bluuebunny/crossref_metadata_2025_split huggingface dataset:
Morphological features of magnetorheological elastomer degradation under a natural weathering environment
Authors: Johari Mohd Aidy Faizal , Mazlan Saiful Amri , Abdul Aziz Siti Aishah , Zaini Nursyafiqah , Nordin Nur Azmah , Ubaidillah Ubaidillah , Upadhyay Ramesh V. , Mohd Yusuf Shahir 
Published: January 2024

AbstractIt is well known in the field of materials science that a substance’s longevity is significantly influenced by its environment. Everything begins with the initial contact on a material’s surface. This influence will then deteriorate and have an extended negative impact on the strength of the material. In this study, the effect of natural weathering in tropical climates on magnetorheological elastomer (MRE) was investigated through microstructural evaluation to understand the aging behavior of the environmentally exposed MRE. To understand and elucidate the process, MREs made of silicone rubber and 70 wt% micron-sized carbonyl iron particles were prepared and exposed to the natural weathering of a tropical climate for 90 days. The MRE samples were then mechanically tensile tested, which revealed that Young’s modulus increased, while elongation at break decreased. Surface degradation due to weathering was suspected to be the primary cause of this condition. Using scanning electron microscopy (SEM), the degradation of MRE was investigated as a function of morphological evidence. Upon examination through SEM, it was noted that the weathering effects on the morphology of the exposed samples showed distinct characteristics on the degraded surfaces of the MRE, including numerous microvoids, cavities, and microcracks. While these features were not prominent for the MRE itself, they bear resemblance to the effects observed in similar materials like rubber and elastomer. An atomic force microscope (AFM) is used to investigate the surface topography and local degradation conditions. This observation revealed a distinctive degradation characteristic of the MRE in connection to natural weathering in tropical climates. The surface damage of the MRE samples became severe and inhomogeneous during the environmental aging process, and degradation began from the exposed MRE surface, causing the mechanical characteristics of the MRE to significantly change.
Development of a neural network-based automated eyelid measurement system
Authors: Nam Yoonsoo , Song Taekyung , Lee Jaesung , Lee Jeong Kyu 
Published: January 2024

AbstractThe purpose of this study was to assess the clinical utility and reliability of an automated eyelid measurement system utilizing neural network (NN) technology. Digital images of the eyelids were taken from a total of 300 subjects, comprising 100 patients with Graves’ orbitopathy (GO), 100 patients with ptosis, and 100 controls. An automated measurement system based on NNs was developed to measure margin–reflex distance 1 and 2 (MRD1 and MRD2), as well as the lengths of the upper and lower eyelids. The results were then compared with values measured using the manual technique. Automated measurements of MRD1, MRD2, upper eyelid length, and lower eyelid length yielded values of 3.2 ± 1.7 mm, 6.0 ± 1.4 mm, 32.9 ± 6.1 mm, and 29.0 ± 5.6 mm, respectively, showing a high level of agreement with manual measurements. To evaluate the morphometry of curved eyelids, the distance from the midpoint of the intercanthal line to the eyelid margin was measured. The minimum number of divisions for detecting eyelid abnormalities was determined to be 24 partitions (15-degree intervals). In conclusion, an automated NN-based measurement system could provide a straightforward and precise method for measuring MRD1 and MRD2, as well as detecting morphological abnormalities in the eyelids.
Modeled foraminiferal calcification and strontium partitioning in benthic foraminifera helps reconstruct calcifying fluid composition
Authors: Jia Qicui , Zhang Shuo , Watkins James M. , Devriendt Laurent S. , Huang Yuefei , Wang Guangqian 
Published: January 2024

