bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mathematical analysis of a three-strain model for dengue with vaccination
Authors: Khan Mohsin , Farhan Muhammad , Zheng Zhoumin , Shah Zahir , Alshehri Mansoor H , Antonescu Elisabeta 
Published: November 2024

Abstract
Dengue has emerged as the most widespread mosquito-borne ailment in humans, causing an estimated 390 million infections within the endemic regions of the world annually. In this paper, a novel mathematical model is proposed for three strains of dengue virus with vaccination measures. Some of the important qualitative analysis carried out are as follows: The dengue serotypes 1, 2 and 3 sub-models are qualitatively analyzed, using well constructed candidates of Lyapunov function. The sub-models’ infection-free equilibria are proven to be locally asymptotically stable. The infection-free and endemic equilibria of the sub-models are established to be globally asymptotically stable. The complete model’s infection-free equilibrium is proven to be locally and globally asymptotically stable. Also, simulations are also presented to validate the theoretical analysis in the paper. The solution profiles of all epidemiological compartments when the reproduction numbers are both below one and greater than one are graphically presented. It was observed that, for the scenarios when the dengue reproduction number

R

0

is below and above one, the solution trajectories converge to the infection-free and dengue-endemic steady states, respectively. Sensitivity analyses using the Latin Hypercube Sampling (LHS), and also using contour plots and surface plots are performed on the dengue serotypes associated reproduction numbers. The impact of influential parameters are graphically presented. Worthy of mention, is the significant impact of dengue transmission rates (positively correlated) and dengue vaccination rates and vaccine effectiveness levels (negatively correlated). Different scenario analyses to investigate the impact of dengue vaccination measures are presented. It was observed that enhanced dengue vaccination programme under the administration of safe and highly effective vaccine could curtail the spread and co-circulation of different dengue serotypes within the population.
Effect of anisotropy field on the resonance frequency and reflection loss shift characteristics of barium hexaferrite ceramics
Authors: Adi Wisnu Ari , Winatapura Didin Sahidin , Mulyawan Ade , Deswita Deswita , Dewi Sari Hasnah , Yunasfi Yunasfi , Mashadi Mashadi , Taryana Yana 
Published: November 2024

Abstract
For this study, a modified barium hexaferrite based microwave and radar absorbing material was used. Synthesis and characterization of BaFe(12−2x)(MnTi)
x
O19 (0.1 ≤ x ≤ 1.0) have been prepared by solid state reaction method. The x-ray diffraction patterns reveal that all samples only crystallized into M-type barium hexaferrite after calcination at 1200 °C. Surface morphology images show that the hexagonal flake-like particle is formed at the initial stages of the Mn-Ti substitution level. The magnetic properties measurement reveals that the variation of magnetization values may vary based on preferable site occupation of Mn4+-Ti2+ cations to replace Fe3+ cations. The significant decrease in coercive field (H
c) from 3.18 kOe to 0.51 kOe with the increase of Mn-Ti substitution affected the lowering values of anisotropy field (H

a
). The maximum reflection loss (RL) positions of BaFe(12−2x)(MnTi)
x
O19 compositional series are shifted to lower frequency range following the H

a
trendlines. The maximum RL value equals to 98.42% microwave absorption at 10.5 GHz has been obtained in x = 1.0 (BaFe10Mn0.5Ti0.5O19) composition.
A first-principles investigation of the structural, optoelectronic, elastic and thermal properties of the p-type half-metallic ferromagnetic perovskites BaFeX3(X = Cl, Br, I)
Authors: Noor Farhan , Kabir Alamgir , Mahmud MD Tareq 
Published: November 2024

