. The results highlight the potential applications of the proposed method in fields such as robotic navigation, autonomous vehicles, and augmented reality. Additionally, the Python code associated with our study has been shared as open-source on GitHub for use in other academic studies at "\href{https://github.com/ufukasia/Adaptive-VIO-Odometry}{https://github.com/ufukasia/Adaptive-VIO-Odometry}".
GPER1/ACACB are potential target genes associated with intracranial aneurysm and vascular endothelial cell senescence
Authors: Zeng Lang , Lu Xuanzhen , Huang Yuzhen , Tu Qin , He Yongqi , Fang Ziwei , Nie Shuyi , Huang Yi , Yu Maling , Min Xiaoli , Zhang Cuntai , Yu Jiasheng , Zhang Le 
Published: September 2024

Abstract

The incidence of intracranial aneurysm (IA) is significantly higher in postmenopausal women than in men and premenopausal women, a disparity traditionally attributed to the decline in estrogen levels. However, the function and expression of estrogen receptors (ERs), including ERα, ERβ, and GPER1, in vascular tissues suggests the involvement of estrogen-independent mechanisms in vascular aging and related pathologies. To investigate this hypothesis and to elucidate the pathophysiology of IA from the perspective of vascular endothelial cell senescence (VECS), a comprehensive bioinformatics analysis was performed using three IA datasets (GSE75436, GSE122897, GSE54083) and two VECS datasets (GSE214476, GSE102397) from the GEO database. This study identified 452 genes that were significantly downregulated and may share common pathogenic molecular mechanisms in both IA and VECS. Notably, GPER1 was the only ER that was consistently downregulated in both IA and VECS. Further weighted gene co-expression network analysis and module clustering identified ACACB as highly co-expressed with GPER1 and negatively correlated with both IA and VECS. In vitro validation confirmed that reduced GPER1 expression during VECS may exacerbate endothelial senescence, suggesting a potential estrogen-independent protective role of GPER1 in preventing IA and VECS. In addition, pharmacological predictive analysis identified PD0325901, SCH772984 and selumetinib as potential therapeutic agents targeting both GPER1 and ACACB, offering a novel strategy for the treatment of IA and VECS-related pathologies, highlighting the therapeutic potential of targeting these molecules in these conditions.
Cu(β-diketonato)2 Bathochromic shifts from the Ultraviolet towards the Visible region
Authors: Conradie Marrigje M 
Published: September 2024

Abstract

The DFT calculated Ultra-Violet/Visible properties of 11 different Cu(β-diketonato)2 complexes are presented. The selected β-diketonato ligands on the Cu complex contains none, one or two aromatic rings. Experimentally measured absorbance maxima range of the Ultra-Violet/Visible is observed at 295–390 nm and the calculated range is 302–425 nm, for the 11 complexes in this study. More aromatic rings on the ligand lead to Bathochromic shifts of the experimentally measured absorbance maxima from the of the Ultra-Violet towards the Visible region. Absorbance maxima of the Cu(β-diketonato)2 complexes with no aromatic rings on the ligand are found to be predominantly ligand-to-metal charge transfer excitations. Whereas introducing one or two aromatic rings shifts the excitations to predominantly ligand-to-ligand charge transfer.
Exploring Trust In Artificial Intelligence Among Primary Care Stakeholders: A Mixed-Methods Study
Authors: Sides Teresa , Kbaier Dhouha , Farrell Tracie , Third Aisling 
Published: September 2024

