bluuebunny/crossref_metadata_2025_split huggingface dataset:
Xm–EOP/PDEM connection for Scarf I potentials and their coherent states revivals
Authors: Yahiaoui Sid-Ahmed , Cherroud Othmane 
Published: December 2024

Abstract
The revival structures for X

m
-exceptional orthogonal polynomials (EOP) of Scarf I potentials endowed with position-dependent effective mass (PDEM) are studied in the context of the generalized Gazeau-Klauder coherent states. It is shown that the deduced coherent states mimic full and fractional revivals phenomena in the case of the constant-mass. However, in the case of position-dependent effective mass, although full revivals take place during their time evolution, there is no trace of fractional revivals as defined in the common sense. These properties are illustrated numerically by means of some specific profiles of the mass-function, with and without singularities. We have also observed a close connection between the coherence time

τ

coh

[
m
]

and the mass-parameter λ. We suspect the effect that a larger mass-parameter λ contributes significantly to a longer coherence time

τ

coh

[
m
]

.
Low-loss weakly coupled four-mode hollow-core antiresonant fiber based on centrosymmetric nested structure
Authors: Wang Shuaihang , Tian Feng , Li Li , Li Zhipei , Zhang Qi , Tian Qinghua , Wang Yongjun , Wang Fu 
Published: December 2024

Abstract
This paper designs a novel centrosymmetric double-layer nested antiresonant fiber (CDNAF) with few-mode transmission characteristics. The cladding structure of the CDNAF incorporates glass plates and multilayer capillaries, effectively mitigating the coupling between various core modes and cladding modes. Simulation results show that the CDNAF can support four modes of low-loss transmission from LP01 to LP02 at 1550 nm. The confinement loss (CL) of the four modes is less than 0.008 dB km−1, 0.07 dB km−1, 0.42 dB km−1, and 4.8 dB km-1, respectively, and the CDNAF has a sizeable differential group delay (DGD) and weak bending sensitivity. The loss of high-order modes is much greater than that of the other four transmission modes, ensuring high-purity transmission of the four modes. In the wavelength range of 1200–1700 nm, the CDNAF ensures few-mode characteristics with at least two low-loss transmission modes. Furthermore, the effective refractive index difference (Δn

eff
) between adjacent modes is much greater than 10–4, eliminating or significantly reducing the need for multiple-input multiple-output digital signal processing (MIMO-DSP) techniques in optical communication systems. Additionally, the results demonstrate that CDNAF can transmit three modes at an ultimate bending radius of 5 cm and can transmit four modes like a straight fiber at a bending radius of 18 cm, which demonstrates that CDNAF has excellent bending performance. These excellent characteristics give the CDNAF great potential for application in large-capacity optical communication systems.
Dispersion and dissipation of shear horizontal wave in magneto-electro-elastic material loaded with complex magnetic viscous fluid
Authors: SINGH RAVINDRA , . Ramnarayan , Yadav Priyanka , prasad surendra 
Published: December 2024

Abstract
The present study outlines the theoretical analysis of Shear horizontal (SH) wave propagation on magneto-electro-elastic (MEE) material lying on an elastic half-space and subjected to magnetic fluid loading. Using an exact analytical approach, complex dispersion relations for SH waves are derived under both electric short and electric open boundary conditions. To validate these derived relations, specific cases are considered where the MEE material behaves as piezoelectric and piezomagnetic. The complex dispersion relations are separated into real and imaginary components, revealing nonlinear relationships between phase velocity and attenuation of SH waves in relation to geometric parameters, frequency, and the physical properties of the magnetic fluid. Five different magnetic fluids are examined to illustrate the phase velocity and attenuation characteristics graphically. The effects of geometric and physical parameters of the magnetic fluids, the thickness of the MEE material, and the frequency and density of the elastic half-space on the phase velocity and attenuation of SH waves are discussed. Additionally, the finite element method (FEM) is employed to validate the results, ensuring the accuracy of the analytical findings. The results of this study are fundamental and can be used to design and development of surface acoustic wave (SAW) liquid sensors as well as magnetic field sensors.
Composite material from polylactic acid and modified fire flax: synthesis and properties
Authors: Cherkashina N I , Pavlenko Z V , Ryzhikh D A , Serebryakov S V , Silchenko D V 
Published: December 2024