AbstractForaminifera are unicellular organisms that inhabit the oceans. They play an important role in the global carbon cycle and record valuable paleoclimate information through the uptake of trace elements such as strontium into their calcitic shells. Understanding how foraminifera control their internal fluid composition to make calcite is important for predicting their response to ocean acidification and for reliably interpreting the chemical and isotopic compositions of their shells. Here, we model foraminiferal calcification and strontium partitioning in the benthic foraminiferaCibicides wuellerstorfiandCibicidoides mundulusbased on insights from inorganic calcite experiments. The numerical model reconciles inter-ocean and taxonomic differences in benthic foraminifer strontium partitioning relationships and enables us to reconstruct the composition of the calcifying fluid. We find that strontium partitioning and mineral growth rates of foraminiferal calcite are not strongly affected by changes in external seawater pH (within 7.8–8.1) and dissolved inorganic carbon (DIC, within 2100–2300 μmol/kg) due to a regulated calcite saturation state at the site of shell formation.
Generation of long-chain fatty acids by hydrogen-driven bicarbonate reduction in ancient alkaline hydrothermal vents
Authors: Purvis Graham , Šiller Lidija , Crosskey Archie , Vincent Jupiter , Wills Corinne , Sheriff Jake , Xavier Cijo , Telling Jon 
Published: January 2024

AbstractThe origin of life required membrane-bound compartments to allow the separation and concentration of internal biochemistry from the external environment and establish energy-harnessing ion gradients. Long-chain amphiphilic molecules, such as fatty acids, appear strong candidates to have formed the first cell membranes although how they were first generated remains unclear. Here we show that the reaction of dissolved hydrogen and bicarbonate with the iron-rich mineral magnetite under conditions of continuous flow, alkaline pH and relatively low temperatures (90 °C) generate a range of functionalised long-chain aliphatic compounds, including mixed fatty acids up to 18 carbon atoms in length. Readily generated membrane-forming amphiphilic organic molecules in the first cellular life may have been driven by similar chemistry generated from the mixing of bicarbonate-rich water (equilibrated with a carbon dioxide-enriched atmosphere) with alkaline hydrogen-rich fluids fed by the serpentinisation of the Earth’s iron-rich early crust.
Mechanistic insights into the incorporation of higher alpha-olefins into acrylate copolymers via photoATRP
Authors: Sharma Bhawna , Verma Akash , Tak Anuj , Saini Swati , Bhati Kapil , Rajagopala Rao Tammineni , Kumar Umesh 
Published: January 2024

Visible light-driven SR & NI photoATRP with CuIIBr2/L yielded acrylate-α-olefin copolymers (Đ ≤ 1.13) incorporating up to 30% α-olefins. DFT revealed low activation energy barriers (14.3 kcal mol−1 and 17.8 kcal mol−1) for PCA2 and PCB2 formation.
Three‐dimensional geometry‐based channel modeling and simulations for reconfigurable intelligent surface‐assisted uav‐to‐ground MIMO communications
Authors: Wang Muyan , Chen Xiao , Wang Sicheng , Shi Wangqi 
Published: January 2024

AbstractConsisting of a large number of passive reflectors, reconfigurable intelligent surface (RIS) has gained traction as an approach to enhance communication quality. The specular reflection assumption is common when ideal conditions are considered. In this paper, an anomalous‐reflector model was found for each RIS reflection unit, deviating from the specular reflector assumption, and the impacts of the aperture area and radiation pattern of the RIS reflecting elements are taken into account. A three‐dimensional (3D) geometry‐based RIS‐assisted channel model is proposed for stochastic multiple‐input multiple‐output (MIMO) unmanned aerial vehicle (UAV)‐to‐ground communications. The RIS is deployed on an additional UAV in the proposed model, which assists the UAV transmitter for reflecting its own signals to the mobile receiver (MR) on the ground level, thereby boosting the quality of signal transmission. In order to achieve a perfect beam alignment towards the desired direction, the reflection phase is regulated by considering the propagation distances among UAV, RIS, and MR.
Real‐world image deblurring using data synthesis and feature complementary network
Authors: Wei Hao , Ge Chenyang , Qiao Xin , Deng Pengchao 
Published: January 2024

AbstractMany learning‐based approaches to image deblurring have received increasing attention in recent years. However, the models trained on existing synthetic datasets do not generalize well to real‐world blur, resulting in undesirable artifacts and residual blur. This work attempts to address this problem from two aspects: training data synthesis and network architecture. To narrow the domain gap between synthetic and real domains, a realistic blur synthesis pipeline to generate high‐quality blurred data is proposed. Since the blur is non‐uniform and has different scales and degrees, a parallel feature complementary module to fully exploit the local and non‐local information, which improves the feature representation and helps the network to perceive the non‐uniform blur, is developed. In addition, a spatial Fourier reconstruction block to facilitate correct detail recovery in the spatial and Fourier domains is introduced. Based on these two designs, an effective encoder–decoder network for deblurring is designed. Extensive experiments demonstrate the validity and superiority of the proposed blur synthesis method and deblurring network. In particular, the proposed deblurring network can achieve superior or comparable performance to Restormer, while saving 70% of network parameters and 53% of floating point operations (FLOPs).
Improving estimation performance of compressive sensing‐based multiple‐input multiple‐output radar using electronic beamsteering
Authors: Schurwanz Max , Mietzner Jan , Hoeher Peter Adam 
Published: January 2024

