bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modelling and numerical simulation of sequencing strategies for connected and autonomous vehicles at signal-free intersections
Authors: Zhang Jiaqi , Yang Qiaoli 
Published: July 2024

Abstract
The signal-free intersections employ connected and automated vehicle technology to manage vehicles passing through the intersection. Due to conflicting traffic flows in opposition directions, a proper sequencing of Connected and Autonomous Vehicles (CAVs) at signal-free intersections becomes critical to impacting intersection traffic performance. Based on an examination of CAV queueing rules under the most common sequencing strategies of First-Come-First-Serve (FCFS) and Longest-Queue-First (LQF), commonly employed as benchmarks for evaluating diverse innovative approaches to signal-free intersections, we propose a Dynamic-Queue-Service (DQS) strategy that is tailored to accommodate high traffic demand. To explicitly elucidate the impact of diverse traffic demand in conflicting directions on the queue uncertainty and stochasticity of CAVs, as well as to investigate how various sequencing strategies influence the equity of CAV traffic at signal-free intersections with regard to CAV queueing dynamics under different strategies, we have developed a double-input traffic queueing model and derived a range of metrics, including the queue length, delay, conditional queue length, and variance of queue length. In addition, for the three strategies, we performed a series of numerical simulations to investigate the queueing process of CAVs at signal-free intersections. Numerical results show that under different levels of traffic demand in the conflicting directions, the FCFS, LQF, and DQS strategies output diverse traffic queueing performances, and the DQS strategy is confirmed to be well-suited for the situation of high traffic demand in both conflicting directions.
Controlled fabrication of freestanding monolayer SiC by electron irradiation
Authors: Da 笪 Yunli 蕴力 , Luo 罗 Ruichun 瑞春 , Lei 雷 Bao 宝 , Ji 季 Wei 威 , Zhou 周 Wu 武 
Published: July 2024

Abstract
The design and preparation of novel quantum materials with atomic precision are crucial for exploring new physics and for device applications. Electron irradiation has been demonstrated as an effective method for preparing novel quantum materials and quantum structures that could be challenging to obtain otherwise. It features the advantages of precise control over the patterning of such new materials and their integration with other materials with different functionalities. Here, we present a new strategy for fabricating freestanding monolayer SiC within nanopores of a graphene membrane. By regulating the energy of the incident electron beam and the in-situ heating temperature in a scanning transmission electron microscope (STEM), we can effectively control the patterning of nanopores and subsequent growth of monolayer SiC within the graphene lattice. The resultant SiC monolayers seamlessly connect with the graphene lattice, forming a planar structure distinct by a wide direct bandgap. Our in-situ STEM observations further uncover that the growth of monolayer SiC within the graphene nanopore is driven by a combination of bond rotation and atom extrusion, providing new insights into the atom-by-atom self-assembly of freestanding two-dimensional (2D) monolayers.
MRGazer: decoding eye gaze points from functional magnetic resonance imaging in individual space
Authors: Wu Xiuwen , Hu Rongjie , Liang Jie , Wang Yanming , Qiu Bensheng , Wang Xiaoxiao 
Published: July 2024

Abstract

Objective. Eye-tracking research has proven valuable in understanding numerous cognitive functions. Recently, Frey et al provided an exciting deep learning method for learning eye movements from functional magnetic resonance imaging (fMRI) data. It employed the multi-step co-registration of fMRI into the group template to obtain eyeball signal, and thus required additional templates and was time consuming. To resolve this issue, in this paper, we propose a framework named MRGazer for predicting eye gaze points from fMRI in individual space. Approach. The MRGazer consists of an eyeball extraction module and a residual network-based eye gaze prediction module. Compared to the previous method, the proposed framework skips the fMRI co-registration step, simplifies the processing protocol, and achieves end-to-end eye gaze regression. Main results. The proposed method achieved superior performance in eye fixation regression (Euclidean error, EE = 2.04°) than the co-registration-based method (EE = 2.89°), and delivered objective results within a shorter time (∼0.02 s volume−1) than prior method (∼0.3 s volume−1). Significance. The MRGazer is an efficient, simple, and accurate deep learning framework for predicting eye movement from fMRI data, and can be employed during fMRI scans in psychological and cognitive research. The code is available at https://github.com/ustc-bmec/MRGazer.
DP-MP: a novel cross-subject fatigue detection framework with DANN-based prototypical representation and mix-up pairwise learning
Authors: He Xiaopeng , Li Haoyu , Yu Peng , Wu Hao , Chen Badong 
Published: July 2024