Abstract
The paper presents data on the synthesis of a composite material based on polylactic acid and fire flax powder. To improve adhesion between the polymer matrix and the plant filler, the fire flax powder was modified (acylated) with acetic anhydride. The IR Fourier spectroscopy method established the acylation reaction of fire flax powder. After modification with acetic anhydride, an increase in the intensity of the following peaks is observed in the IR Fourier spectrum: at 1747 cm−1, at 1374 cm−1 and at 1234 cm−1. Composites based on polylactic acid were manufactured, which contained the modified filler in concentrations of 30%, 40% and 50% by weight. Physicomechanical, electron microscopic and thermal studies of the developed polymer composites are presented. The tensile strength of the studied composites was determined using standard methods according to ISO 527–2:2012. The composite containing 50 wt% modified fire flax powder has the following characteristics: tensile strength—6.53 MPa, relative elongation −13.89%, density −1.247 g cm−3, maximum permissible operating temperature (sample weight loss up to 5 wt%) −254 °C. This study promotes the development of biodegradable materials by offering polylactide-based composites with the addition of fire flax as an alternative to non-degradable synthetic fillers. The use of agricultural waste not only reduces the cost of production, but also solves the problem of biomass utilization, which opens up prospects for the creation of environmentally friendly composites in various industries. The research methodology also makes it possible to modify natural components, expanding their use and potentially replacing traditional plastics.
Generative modeling and augmentation of EEG signals using improved diffusion probabilistic models
Authors: Torma Szabolcs , Szegletes Luca 
Published: December 2024

Abstract

Objective. The development of deep learning models for electroencephalography (EEG) signal processing is often constrained by the limited availability of high-quality data. Data augmentation techniques are among the solutions to overcome these challenges, and deep neural generative models, with their data synthesis capabilities, are potential candidates. Approach. The current work investigates enhanced diffusion probabilistic models (DPM) and sampling methods for brain signal generation and data augmentation. We used implicit sampling and progressive distillation to shorten the inference and subsequently analyzed the effects of these methods on the generated data. To assess the feasibility of our method, four classification models were trained and evaluated in an inter-subject setting on datasets augmented with synthetic signals. Main results. Our analysis of generative metrics and statistical evaluations, including subject- and group-level tests, showed that our DPMs could generate visual evoked potentials and motor imagery signals. Distilled, single-step DPMs were trained on two publicly available datasets and were used to synthesize relatively high-quality EEG samples. The performance of the classifiers was improved by the application of the synthesized signals. The present work demonstrates that DPMs are capable of augmenting data with high fidelity and improving the diversity of EEG signals. Although samples can be generated in a single step, there is a significant trade-off between the data quality and sampling steps. Significance. The findings and results of this study demonstrate the promising capability of diffusion models for EEG synthesis, which marks progress toward an efficient and generalizable augmentation method for various EEG decoding tasks.
Multi-dimensional hybrid bilinear CNN-LSTM models for epileptic seizure detection and prediction using EEG signals
Authors: Liu Shan , Wang Jiang , Li Shanshan , Cai Lihui 
Published: December 2024

Abstract

Objective. Automatic detection and prediction of epilepsy are crucial for improving patient care and quality of life. However, existing methods typically focus on single-dimensional information and often confuse the periodic and aperiodic components in electrophysiological signals. Approach. We propose a novel deep learning (DL) framework that integrates temporal, spatial, and frequency information of EEG signals, in which periodic and aperiodic components are separated in the frequency domain. Specifically, we calculated the periodic and aperiodic components in single channel and the synchronization index of each component between channels. A self-attention mechanism is employed to filter single-channel features by selectively focusing on the most distinguishing features. Then, a hybrid bilinear DL network is utilized to capture the spatiotemporal features by combining a convolutional neural network and a long short-term memory network. Finally, a bilinear pooling layer is employed to extract second-order features based on interactions between these spatiotemporal features. Main results. The model achieves exceptional performance, with a detection accuracy of 98.84% on the CHB-MIT dataset, and a prediction accuracy of 98.44% on CHB-MIT and 97.65% on the Kaggle dataset, both with an false positive rate of 0.02. Significance. This work paves the way for developing real-time, wearable epilepsy prediction devices to improve patient care.
The ‘Brussels 4’: essential requirements for implantable brain–computer interface user autonomy
Authors: Oxley Thomas J , Deo Darrel R , Cernera Stephanie , Sawyer Abbey , Putrino David , Ramsey Nick F , Fry Adam 
Published: December 2024

Abstract

Objective. Implantable brain–computer interfaces (iBCIs) hold great promise for individuals with severe paralysis and are advancing toward commercialization. The features required for successful clinical translation and patient adoption of iBCIs may be under recognized within traditional academic iBCI research and deserve further consideration. Approach. Here we consider potentially critical factors to achieve iBCI user autonomy, reflecting the authors’ perspectives on discussions during various sessions and workshops across the 10th International BCI Society Meeting, Brussels, 2023. Main results. Four key considerations were identified: (1) immediate use, (2) easy to use, (3) continuous use, and (4) stable system use. Significance. Addressing these considerations may enable successful clinical translation of iBCIs.
Longitudinal changes in electrophysiology and widefield calcium imaging following electrode implantation
Authors: Robbins Constance , Eles James , Zheng X Sally , Kozai Takashi , Cui X Tracy , Vazquez Alberto 
Published: December 2024