AbstractTwo‐dimensional direction‐of‐arrival (DoA) estimation in azimuth and elevation via radar systems equipped with uniform rectangular arrays (URAs) will play an important role in various application areas—most distinctively in future urban air mobility settings with unmanned aerial vehicles. A key factor is the fast and reliable provision of target detections in terms of range and DoA for safe autonomous operation of the vehicle using on‐board antenna arrays with compact installation size. The authors present a technique for improving the performance of DoA estimation using compressive sensing in conjunction with multiple‐input multiple‐output arrays with electronically steered beams in the transmit direction. The simulation study investigates the impact of different design considerations on radar signal processing performance. An optimisation of a radar system using electronic beamsteering in the transmit domain is presented numerically. Based on the architecture of the URAs used, performance and detection accuracy can be improved.
Granulomatose mit Polyangiitis und mikroskopische Polyangiitis
Authors: Klapa Sebastian , Arnold Sabrina , Lamprecht Peter 
Published: January 2024

ZusammenfassungDie Granulomatose mit Polyangiitis (GPA) und mikroskopische Polyangiitis (MPA) sind zwei zur ANCA-assoziierten Vaskulitis (AAV) zählende Entitäten. Beiden Erkrankungen liegt eine systemische nekrotisierende Kleingefäßvaskulitis zugrunde, die jedes Organ betreffen kann. Bei der GPA ist zusätzlich eine in der Regel den Respirationstrakt betreffende extravaskuläre nekrotisierende granulomatöse Entzündung vorzufinden. Das klinische Bild wird in der Mehrzahl der Fälle durch ein pulmorenales Syndrom mit alveolärer Hämorrhagie und rapid-progressiver Glomerulonephritis sowie weitere Organmanifestationen bestimmt. Bei der GPA imponiert zudem die fast regelhafte Mitbeteiligung des oberen Respirationstrakts. Die GPA ist mit Anti-Neutrophilen zytoplasmatischen Autoantikörpern (ANCA) mit einer Spezifität für die Proteinase 3 (PR3-ANCA) und die MPA für Myeloperoxidase (MPO-ANCA) assoziiert. Die immunsuppressive Therapie richtet sich nach der Krankheitsaktivität und Schwere der Organbeteiligung.
Ultra-wide-angle and broadband metamaterial absorber based on monopole top loading antenna and its reciprocity
Authors: Wang Aixia , Li Lei , Zhang Gaiping , Wang Wenjie , Fu Xinmin , Wang Jiafu 
Published: January 2024

In this paper, an ultra-wide-angle and broadband metamaterial absorber with a monopole top loading structure (MA-MTLS) was proposed. The resistive films printed on the dielectric are on the top layer. The dielectric square cylindrical shells with resistive films on the outside are in the middle, and a metal plate is on the bottom layer. The whole structure can be regarded as a top loading monopole antenna that has a good omnidirectional radiation capability. According to reciprocity, when a composite structure is used as an absorber, it will have a good absorption performance. The impedance matching characteristics were demonstrated by Smith chart and equivalent circuit, and then, the absorption performance was optimized. The simulated results show that the absorption of the MA-MTLS is more than 90% under TM polarized waves of 3.6–13.8 GHz as the incident angle changes from 0° to 80°. When the incident angle increases to 83°, the absorption is higher than 80% in the frequency band of 3.7–14.5 GHz. At the stage of experiment, the dielectric substrate was made by three-dimensional printing technology, the resistive films on the top layer were printed using screen printing techniques, and the resistive films on the outside of the square cylindrical shells were completed by pasting. The consistency between the experimental results and simulation data indicates that the design method is feasible and has good application prospects.
An analysis of the legal regime for agricultural marketing in India
Authors: Vohra Mehak , Sharma Vijaylaxmi 
Published: January 2024