Abstract
Abstract. Objective. Electroencephalography (EEG) is widely recognized as an effective method for detecting fatigue. However, practical applications of EEG for fatigue detection in real-world scenarios are often challenging, particularly in cases involving subjects not included in the training datasets, owing to bio-individual differences and noisy labels. This study aims to develop an effective framework for cross-subject fatigue detection by addressing these challenges. Approach. In this study, we propose a novel framework, termed DP-MP, for cross-subject fatigue detection, which utilizes a Domain-Adversarial Neural Network (DANN)-based prototypical representation in conjunction with Mix-up pairwise learning. Our proposed DP-MP framework aims to mitigate the impact of bio-individual differences by encoding fatigue-related semantic structures within EEG signals and exploring shared fatigue prototype features across individuals. Notably, to the best of our knowledge, this work is the first to conceptualize fatigue detection as a pairwise learning task, thereby effectively reducing the interference from noisy labels. Furthermore, we propose the Mix-up pairwise learning (MixPa) approach in the field of fatigue detection, which broadens the advantages of pairwise learning by introducing more diverse and informative relationships among samples. Results. Cross-subject experiments were conducted on two benchmark databases, SEED-VIG and FTEF, achieving state-of-the-art performance with average accuracies of 88.14% and 97.41%, respectively. These promising results demonstrate our model’s effectiveness and excellent generalization capability. Significance. This is the first time EEG-based fatigue detection has been conceptualized as a pairwise learning task, offering a novel perspective to this field. Moreover, our proposed DP-MP framework effectively tackles the challenges of bio-individual differences and noisy labels in the fatigue detection field and demonstrates superior performance. Our work provides valuable insights for future research, promoting the application of brain-computer interfaces for fatigue detection in real-world scenarios.&#xD;
Gibbs measures for hardcore-solid-on-solid models on Cayley trees
Authors: Jahnel Benedikt , Rozikov Utkir 
Published: July 2024

AbstractWe investigate the finite-statep-solid-on-solid (p-SOS) model forp=∞on Cayley trees of orderk⩾2and establish a system of functional equations where each solution corresponds to a (splitting) Gibbs measure of the model. Our main result is that, for three states,k=2,3and increasing coupling strength, the number of translation-invariant Gibbs measures behaves as1→3→5→6→7. This phase diagram is qualitatively similar to the one observed for three-statep-SOS models withp > 0 and, in the case ofk = 2, we demonstrate that, on the level of the functional equations, the transitionp→∞is continuous.
On the acceptance of high carbon taxes in low- and middle-income countries: a conjoint survey experiment
Authors: Malerba Daniele , Never Babette , Fesenfeld Lukas , Fuhrmann-Riebel Hanna , Kuhn Sascha 
Published: July 2024

Abstract
Changing consumption patterns from growing middle-classes with consequent rising energy use and emissions in low- and middle-income countries (LMICs) present key challenges for the energy transition and climate change mitigation. Carbon taxes are an effective policy instrument to counter these developments, yet concerns about low public acceptability hinder their introduction. Here, we seek to fill a research gap and identify publicly acceptable carbon tax designs in LMICs. We provide novel evidence from three conjoint experiments with 2700 middle-class respondents in Ghana, Peru, and the Philippines. We show that overall, the majority in all three countries supports even high taxes of USD-PPP 75/tCO2 per year, irrespective of specific policy design features. The support for a very high tax rate is especially high if revenues are recycled for environmental purposes. Thus, governments in LMICs have political leeway to finance the transition to a low-carbon economy via carbon taxes. Moreover, revenue recycling for the poorest receives high support from important subgroups. These insights are crucial to achieving an effective, acceptable, and just carbon tax policy design.
Spermatogenesis in mouse testicular organoids with testis-specific architecture, improved germ cell survival and testosterone production
Authors: Richer Guillaume , Goyvaerts Cleo , Marchandise Lorna , Vanhaecke Tamara , Goossens Ellen , Baert Yoni 
Published: July 2024