Abstract

Objective. Intracortical microelectrode arrays often fail to deliver reliable signal quality over chronic recordings, and the effect of an implanted recording array on local neural circuits is not completely understood. Approach. In this work we examined the degree of correlation and the spatial dependence of that relationship between widefield calcium imaging and electrophysiology in awake mice from 4 to 44 d post-implantation. Both correlation maps and spike-triggered averaging (STA) are used to characterize the relationship. Main results. We find that calcium imaging and electrophysiological signal are highly correlated in all animals, however, spatial variability in the correlation is affected by inherent correlation in the calcium imaging signal. Some animals exhibit a high degree of apparent neuronal synchrony in the vicinity of the probe at 4 d, while more diversity of response is detected at later time points. Significance. Degree of synchrony appears to be related to the acute injury response to the implanted electrode, with later time points displaying less synchrony. STA may be used to uncover the diverse cortical connections of spiking units.
Forecasting Strategies in Retail: Utilizing Advanced Machine Learning Methods while Safeguarding Privacy
Authors: Naskinova Irina , Kolev Mikhail , Lazarova Meglena 
Published: December 2024

Abstract
Demand forecasting is critical to optimizing retail inventory management, pricing, and operations. This study compares several time series forecasting models on a publicly available retail dataset, including traditional stats like ARIMA and SARIMA, smoothing techniques, and new ones from Facebook, such as Prophet and Neural Prophet. We evaluate each model using metrics like Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and R2. The results show that NeuralProphet and hybrid models outperform traditional models like ARIMA and SARIMA. We also look at the computational efficiency and practicality of the models and provide insights into how they can be used in real-world demand forecasting scenarios. The results show that traditional models are robust. Still, advanced models like NeuralProphet and hybrids, which combine machine learning with time series forecasting, have a lot of potential to improve forecast accuracy and operational decision-making.
Minimization Principle for Analytical Solution of Turbulent Flow in Channel
Authors: Fedoseyev Alex 
Published: December 2024

Abstract
The analytical solution for turbulent flow in a channel, presented in Fedoseyev (2023), described the mean turbulent flow velocity as a superposition of the parabolic and superexponential solutions. In this study, the coefficients of superposition are obtained through the minimization principle, the principle of minimum viscous dissipation. The laminar flow showed a significantly larger dissipation rate. The obtained analytical solutions agreed well with turbulent flow experiments.
A Review of the Influence of Global Anthropogenic Activity on the State of Biosphere
Authors: Petrov Mihai , Traneva Velichka , Tranev Stoyan , Todorov Venelin 
Published: December 2024

Abstract
The current stage of the World is characterized by a very intense anthropogenic activity with the aim of providing energy for whole of humanity. The pollutants emitted as a result of anthropogenic activity accumulate in the atmosphere and some of them have a greenhouse effect. Greenhouse gases lead to an increase in atmospheric temperature and as a result we have negative consequences on flora and fauna with frequent natural cataclysms (floods, drought, torrential rains, strong winds, spontaneous natural wildfires, etc.). The main purpose of the work is the systematization of the very recent current literature with the elaboration of the qualitative and quantitative description of the atmospheric state influenced by pollutants. It is found the following moment from this generalization that the increase in the concentration of pollutants of the atmosphere leads to the increase of the Albedo values of the unique complex Earth-Atmosphere system. The proportionality coefficient between the Albedo and concentration values contains the time interval required for combustion as well as the power of the solar flux and the specific heat of combustion of the fuels. The following fact can be found by the quantitative expression that when the fuels with a high specific heat of combustion are used, then the level of pollutants in the atmosphere is as minimal as possible with minimal negative effects on the flora and fauna.
Spreading and leveling of finite thin films with elastic interfaces: An eigenfunction expansion approach
Authors: Papanicolaou N C , Christov I C 
Published: December 2024

Abstract
The flow of a thin viscous liquid layer under an elastic film arises in natural processes, such as magmatic intrusions between rock strata, and industrial applications, such as coating surfaces with cured polymeric films. We study the linear dynamics of small perturbations to the equilibrium state of the film in a closed trough (finite film). Specifically, we are interested in the spreading (early-time) and leveling (late-time) dynamics as the film adjusts to equilibrium, starting from different initial perturbations. We consider both smooth and non-smooth spatially symmetric and localized initial conditions (perturbations). We find the exact series solutions for the film height, using the sixth-order complete orthonormal eigenfunctions associated with the posed initial-boundary-value problem derived in our previous work [Papanicolaou N C and Christov I C 2023 J. Phys.: Conf. Ser. 2675 012016]. We show that the evolution of the perturbations begins with the spreading of the localized perturbations, followed by their mutual interaction as they spread, and finally, interactions with the confining lateral boundaries of the domain as the perturbations level. In particular, we highlight how the leading eigenvalues of the problem determine the scalings of certain figures of merit with time.
Effective signal denoising with adaptive polynomials
Authors: Idirizov Byulent 
Published: December 2024