Abstract

Background:
Artificial intelligence (AI) in healthcare has grown rapidly in recent years. The United Kingdom government recognises AI’s potential to enhance National Health Services with increased funding available. Despite this, AI acceptance presents unique challenges in primary care (PC), characterised by fragmented structures and multiple government departments. The organisational levels within PC are categorised as macro, meso, and micro levels. Many existing studies focus on micro-level stakeholders.
Methods:
This study investigates the factors affecting trust in artificial intelligence (AI) within PC settings through a mixed-methods approach. An online survey addressed this research gap by encompassing stakeholder perspectives at all organisational levels. To validate the results in-depth semi-structured interviews were conducted with some survey participants enabling triangulation of the data.
Results:
The results demonstrate the crucial role of meso-level stakeholders in facilitating trust in and acceptance of AI. Thematic analysis identified key barriers which include: a requirement for skills development, concerns about job displacement and factors associated with resistance to change. The study also highlighted disparities in care and potential inequities arising from varied AI usage rates. Public perception, leadership approval and media influence were identified as critical factors needing careful management to ensure successful AI integration in healthcare.
Conclusion:
The key contribution to the research field is the data from all stakeholder levels on the perceptions of AI for PC. Despite the study's robustness, limitations such as self-selection bias and low interview participation were noted. The findings underscore the necessity for ethical AI systems, targeted stakeholder engagement, and strategies to ensure equitable and effective AI implementation in PC. Further research in the relationship between trust and equity of care would be beneficial to the important research in the field of AI for PC.
Synthesis and characterization of starch-g-polyacrylamide-co-polylactic acid hydrogel for the potential wound dressing application
Authors: Mondal Md. Ibrahim H. , Kadri H. Jahan , Ahmed Firoz , Rahman Md. Hasinur 
Published: September 2024

Abstract

A starch-based hydrogel was synthesised by direct grafting of polylactic acid (PLA) and acrylamide onto starch. Potassium persulphate (K2S2O8) was used as an initiator and citric acid (CA) was used as an eco-friendly cross-linker. The purpose of the graft was to test an alternative anti-microbial wound dressing material. The FTIR, XRD, SEM and EDX data confirmed that the copolymerisation and cross-linking of the hydrogel was successful. Tests, with chemical reactions; yielded TGA data, which confirmed the enhanced thermal and mechanical properties of the augmented hydrogel. The hydrogel swelled up to 481% at pH 7.20 and exhibited a water vapour transmission rate of 148 g/m2 per day. The hydrogel also showed anti-microbial activity against both gram-positive (S. aureus) and gram-negative (E. coli) bacteria. Its zone of inhibition was 21 mm and 19 mm with a mild anti-oxidant property. This synthesised hydrogel is completely non-toxic and bio-degradable, making it especially suitable as a wound dressing material.
Automatic Modulation Recognition Method Basedon Multimodal I/Q-FRFT Fusion
Authors: Ning Meng , Zhou Fan , Wang Wei , Wang Yang , Fei Shunchao , Wang Jian 
Published: September 2024

Abstract

Automatic modulation recognition (AMR) is a key technology in the domain of cognitive radio communications. Accurately identifying the modulation schemes of signals is crucial for enhancing the robustness and reliability of communication systems. The existing methods usually use deep learning technology to intelligently model the single modality such as in-phase quadrature (I/Q). However, single modality has the disadvantages of low recognition rate and limited feature expression ability. In this paper, we propose an innovative automatic modulation recognition method based on multimodal fusion of I and Fractional Fourier Transform (FRFT). Specifically, we first design the entire multimodal approach as an intermediate fusion mode, that is, performing the unimodal representation first and then multimodal fusion later. In the multimodal fusion stage, we introduce a Multimodal Processing Unit (MPU), which realizes the enhancement and aggregation of different modes by learning the complementary features between and within modalities. Furthermore, we employ contrast learning to categorize signals of different modulation into positive and negative samples to enhance the robustness of the multimodal features. In order to verify the effectiveness of the proposed method, we conduct experiments on two public datasets, RML2016.10a and HisarMod2019.1. The experimental results indicate that the multimodal approach consistently outperforms the unimodal methods significantly, achieving the state-of-the-art.
The effect of high-quality voice on observing employees’ helping behavior: A moderated mediation model
Authors: Liang Liang , Li Zhongqiu , Shang Hangbiao , Zhao Feng , Liu Sitong 
Published: September 2024