Abstract
Despite the significant growth in the Indian economy and the expansion of the primary sector, farmers continue to live in extreme poverty and their hopelessness has been on the rise. Improving farmers’ conditions is crucial because there is no way to avoid the agrarian crisis or their dilemma. Over the years, the government has implemented several reforms despite farmers generally opposing these attempts. It goes without saying that the government must continue to develop the industry if it is to ensure the farmers in India continue to profit. The agricultural market system which is predominantly guided by the agricultural produce marketing legislations, has major flaws, which raises significant challenges in achieving a strong position for a farmer. The policies around price assurance have led to acute interventions, which have been attributed to fragmentation. On the one hand, government intervention is necessary, but on the other hand, too much of it will lead to negative effects. It calls for regulatory reform of the whole system using a balanced approach. This study has analysed the present-day structural problems in the marketing sector with relevance to the historical background of the reforms and suggested a few policy changes for a better future for the farmers.
Improved power quality based PVDG system using different optimised MPPT controllers
Authors: Tiwari Anurag 
Published: January 2024

Abstract
The characteristic curve of photovoltaic (PV) modules is nonlinear due to environmental influences. The maximum quantity of energy can only be taken from the nonlinear angle of the solar system at one exact moment. The primary function of an MPPT (maximum power point tracking) controller in a PV system is to extract maximum power point (MPP) from solar panels. In this paper, an enhanced MPPT approach using different optimization techniques is suggested for PV systems. The Fuzzy logic controller (FLC), Whale Optimization Algorithm(WOA), and Modified Grey Wolf Optimization algorithm (MGWO) are presented for the MPPT controller. Among all methods, the MGWO technique is one of the best at determining the MPP in solar systems because of its quick response and low fluctuations. Accurate training data is one of the biggest challenges in developing an effective MGWO. The irradiance and temperature are taken into consideration as input variables, and the optimal voltages are optimized as an output variable using the MGWO algorithm. Matlab/Simulink simulations are run to verify the suggested model’s suggested tracking effectiveness. To ensure accurate results, simulations are run under various climatic conditions. The simulation result shows that the proposed method operates correctly in a variety of climatic conditions efficiently.
A review of novel methods to improve the optical and electrical properties of n-type and p-type sulphides and oxides: leading the frontiers of semiconductor technology
Authors: Madkhali O 
Published: January 2024

Abstract
This review paper focuses on the current advancements in improving the optical and electrical properties of n-type and p-type oxides and sulphide semiconductors. The demand for high-performance semiconductors has grown significantly in recent years due to their wide range of application in electronic and optoelectronic devices. However, the inherent limitations of these materials such as low conductivity, poor optical absorption, and low carrier mobility have hindered their widespread adoption. This paper provides an overview of various techniques that have been employed to improve the optical and electrical properties of n-type and p-type oxides and sulphide semiconductors. These techniques include doping with impurities, defect engineering, surface passivation, and bandgap engineering. The paper also discusses the recent progress in the synthesis of these materials using different methods such as chemical vapor deposition, sol–gel, and hydrothermal methods. Furthermore, this review paper highlights the applications of these improved materials in various fields such as solar cells, light-emitting diodes, photocatalysis, and sensing. Finally, the paper concludes with the prospects of these materials and the challenges that need to be addressed to achieve their full potential. Overall, this review paper provides valuable insights into the current state-of-the-art techniques for improving the optical and electrical properties of n-type and p-type oxides and sulphide semiconductors, which can potentially lead to the development of high-performance devices.
Giant Kerr effect of a p
x
+ ip
y
superconductor engineered by semiconductor nanowires
Authors: Yazdani-Hamid Meghdad 
Published: January 2024

Abstract
Twisted array of proximitized quantum wires is recently proposed as a promising platform to host Majorana zero modes and superconducting phases with broken time reversal symmetry. Thus, this device is expected to have a nonzero polar Kerr effect. We study this signal and the corresponding Hall conductivity for the variety of topological phases in the presence and absence of bulk free carriers. The calculated Kerr angles can easily be measured because of the high characteristic energy scales using existent experimental techniques. Then, the unique optical results of each topological phase may be used as fingerprints of these interesting phases.
Higgs inflation model with non-minimal coupling in hybrid Palatini approach
Authors: Asfour Brahim , Bargach Aatifa , Errahmani Ahmed , Ouali Taoufik 
Published: January 2024