Abstract
The study presents an informatic model for signal processing and noise reduction, harnessing the assistance of mathematics. Advanced noise reduction algorithms are applied to improve signal quality. A MATLAB program was developed integrating algorithms designed to reduce noise regardless of its parameter. Employment of adaptive polynomials was also utilized to enhance the reduction of noise interference. All algorithms within the model have been thoroughly automated, ensuring seamless execution. The results demonstrate significant improvements in signal clarity, with filtered signals closely matching the expected noiseless signals. One of the model’s aims was to achieve a significant reduction in noise emitted by rapidly moving objects, an aim that was effectively achieved. The model is applicable in various fields requiring precise signal analysis, demonstrating robust noise reduction capabilities. As an example, it could encompass security-oriented applications such as radar systems and communication networks.
Enhanced Monte Carlo Techniques for Solving Linear Systems
Authors: Apostolov Stoyan , Georgiev Ivan , Nikitov Nikita , Traneva Velichka , Tranev Stoyan , Petrov Mihai , Dimitrov Yuri 
Published: December 2024

Abstract
A novel hybrid Monte Carlo algorithm for solving systems of linear algebraic equations is introduced and evaluated in this study. This algorithm builds on the recent “Walk on Equations” Monte Carlo method developed by Ivan Dimov, Sylvain Maire, and Jean Michel Sellier. For the first time, this approach has been compared with the Gauss-Seidel method for matrices of big size. Significant improvements have been made to the algorithm by selecting optimal values for the relaxation parameters, resulting in a considerable reduction in computational time and lower relative errors across a specified number of iterations. The convergence of the algorithm has been rigorously established through a new theorem. It has been demonstrated that the original algorithm can be optimized by properly balancing the iteration matrix. Additionally, a sequential Monte Carlo method developed by John Halton, which utilizes the control variate method iteratively, has also been implemented.
Development of rainfall hyetographs for the North Coastal Area of Central Java
Authors: Suripin  , Ulfiana Desyta 
Published: December 2024

Abstract
Temporal distribution of hyetograph is a significant data used by engineers for designing hydraulic structures and urban drainage systems. It is used to estimate peak flood discharge and flood volume. The design storm hyetograph need to be determined accurately before taking any hydrologic analyses. The North Coast of Central Java-Indonesia has been severely affected by flooding during the last two decades. So far, engineers have predicted flood discharge using hyetographs from elsewhere, even though the storm’s characteristics are local. The developed hyetograph in a certain region may not necessarily be adopted in different places. Therefore, it is necessary to develop local hyetographs. This article is aimed to develop hyetographs for the North Coast of Central Java-Indonesia. Analytical statistic approach to historical data is applied to develop the storm hyetographs. The results reveal that there was a difference between the Alternating Block Method (ABM) hyetograph, which tended to be symmetrical, and the hyetograph developed tended to skew to the left (positive skewness), with lower peak storm. It is recommended to evaluate the use of the ABM method in other locations in Indonesia by developing hyetographs based on historical rainfall data.
Identification of spatial potential flood-prone area using topographic wetness index under the digital elevation model of Kr. Keureuto watershed, North Aceh.
Authors: Rizalihadi Maimun , Meilianda Ella , Yulianur Alfiansyah , Away Yuwaldi 
Published: December 2024

Abstract
Floods are the most frequent disaster events in Lhoksukon, resulting in significant losses and community and environmental damage. Floods are generated by several factors, consisting of hydrometeorological, topographical, geological, soil, and human activities. Topography is a key controlling factor in flood initiation. Topographic analysis for detecting flood susceptibility, especially flood inundation, can be conducted using the TWI. The research aims to identify the potential spatial distribution of flood-prone areas based on TWI and assess the model accuracy using the ROC-AUC method. A case study was conducted in the Kr. Keureuto watershed. of North Aceh. TWI analysis is based on the topography of an area denoted by extracting DEM using GIS to create slope, flow direction, and flow accumulation. Higher TWI values are associated with higher flood susceptibility. The results show that the value of TWI is approximately 1.571-27.147, showing that more than 20% of area are potentially flood inundations with high and very hight rating of flood susceptibility. Furthermore, based on the analysis using field observation flood is obtained the AUC value of 71,60%. It can be concluded that the spatial model of flood-prone using TWI is good and effective for determining flood prone region in the Kr. Keureuto River basin