Abstract

Background: Grounding on social information processing theory and theory of cooperation and competitiveness, this study aims to explore the impact of voicers’ high-quality voice on observing employees’ helping behavior while considering the mediator of perceptions of benefit to resources, along with the moderating role of goal competitiveness.
Method: This study employed a two-wave study to examine the theoretical model. A total of 226 employees in China were used to test our hypotheses by adopting hierarchical multiple regression method. SPSS and MPLUS were used to analyze data.
Results: The findings revealed that voicer’s high-quality voice positively predicted observing employees’ helping behavior, and perceptions of benefit to resources mediated this relationship. Furthermore, goal competitiveness weakened the positive relationship between voicers’ high-quality voice and observing employees’ perceptions of benefit to resources as well as the positive indirect effects of voicers’ high-quality voice on observing employees’ helping behavior via perceptions of benefit to resources.
Conclusion: Voice quality is vital for organizational effectiveness but related research is limited. Hence, scholars encourage future research to shift attention from voice frequency to voice quality. Our research contributes to the emerging literature on employee voice quality by revealing the positive effect of high-quality voice on observing employees’ helping behavior through perceptions of benefit to resources and exploring the boundary condition (i.e., goal competitiveness) of this relationship. Our research is among the first to explore the influence of high-quality voice in observing employees’ helping behavior, enriching the literature on voice quality.
Identification of $tqg$ flavor-changing neutral current interactions using machine learning techniques
Authors: Ko Byeonghak , Heo Jeewon , Jang Woojin , Lee Jason Sang Hun , Roh Youn Jung , Watson Ian James , Yang Seungjin 
Published: September 2024

Abstract

Flavor-changing neutral currents (FCNCs) are forbidden at tree level in the Standard Model (SM), but they can be enhanced in physics Beyond the Standard Model (BSM) scenarios.To test these potential enhancements, we investigate the production of a top quark and an associated parton through the $tqg$ FCNC process, which originates from the $tug$ and $tcg$ vertices.The $tqg$ FCNC events can be produced with a top quark and either an associated gluon or quark, while SM only has events with a top quark and an associated quark. We apply machine learning techniques to distinguish the $tqg$ FCNC events from the SM backgrounds, including $qg$-discrimination variables.We use the Boosted Decision Tree (BDT) method as a baseline classifier, assuming that the leading jet originates from the associated parton.We compare with a Transformer-based deep learning method known as the Self-Attention for Jet-parton Assignment (SaJa) network, which allows us to include information from all jets in the event, regardless of their number, eliminating the necessity to match the associated parton to the leading jet.The SaJa network with qg-discrimination variables has the best performance, giving expected upper limits on the branching ratios $\Br(t \to qg)$ that are 25--35\% lower than those from the BDT method.
GCD-SPKAU:A Model-based Meta-learning with Sharing Prior Knowledge Among User-clusters classified through Graph Community Detection for Cold-Start Recommendation
Authors: Dai Yang , Wang Heyu , Xu Fulin 
Published: September 2024

Abstract

The cold-start problem has consistently been a significant challenge in recommender systems, particularly in the initial stage for new users or new items. This is due to the lack of sufficient historical interaction data, which presents a significant obstacle to the development of effective personalized recommendations. Nowadays, a considerable number of researchers and scholars have investigated the issue of cold-start problems, resulting in the emergence of a multitude of sophisticated methodologies aimed at addressing this challenge. Among these, meta-learning has emerged as a particularly promising avenue of enquiry. Most existing meta-learning algorithms assume that a priori knowledge can be shared globally among all users. However, a problem arises that information sharing among users with widely different interests is usually ineffective, which leads to suboptimal solutions. Therefore, it is important to improve the meta-learning model. As a result, this paper proposes a new, improved meta-learning model idea, which first invokes the clustering algorithm of Graph Community Detection to classify different categories of user clusters, and then obtains the unique prior knowledge belonging to themselves in each user cluster, and finally enables the prior knowledge to be shared among the clusters of those categories that have the most effective effects. We compare the performance advantages and disadvantages of the new model and the traditional model in cold-start recommendation, verify the effectiveness of our new idea in improving the performance of cold-start recommendation, and discuss its potential applications and future research directions.
Porcine milk small extracellular vesicles modulate peripheral blood mononuclear cell proteome in vitro
Authors: Avila Gabriela , Bonnet Muriel , Viala Didier , Dejean Sebastian , Agazzi Alessandro , Lecchi Cristina , Ceciliani Fabrizio 
Published: September 2024