Abstract
The half-metallic nature of the metal halide perovskites BaFeX
3 (X = Cl, Br,I) and their physical properties were studied using Spin-polarised Density Functional Theory calculations. For each structure, ferromagnetic, antiferromagnetic and non-magnetic calculation were performed and the ferromagnetic phase was found to have the lowest energy. The calculated band structures in addition to the electronic density of states confirmed half-metallicity, where the perovskites showed semiconducting nature in the spin up channel and metallic in spin-down channel. The optical properties are calculated and strong absorption in the UV range was seen and the mechanical properties demonstrated mechanical stability with ductile behaviour for all perovskites. The specific heats (at constant volume) of all of the studied perovskites levelled off to about 245 JK−1 mol−1 at high temperatures. The Seebeck coefficient was also calculated as a function of temperature and found to be positive for all the structures which confirm them to be p-type materials. These perovskites are therefore suited for thin film fabrication and bulk single crystals for applications such as UV photodetectors and energy harvesting, in addition to spintronics applications.
Investigating the fractional Caudrey-Dodd-Gibbon-Sawada-Kotera equation: an iterative framework for nonlinear wave dynamics
Authors: Ayata Muammer 
Published: November 2024

Abstract
This paper addresses the solution of the fractional Caudrey-Dodd-Gibbon-Sawada-Kotera (CDGSK) equation using the Conformable Laplace Decomposition Method (CLDM). The CDGSK equation, a fundamental model in wave dynamics and fluid mechanics, is explored for its applications in quantum mechanics and nonlinear optics. By employing fractional calculus, we demonstrate how fractional derivatives influence the physical characteristics of wave propagation in both optical and quantum systems. The exact solutions obtained provide insight into soliton behavior, essential for understanding wave-particle interactions in quantum fields and light–matter interactions in optics. The fractional nature of the equation allows for more accurate modeling of non-integer order dynamics commonly found in optical fibers and quantum waveguides. The CLDM method proves to be highly effective, providing approximate solutions with minimal computational effort. These findings offer significant contributions to the fields of quantum mechanics and nonlinear optics, where the fractional CDGSK equation can be applied to solve complex wave equations with great accuracy.
Modulational instability for a cubic-quintic model of coupled Gross–Pitaevskii equations with residual nonlinearities
Authors: Mboumba Maïk Delon , Kamsap Marius Romuald , Moubissi Alain Brice , Ekogo Thierry Blanchard , Kofané Timoléon Crépin 
Published: November 2024

Abstract
We demonstrate the existence of modulational instability (MI) in both trapped miscible and immiscible two component Bose–Einstein condensates. The study is addressed theoretically and numerically in the framework of one-dimensional coupled Gross–Pitaevskii equations incorporating intra- and interspecies cubic-quintic nonlinearities with higher-order ones. Using the time-dependent variational approach, we derive the new Euler-Langrange equations for the time evolution of the phase and amplitude of the modulational perturbation as well as the effective potential and the instability criteria of the system. We examine the effects of higher order nonlinearities on the instability dynamics of the condensates. We show that the modulational properties of the chosen wave numbers are significantly modified. Direct numerical simulations run by the split step Fourier method confirm the analytical predictions.
Operational matrix method approach for fractional partial differential-equations
Authors: Turan-Dincel Arzu , Tural-Polat Sadiye Nergis 
Published: November 2024

Abstract
Fractional partial differential equations (FPDEs) have become very popular to model and analyze numerous different physical phenomena in recent years. However, it is generally complicated to find the exact solutions of those FPDEs. The objective of this study is to find the approximate numerical solution of FPDEs by introducing a wavelet-based operational matrix technique. In this study we employ Hermite wavelets (HWs) and the operational matrices of the fractional integration for Hermite wavelets. The sparsity of the obtained operational matrices provides fast and efficient computation of the proposed method. The original FPDE equations are converted to Sylvester equations, which then are solved to obtain the final solution. We provide a few numerical examples to demonstrate the versatility and efficiency of the proposed method.
Nonlocal correlations and entanglement in two coupled double quantum dots under external magnetic field
Authors: Ait Mansour H , Chouiba A , Mansour M , El Baz M 
Published: November 2024