Abstract
In this paper, we propose a hybrid metric Palatini approach in which the Palatini scalar curvature is non minimally coupled to the scalar field. We derive Einstein's field equations, i.e., the equations of motion of the scalar field. Furthermore, the background and perturbative parameters are obtained by means of Friedmann equations in the slow roll regime. The analysis of cosmological perturbations allowed us to obtain the main inflationary parameters, e.g., the scalar spectral index

and tensor to scalar ratio r. From this perspective, as an application of our analysis, we consider the Higgs field with quartic potential, which plays the inflaton role, and show that predictions of Higgs hybrid inflation are in good agreement with recent observational data [Astron. Astrophys. 641, 61 (2020)].
Early prediction of dementia using fMRI data with a graph convolutional network approach
Authors: Han Shuning , Sun Zhe , Zhao Kanhao , Duan Feng , Caiafa Cesar F , Zhang Yu , Solé-Casals Jordi 
Published: January 2024

Abstract

Objective. Alzheimer’s disease is a progressive neurodegenerative dementia that poses a significant global health threat. It is imperative and essential to detect patients in the mild cognitive impairment (MCI) stage or even earlier, enabling effective interventions to prevent further deterioration of dementia. This study focuses on the early prediction of dementia utilizing Magnetic Resonance Imaging (MRI) data, using the proposed Graph Convolutional Networks (GCNs). Approach. Specifically, we developed a functional connectivity (FC) based GCN framework for binary classifications using resting-state fMRI data. We explored different types and processing methods of FC and evaluated the performance on the OASIS-3 dataset. We developed the GCN model for two different purposes: (1) MCI diagnosis: classifying MCI from normal controls (NCs); and (2) dementia risk prediction: classifying NCs from subjects who have the potential for developing MCI but have not been clinically diagnosed as MCI. Main results. The results of the experiments revealed several important findings: First, the proposed GCN outperformed both the baseline GCN and Support Vector Machine (SVM). It achieved the best average accuracy of 80.3% (11.7% higher than the baseline GCN and 23.5% higher than SVM) and the highest accuracy of 91.2%. Secondly, the GCN framework with (absolute) individual FC performed slightly better than that with global FC generally. However, GCN using global graphs with appropriate connectivity can achieve equivalent or superior performance to individual graphs in some cases, which highlights the significance of suitable connectivity for achieving performance. Additionally, the results indicate that the self-network connectivity of specific brain network regions (such as default mode network, visual network, ventral attention network and somatomotor network) may play a more significant role in GCN classification. Significance. Overall, this study offers valuable insights into the application of GCNs in brain analysis and early diagnosis of dementia. This contributes significantly to the understanding of MCI and has substantial potential for clinical applications in early diagnosis and intervention for dementia and other neurodegenerative diseases. Our code for GCN implementation is available at: https://github.com/Shuning-Han/FC-based-GCN.
Monte Carlo study for the thermodynamic and dynamic phase transitions in the spin-S Ising model on Sierpiński carpet
Authors: Jang Hoseung , Azhari Mouhcine , Yu Unjong 
Published: January 2024

Abstract
We study the thermodynamic and dynamic phase transitions (TPT and DPT) of the spin-

1

/

2

and spin-1 Ising models on three graphs constructed on the Sierpiński carpet. This study employs Monte Carlo methods, specifically the Wolff and Metropolis algorithms, in conjunction with finite-size scaling analysis. By calculating the critical temperature and critical exponent ratio

γ

/

ν

associated with the TPT, we demonstrate that the three graphs exhibit an identical critical exponent ratio for both the spin-

1

/

2

and spin-1 Ising models within statistical error. Furthermore, we explore the kinetic Ising model by varying the period of the oscillating external magnetic field and verify the existence of the DPT. We find that the critical exponent ratio

γ

/

ν

for the DPT matches that of the TPT. Our results suggest that the critical exponents or their ratios for continuous phase transitions in equilibrium and non-equilibrium systems with short-range interactions are independent of the graph structure and interaction type, as long as the background space is the same.