Abstract

Small extracellular vesicles (EVs) are a subtype of nano-sized extracellular vesicles that mediate intercellular communication. EVs can be found in different body fluids, including milk. Monocytes internalize porcine milk EVs and modulate immune functions in vitro by decreasing their phagocytosis and chemotaxis while increasing their oxidative burst This study aimed to assess the impact of porcine milk EVs on the porcine peripheral blood mononuclear cells (PBMC) proteome. Porcine PBMC were incubated with porcine milk EVs or medium as a control. Extracted proteins were then analyzed using nano-LC-MS/MS. A total of 1584 proteins were identified. The supervised multivariate statistical analysis, sparse variant partial least squares – discriminant analysis (sPLS-DA) for paired data identified discriminant proteins (DP) that contributed to a clear separation between the porcine milk EV treated cells and control groups. A total of 384 DP from both components were selected. Gene Ontology (GO) enrichment analysis with ProteINSIDE provided the evidence that the DP with a higher abundance in porcine milk EVs, like TLR2, APOE, CD36, MFGE8, were mainly involved in innate immunity and EV uptake processes. These results provide a proteomics background to the immunomodulatory activity of porcine milk EVs and to the potential mechanisms used by immune cells to internalize them.
Radiological evaluation of pituitary lesions by CT, plain radiography and MRI
Authors: Arian Maha Mejwal , khattab Khalid 
Published: September 2024

Abstract

Background: The pituitary is an important endocrine gland located at the base of the brain. It is involved in nearly all processes of homeostasis, as well as growth and development. This gland commonly develops pathology, which may result in a mass effect on adjacent intracranial structures or be hormonally active.
Methods and materials: Study location: Al-Mouwasat University Hospital (Endocrine + Surgery + Radiology Departments)., Study type: A retrospective cross-sectional study, Study duration: From February 2020 to December 2023, focusing on cases that underwent MRI of the pituitary gland and radiological images.
Results: Number of patients who underwent lateral radiographs of the skull with a focus on the sella turcica: 250 patients: normal images (normal sella turcica) 82%, abnormal sella turcica 18%, enlargement of the sella turcica 42%, calcifications within the sella turcica 17%, destruction and erosion of the anterior clinical processes 5%, destruction and erosion of the posterior clinical processes 7%, destruction and erosion of the anterior and posterior clinical processes 22%, deformity of the sella turcica 13%, calcifications around the sella turcica 12%. We found that the tumor size of 1-1.5 cm was 40%, the tumor size of 1.5-2 cm was 42%, the tumor size of 2-3 cm was 18%, the rate of pituitary dwarfism was 18%, the small adenoma with low density appeared in 10%, and the large adenoma with high density appeared in 14%.
Conclusion: Standard views of the pituitary gland can be obtained by image reconstruction and formatting to standard coronal, sagittal, and axial anatomic landmarks. Since MRI can acquire imaging data in multiple planes, patient positioning is also less critical.
Discovering Maternal Minds: Exploring Maternal Mind-Mindedness for Preschoolers
Authors: Ambreen Mominah 
Published: September 2024