Abstract
This study presents a biphasic approach to overcome the limitations of current testicular organoid (TO) cultures, including histological heterogeneity, germ cell loss and absence of spermatogenesis. Agarose microwells were utilized to create TOs from prepubertal C57BL/6 J testicular cells. First emphasis was on improving germ cell survival during the initial 2-week reorganization phase by comparing α-MEM + 10% knockout serum replacement (KSR) medium, known to support TO generation in mice, to three optimized media (1–3). Cell densities and culture dynamics were also tested to recreate histological resemblance to testes. After optimizing germ cell survival and cell organization, the effect of growth factors and immunomodulation through CD45+ immune cell depletion or dexamethasone (DEX) supplementation were assessed for enhancing spermatogenesis during the subsequent differentiation phase. Testicular cells self-reorganized into organoids resembling the testicular anatomical unit, characterized by one tubule-like structure surrounded by interstitium. Media 1–3 proved superior for organoid growth during the reorganization phase, with TOs in medium 3 exhibiting germ cell numbers (7.4% ± 4.8%) comparable to controls (9.3% ± 5.3%). Additionally, 37% ± 30% demonstrated organized histology from 32 × 103 cells under static conditions. Switching to α-MEM + 10% KSR during the differentiation phase increased formation efficiency to 85 ± 7%, along with elevated germ cell numbers, testosterone production (3.1 ± 0.9 ng ml−1) and generation of γ-H2AX+ spermatid-like cells (steps 8–11, 1.2% ± 2.2% of the total). Adding differentiation factors to the α-MEM increased spermatid-like cell numbers to 2.9% ± 5.9%, confirmed through positive staining for CREM, transition protein 1, and peanut agglutinin. Although, these remained diploid with irregular nuclear maturation. DEX supplementation had no additional effect, and immune cell depletion adversely impacted TO formation. The manipulability of TOs offers advantages in studying male infertility and exploring therapies, with scalability enabling high-throughput chemical screening and reducing animal usage in reproductive toxicity and drug discovery studies.
Quantitative and deep learning based fourier transform infrared radiation and tensile characteristics study on chemically treated hibiscus rosa-sinensis plant fibers
Authors: J P Supriya , Shetty Sawan , Shetty Raviraj , Nayak Rajesh , Maddasani Srinivasulu , Hegde Adithya 
Published: July 2024

Abstract
Incorporation of natural fibers with Fiber Reinforced Polymers (FRPs) is a promising avenue for sustainable and high-performance composite materials. The fibers, derived from outer bark portion of plants, offer significant merits such as renewability, low cost, and eco-friendly. Unique mechanical and physical properties, and widespread availability of Hibiscus Rosa-sinensis have made them subject of intense research interest. The present study investigated the chemically treatment of HRS Fibers using Sodium Hydroxide (NaOH), Potassium Permanganate (KMnO4), and Acetic Acid (CH3COOH) bat varying weight percentages (3, 4, 5 Wt%) and solutionizing times (1, 2, 3 h) based on Taguchi’s L27 orthogonal array. Fourier Transform Infrared (FT-IR) analysis revealed significant changes in O–H, C–H stretching, C=O moiety, aromatic ring, and C–O/C–C stretching. Potassium Permanganate treatment at 4 Wt% and 3 h of solutionizing time has yielded the best results. Multi-Layer Perceptron Artificial Neural Network (MLP-ANN) has been successfully applied to accurately predict the output physical characteristics of chemically treated HRS fibers using experimental data. Further Single Fiber Pull-out test results in Potassium Permanganate at 4 Wt% and 3 h solutionizing time as best sample with highest Tensile Strength and Modulus. This research underscores the effectiveness of the chemical treatment process in enhancing the properties of HRS plant fibers for potential composite applications.
Edge and dense attention U-net for atrial scar segmentation in LGE-MRI
Authors: Li Gaoyuan , Liu Mingxin , Lu Jun , Ma Jiquan 
Published: July 2024