Abstract
Double quantum dot (DQD) systems are highly regarded as promising candidates for advancements in the fields of quantum computing and quantum information processing. In this work, we investigate the behaviour of quantum correlations (QCs) in a system of two DQDs, AlGaAs/GaAs under various parameters such as temperature, energy offsets, coupling strength, and magnetic fields. We employ uncertainty-induced nonlocality and Bell nonlocality to quantify QC and logarithmic negativity to measure entanglement in the considered physical system. The findings demonstrate that QCs are significantly influenced by noisy equilibrium temperature and system parameters. In particular, lower temperatures enhance QCs, whereas higher temperatures result in a decrease due to thermal effects. In addition, the magnetic fields have a profound influence on the conditions of resonance. We also show that maximum QCs occur at resonance conditions with no energy offset between each DQD. However, introducing an energy offset or too-strong coupling reduces these correlations. Finally, our findings provide an understanding of the behaviour of entanglement and quantum nonlocality in DQD systems, offering potential implications for quantum technologies.
Plasma self-driven current in tokamaks with magnetic islands
Authors: Wang W.X. , Yoo M.G. , Startsev E.A. , Kaye S. , Ethier S. , Chen J. 
Published: November 2024

Abstract
Magnetic island perturbations may cause a reduction in plasma self-driven current that is needed for tokamak operation. A novel effect on tokamak self-driven current revealed by global gyrokinetic simulations is due to magnetic-island-induced 3D electric potential structures, which have the same dominant mode numbers as that of the magnetic island, whereas centered at both the inner and outer edge of the island. The non-resonant potential islands are shown to drive a current through an efficient nonlinear parallel acceleration of electrons. In large aspect ratio (large-A) tokamak devices, this new effect can result in a significant global reduction of the electron bootstrap current when the island size is sufficiently large, in addition to the local current loss across the island region due to the pressure profile flattening. It is shown that there exists a critical magnetic island width for large-A tokamaks beyond which the electron bootstrap current loss is global and increases rapidly with the island size. As such, this process may introduce a size limit for tolerable magnetic islands in large-A tokamak devices in the context of steady state operation. On the other hand, the current loss caused by magnetic islands in low-A tokamaks such as spherical tokamak (ST) NSTX/U is minor. The reduction of the axisymmetric current by magnetic islands scales with the square of island width. However, the loss of the current is mainly local to the island region, and the pace of current loss as the island size increases is substantially slower compared to large-A tokamaks. In particular, the bootstrap current reduction in STs is even smaller in the reactor-relevant high-β

p
regime where neoclassical tearing modes are more likely to develop.
Immunological reactivity in cows under technogenic load conditions
Authors: Poryvaeva A P , Pechura E V , Krasnopeorov A S , Belousova D A , Klepova Yu V , Kozhukhovskaya V V 
Published: November 2024

Abstract
Technogenic load has a negative impact on agricultural efficiency and threatens global food security. Exogenous toxicants have a complex effect on the organism of animals, provoking the development of compensatory mechanisms and changes in the clinical status, morphological and immune blood parameters. The authors analysed the state of the immunohaematological profile. For qualitative and quantitative adaptation reactions characterisation of the organism, leukocyte blood indexes were calculated. The results of the study have allowed to determine the main markers of impaired immunological reactivity in animals kept in territories with unfavourable environmental conditions.
Reinforcing polyvinyl alcohol films with layered double hydroxide and tannic acid to enhance tensile strength, tribological performance, and corrosion resistance in biomedical coating applications
Authors: Rahmadiawan Dieter , Shi Shih-Chen , Zhuang Wei-Ting 
Published: November 2024