Abstract

Most studies on mind-mindedness (MM) and its role in child development have been conducted predominantly in Western countries. To address this gap, we conducted the first-ever qualitative study in Pakistan with a sample of working and nonworking mothers (N = 30) of preschoolers (aged 2–6 years). Our aim was to assess their ability to describe their children in a mind-directed manner. Each mother was asked to describe her child. The transcripts of these four- to five-minute speech samples were coded for (i) mental attributes (comments that refer to or describe the child's mental life), (ii) behavioral attributes (comments that refer to the child's behavior), (iii) physical attributes (physical appearance, age, position in the family), (iii) general attributes (any vague comment), and (iv) self-referential attributes (comments in which the primary reference is self-focused rather than describing the child). The results showed that 19 out of 30 mothers could appropriately describe their child in the context of their mental characteristics, as calculated by the index score given in the coding manual (Meins & Fernyhough, 2015). In addition, variations in mothers' responses on the basis of their occupation status and the child's birth order were also assessed qualitatively. Working mothers displayed less mind-mindedness than nonworking mothers did, and mothers with only one child were also found to be less mind-minded. This is the latest and entirely new study conducted in Pakistan and therefore offers a breakthrough in research. Potential limitations include a lack of generalizability and possible bias in mothers’ descriptions to appear socially desirable.
EBSD mapping of Cu-Fe-sulfides reveal microstructures enriched in critical/precious metals and resolve deformation histories
Authors: King Samuel A. , Cook Nigel J. , Ciobanu Cristiana L. , Ehrig Kathy , Rodriguez Yuri Tatiana Campo , Gilbert Sarah , Basak Animesh 
Published: September 2024

Abstract
Chalcopyrite (CuFeS2) and bornite (Cu5FeS4) from the Olympic Dam Cu-U-Au-Ag deposit (South Australia) are characterized using electron backscatter diffraction (EBSD) to identify microstructures and their correlations with trace element concentrations measured by laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). Natural chalcopyrite is shown to be a rich source of micro-structural and -textural information, preserving &lt;110&gt; and &lt;001&gt; crystallographic preferred orientations (CPO), {110} and {112} twin systems, grain boundary migration, foam textures and subgrain boundaries. Selected examples of chalcopyrite illustrate different aspects of its behavior and relationship with bornite across the mineralogically zoned deposit. The oriented stress imposed by brecciation and/or fluid fluxes at Olympic Dam, alongside temperature, pressure and strain rate, are shown to induce a variety of microstructures preserved in chalcopyrite. Microstructures can therefore be used to elucidate sequential stages of low to medium temperature (&lt;300 °C) ore evolution. Although pyrite microstructures are already routinely used to understand higher temperature ore evolution, complementary microstructural study of chalcopyrite coexisting with pyrite has the potential to reveal deformational events across a more complete range of temperatures. In ore systems that lack obvious evidence for post-mineralization deformation, chalcopyrite is particularly well suited to unravel episodes of low-to medium-temperature overprinting.
EBSD mapping reveals what appears as single grains of chalcopyrite in reflected light is in fact aggregates composed of ~100 individual grains. In contrast, analyzed bornite displays overwhelming crystallographic homogeneity. Rare instances of misorientation in bornite are all associated with replacement and, if correlated with EBSD analysis of coexisting chalcopyrite and its inclusions (e.g., cobaltite), can be used to discern the origin and evolution of different bornite associations. LA-ICP-MS trace element mapping of chalcopyrite aggregates indicate that grain boundaries host concentrations of Pb, Bi, Ag and Sb, with twin boundaries displaying a weaker concentration of the same elements. Bornite grain boundaries are also enriched in Pb. These observations confirm the critical role played by microstructures in Cu-(Fe)-sulfides as traps for Pb, a non-target contaminant in copper concentrates, as well as new evidence for the physical state of Ag and potential value-add critical metals like Bi and Sb. The preferential occurrence of Pb, Bi, Ag and Sb along permeable grain boundaries may incentivize efforts to remove contaminants and/or recover by-products via leaching.