Abstract
The segmentation of atrial scars in LGE-MRI images has huge potential value for clinical diagnosis and subsequent treatment. In clinical practice, atrial scars are usually manually calibrated by experienced experts, which is time-consuming and prone to errors. However, automatic segmentation also faces difficulties due to myocardial scars’ small size and variable shape. The present study introduces a dual branch network, incorporating edge attention, and deep supervision strategy. Edge attention is introduced to fully utilize the spatial relationship between the scar and the atrium. Besides, dense attention is embedded in bottom layer to solve feature disappearance. At the same time, deep supervision accelerates the convergence of the model and improves segmentation accuracy. The experiments were conducted on the 2022 atrial and scar segmentation challenge dataset. The results demonstrate that the proposed method has achieved superior performance.
Stress tolerance activity and diversification of endophytic fungi from the medicinal plant Abutilon indicum
Authors: M Haseena , Arumugam Sabaridasan , Gopal Suresh , Salmen Saleh H , Aljawdah Hossam M , Munusamy Murugan A 
Published: July 2024

Abstract
This study aimed to assess the diversity of endophytic fungi isolated from Abutilon indicum using morphological and molecular techniques. The isolates were exposed to various levels of salinity, temperatures, and heavy metals, including Ag2+ and Zn2+, at concentrations of 3.6 and 11.5 mM. Thirty root segments were isolated from each plant and cultured on potato dextrose agar plates. Four endophytic fungi were randomly isolated from infected root segments, belonging to the genera Aspergillus, Meyerozyma, and Penicillium. The phylogenetic analysis revealed significant diversity among the isolates of Aspergillus welwitschiae, Aspergillus indologenus, Meyerozyma carpophila, and Penicillium citrinum, with a 99% similarity in their sequences. Most isolates were able to thrive under salt stress conditions at NaCl concentrations of 200 mM (26%), 400 mM (24%), 600 mM (21%), 800 mM (13%), and 1000 mM (16%). Tolerant to temperature, endophytes could survive in the range of 25 °C to 35 °C but could not survive above 50 °C. Heavy metals tolerance of 89% of these isolates led to a significant decrease in biomass production when exposed to Ag2+. Endophytic fungal isolates showed decreased sensitivity to Zn2+, but between 33% and 60% showed strong growth in conditions with high levels of Zn2+. These findings revealed that endophytic fungi of A. welwitschiae enhanced growth when exposed to various stress conditions. Our findings indicate that the presence of fungal endophytes in different stress conditions leads to significant growth, and this could be useful for phytoremediation purposes.
Where ideology meets private interest: the three-part composition of climate obstruction in the United States
Authors: Hall Galen , Loy Loredana , Brulle Robert J , Schell-Smith Kennedy , Hu Ming-May , Trollback Stina 
Published: July 2024

Abstract
A network of organizations working to oppose climate action, called the climate change countermovement (CCCM), has long been a critical yet highly opaque subject of study for social scientists concerned with climate politics. We leverage a new combined dataset of boards of directors, financial contributions, and texts produced by CCCM members to characterize its sources of support and social structure. We show that foundations tend to make more frequent and larger donations to CCCM nonprofits when they are linked through a board member. We also show that CCCM nonprofits which are more distant from each other in the social network of board members produce different climate change discourses. Community detection methods robustly detect three communities within the CCCM: conservative think tanks (CTT), oil and gas trade associations, and utility, coal, and manufacturing trade associations, each with unique goals within the countermovement. The findings suggest that the climate countermovement is an interface among these communities which together ensure that climate action obstruction is achieved on different but complementary fronts, through both discursive and more concrete policy efforts. This paper also introduces a new way of understanding organized climate obstruction and makes significant methodological contributions in the study of social movements and countermovements.
Indirect magneto-ionic effect in FeSi2/Si nanocomposite induced by electrochemical lithiation and delithiation
Authors: Prasch M , Würschum R , Topolovec S 
Published: July 2024