Abstract
This study investigates the synergistic effects of incorporating layered double hydroxide (LDH) and tannic acid (TA) into polyvinyl alcohol (PVA) films to enhance their mechanical, tribological, and corrosion resistance properties for biomedical applications. Composite coating films were prepared by blending PVA with LDH and TA in various concentrations. The addition of LDH and TA significantly increased the crystallinity index of the composite films, with the highest crystallinity observed at 66.3% for the sample containing 1 wt% TA and 2 wt% LDH (PVA/TA1/LDH2). This enhancement in crystallinity contributed to improved mechanical performance, as demonstrated by tensile tests, where the PVA/TA1/LDH2 composite exhibited the highest tensile strength among all samples. Tribological testing revealed that the PVA/TA1/LDH2 composite also achieved the lowest coefficient of friction (COF), along with a minimal wear rate, indicating superior wear resistance. SEM analysis of the wear scars confirmed a narrow wear track and smoother surface morphology for this composite, which suggests effective load distribution and reduced surface degradation. The addition of TA was further shown to improve the corrosion resistance of the PVA composite films, with the PVA/TA1/LDH1 sample exhibiting the lowest corrosion current density (Icorr) of 0.36 μA cm−2, representing a significant improvement over neat PVA. These findings highlight the potential of PVA/LDH/TA films for coating applications in biomedical devices, where enhanced mechanical strength, wear resistance, and corrosion protection are critical. The synergistic effects of LDH and TA provide a pathway for developing durable and functional coatings, expanding the practical utility of PVA films in demanding biomedical environments.
‘Going the distance’? The effects of a new method of proximizing climate change on perceived distance, risk perception, emotional response, and engagement in climate change mitigation
Authors: Langlais C , Mauduy M , Demarque C , Cantat O , Sénémeaud C 
Published: November 2024

Abstract

‘Proximizing climate change’ is a widely used strategy for promoting public engagement in environmental communication. However, experimental manipulations of psychological distance often fail to substantially reduce the perceived distance of climate change, and, do not systematically affect responses to this issue. In this study, we test the effectiveness of a new proximizing method that combines two strategies on a sample of French students (N = 349). First, we communicated about the immediate (vs. distant) consequences of climate change. Then, participants were asked to relate these consequences to their own direct experiences to accentuate the level of distance induced (versus a no-accentuation condition). We found that presenting proximal events reduces the perceived distance of climate change, but only when proximity is accentuated. This combined method also leads to greater risk perception, stronger emotional response, and increased engagement in mitigation, as it influences the perceived distance. Our results suggest that proximizing climate change is a valuable communication strategy in environmental campaigns when psychological closeness to climate change is made relevant to individuals’ personal experience.
Long-term load forecasting for smart grid
Authors: Kumar Vikash , Mandal Rajib Kumar 
Published: November 2024

Abstract
The load forecasting problem is a complicated non-linear problem connected with the weather, economy, and other complex factors. For electrical power systems, long-term load forecasting provides valuable information for scheduling maintenance, evaluating adequacy, and managing limited energy supplies. A future generating, transmission, and distribution facility’s development and planning process begins with long-term demand forecasting. The development of advanced metering infrastructure (AMI) has greatly expanded the amount of real-time data collection on large-scale electricity consumption. The load forecasting techniques have changed significantly as a result of the real-time utilization of this vast amount of smart meter data. This study suggests numerous approaches for long-term load forecasting using smart-metered data from an actual distribution system on the NIT Patna campus. Data pre-processing is the process of converting unprocessed data into a suitable format by eliminating possible errors caused by lost or interrupted communications, the presence of noise or outliers, duplicate or incorrect data, etc. The load forecasting model is trained using historical load data and significant climatic variables discovered through correlation analysis. With a minimum MAPE and RMSE for every testing scenario, the proposed artificial neural network model yields the greatest forecasting performance for the used system data. The efficacy of the proposed technique has been through a comparison of the acquired results with various alternative load forecasting methods.
Relationship between oriT length and efficiency of RP4-mediated conjugation from Escherichia coli to Gram-positive bacteria
Authors: Fukada Yuta , Inomata Shunsuke , Kataoka Masakazu 
Published: November 2024

Abstract
In RP4 conjugation, approximately 350 bp of the origin of transfer (oriT) is required for transfer. Within this oriT, there are binding regions for the transfer-related proteins TraI, TraK, and TraJ. We investigated the influence of deleting each protein-binding region within oriT on transfer efficiency in Escherichia coli, Streptomyces lividans, and Bacillus subtilis. The deletion of the TraI-binding region completely abolished transfer in all species. The partial deletion of the TraK-binding region had a minimal impact when targeting but affected efficiency when targeting B. subtilis. The deletion of the TraJ-binding region completely abolished transfer in E. coli and B. subtilis but only reduced efficiency in S. lividans. This is the first report to investigate the influence of each region within oriT on transfer efficiency in S. lividans and B. subtilis, suggesting that the length of oriT required for effective RP4 conjugation varies when targeting Gram-positive bacteria.
A hierarchical random effects state-space model for modeling brain activities from electroencephalogram data
Authors: Guo Xingche , Yang Bin , Loh Ji Meng , Wang Qinxia , Wang Yuanjia 
Published: November 2024

ABSTRACT
Mental disorders present challenges in diagnosis and treatment due to their complex and heterogeneous nature. Electroencephalogram (EEG) has shown promise as a source of potential biomarkers for these disorders. However, existing methods for analyzing EEG signals have limitations in addressing heterogeneity and capturing complex brain activity patterns between regions. This paper proposes a novel random effects state-space model (RESSM) for analyzing large-scale multi-channel resting-state EEG signals, accounting for the heterogeneity of brain connectivities between groups and individual subjects. We incorporate multi-level random effects for temporal dynamical and spatial mapping matrices and address non-stationarity so that the brain connectivity patterns can vary over time. The model is fitted under a Bayesian hierarchical model framework coupled with a Gibbs sampler. Compared to previous mixed-effects state-space models, we directly model high-dimensional random effects matrices of interest without structural constraints and tackle the challenge of identifiability. Through extensive simulation studies, we demonstrate that our approach yields valid estimation and inference. We apply RESSM to a multi-site clinical trial of major depressive disorder (MDD). Our analysis uncovers significant differences in resting-state brain temporal dynamics among MDD patients compared to healthy individuals. In addition, we show the subject-level EEG features derived from RESSM exhibit a superior predictive value for the heterogeneous treatment effect compared to the EEG frequency band power, suggesting the potential of EEG as a valuable biomarker for MDD.
Application value of strain elastography and shear wave elastography in patients with type 2 diabetic peripheral neuropathy: a prospective observational study
Authors: Zheng Siqi , Zhu Miao , Fan Gaoxiang , Yang Xueting , Bai Min 
Published: November 2024

Abstract

Objective
To evaluate the value of conventional ultrasound (US), strain elastography (SE), and shear wave elastography (SWE) in detecting diabetic peripheral neuropathy (DPN) of the tibial nerve (TN), and to establish a predictive model for the diagnosis of DPN.

Methods
A total of 32 healthy participants, 34 diabetic patients without DPN, and 36 diabetic patients with DPN were recruited for this study. The TN at the ankle and popliteal fossa were selected for examination. US was used to measure the cross-sectional area (CSA) and perimeter of the TN. Additionally, SE was used to measure the strain ratio (SR) between the TN and the surrounding adipose tissue, and SWE was used to measure the shear wave velocity (SWV) of the TN.

Results
The CSA, perimeter, SR, and SWV of the TN at the ankle were significantly higher in the DPN group compared to both the Non-DPN group and control group (P &lt; .05). Similarly, the TN at the popliteal fossa showed these differences. At the ankle, the CSA, perimeter, SR, and SWV of the TN in patients without DPN were significantly higher than those in the control group (P &lt; .05). At the popliteal fossa, the SR and SWV of the TN in patients without DPN were significantly higher than those in the control group (P &lt; .05). However, the CSA and perimeter of the TN in patients without DPN did not show a statistically significant difference compared to the control group. The area under the curve (AUC) for the diagnosis of DPN using SWE is significantly greater than that of SE and US.

Conclusion
US, SE, and SWE could be used to diagnose DPN, and they also have good diagnostic value for sub-clinical DPN. Among these methods, SWE has demonstrated superior diagnostic efficacy. Compared to examining the TN in the popliteal fossa, the ankle level offers a better site for examination.

Advances in knowledge
For diabetic peripheral neuropathy, US, SE, and SWE are all promising diagnostic methods with high clinical utility.