Abstract
A nanocomposite consisting of iron disilicide nanocrystals embedded in a Si matrix was prepared from industry-grade ferrosilicon by ball milling and subsequent heat treatment. By tailoring the heat treatment temperature either the metallic α-FeSi2 or the semiconducting β-FeSi2 phase could be made the dominant one, as indicated by x-ray diffraction. Magnetization curve and zero-field cooled/field cooled measurements revealed that ferromagnetic and superparamagnetic centers are present in the nanocomposites, which could be attributed to Fe-rich defective regions at the surface of the iron disilicide nanocrystals. For both nanocomposites, containing either mainly the α or β phase, we could show that the magnetization can be varied by about 40% by electrochemical lithiation and delithiation of the surrounding Si matrix, with up to 6.5% of the magnetization change being reversible. These variations could be attributed to the formation of additional Fe-rich magnetic regions, induced by a local change of the Fe/Si fraction at the FeSi2/Si interfaces, and their subsequent partial elimination. Thus, this work demonstrates a new concept for how an ‘indirect magneto-ionic effect’ can be obtained in composite materials consisting of a phase prone to the electrochemical ion uptake (i.e. the Si matrix) and a magnetic phase (i.e. the FeSi2 nanocrystals).
Optimal path planning using bidirectional rapidly-exploring random tree star-dynamic window approach (BRRT*-DWA) with adaptive Monte Carlo localization (AMCL) for mobile robot
Authors: Ayalew Wubshet , Menebo Muluken , Merga Chala , Negash Lebsework 
Published: July 2024

Abstract
Path planning is an important task for mobileF service robots. Most of the available path-planning algorithms are applicable only in static environments. Achieving path planning becomes a difficult task in an unknown, dynamic environment. To solve the path planning problem in an unknown dynamic environment, this paper proposes a Bidirectional Rapidly-exploring Random Tree Star-Dynamic Window Approach (BRRT*-DWA) algorithm with Adaptive Monte Carlo Localization (AMCL). Bidirectional Rapidly-exploring Random Tree Star(BRRT*) is used to generate an optimal global path plan, Dynamic Window Approach(DWA) is a local planner and Adaptive Monte Carlo Localization(AMCL) is used as a localization technique. The robot can navigate using the map file of the unknown environment created by Simultaneous Localization And Mapping (SLAM) and the data from the Light Detection and Ranging (LiDAR) sensor while avoiding dynamic and static obstacles. In addition, the object identification algorithm You Only Look Once (YOLO) was adopted, trained, and used for the robot to recognize objects and people. Results obtained from both simulation and experiment show the proposed method can achieve better performance in a dynamic environment compared with other state-of-the-art algorithms.
Nitrogen-vacancy centers in diamond: discovery of additional electronic states
Authors: Luu Minh Tuan , Tayefeh Younesi Ali , Ulbricht Ronald 
Published: July 2024

Abstract
Nitrogen-vacancy (NV) defect centers in diamond are key to applications in quantum sensing and quantum computing. They create localized electronic states in the diamond lattice with distinct population relaxation pathways following photoexcitation that ultimately enable its unique properties. The defect is known to exist in two charge states: neutral and negative, with respectively one and two known optically-active electronic transitions. Here, we report on the observation of a large number of hitherto undiscovered excited electronic states in both charge states as evidenced by distinct optical transitions in the infrared to ultraviolet part of the spectrum. These transitions are observed by monitoring the electronic relaxation of NV centers after photoexcitation using transient absorption spectroscopy, directly probing transient phenomena occurring on timescales from femtoseconds to microseconds. We also for the first time probed the electron transfer dynamics from the

3

E

state of NV− to nearby single-substitutional nitrogen defects (N

s

) that leads to the well-known effect of NV photoluminescence quenching.
Rhodian Associations and Religious Experience
Authors: Zachhuber Juliane 
Published: July 2024

AbstractThis chapter moves away from the overwhelmingly civic focus of the previous sections and examines the lively world of Rhodian associations. Although these are often named after gods, their religious activities are little known. Building on their naming conventions, the chapter compares the religious tastes and cultic affiliations of these groups against the backdrop of Rhodian religion, as established in the rest of the book. Religious spaces and festivals allow an insight into the intersection between public and private religious experience, leading us to question the usefulness of this distinction. Finally, the chapter looks at the religious models these associations might offer for other spheres of Rhodian life, in particular the navy, and to what extent these spaces offered access to new religious experiences (such as initiation).