bluuebunny/crossref_metadata_2025 huggingface dataset:
Practical Dirac Majorana confusion theorem: issues and applicability
Authors: Kim C. S.
Published: October 2023

We inspect the model-independent study of practical Dirac Majorana confusion theorem (pDMCT) – a wide spread belief that the difference between Dirac and Majorana neutrinos via any kinematical observable would be practically impossible to determine because of the difference only being proportional to the square of neutrino mass – in context of processes that have at least a neutrino antineutrino pair in their final state. We scrutinize the domain of applicability of pDMCT and also highlight those aspects that are often misunderstood. We try to clarify some of the frequently used concepts that are used to assert pDMCT as a generic feature irrespective of the process, or observable, such as the existence of any analytic continuity between Dirac and Majorana neutrinos in the limit $$m_{\nu } \rightarrow 0.$$

m
ν

→
0
.

In summary, we illustrate that pDMCT is not any fundamental property of neutrinos, instead, it is a phenomenological feature of neutrino non-observation, depending on models and processes.
Studying the influence of a gyrostatic moment on the motion of a charged rigid body containing a viscous incompressible liquid
Authors: Galal A. A. , Amer T. S. , Elneklawy A. H. , El-Kafly H. F.
Published: October 2023

The rotational motion of a charged rigid body (RB) is examined. The RB has a spherical cavity that contains an incompressible viscous liquid. The influence of a gyrostatic moment (GM), constant torques at the body-connected axes, and the action of the torque of a resistant force, due to the shape of the liquid, are considered. Assuming the liquid has a sufficiently high velocity, the Reynolds number does indeed have a small value. The regulating system of motion is derived in an appropriate formulation through Euler's equations of motion. The averaging method is used to approach a suitable form of the motion's governing system. In addition to using Taylor’s method to reach a solution for the averaged equations of motion of the RB, some initial conditions are considered to approach the required results. The asymptotic approach of the averaged system besides the numerical analysis enables us to obtain the appropriate results of the problem. To draw attention to the beneficial effects of the different values of the body’s parameter on the motion's behavior, these results are graphed through a computer program along with the associated phase plane curves. These diagrams illustrate the influence of several values respected to the GM, charge, body-constant torques, and resistive force torque. The stability of the RB's motion has also been discussed through the represented phase plane diagrams. These results are viewed as a generalization of prior ones, which have been reported for the scenario of an uncharged body or the absence case of the GM. The significance of the obtained results is due to its numerous real-world applications in life, such as for spaceships and wagons carrying liquid fuel.
Neonatal White Matter Damage Analysis Using DTI Super-Resolution and Multi-Modality Image Registration
Authors: Wang Yi , Zhang Yuan , Ma Chi , Wang Rui , Guo Zhe , Shen Yu , Wang Miaomiao , Meng Hongying
Published: October 2023

Punctate White Matter Damage (PWMD) is a common neonatal brain disease, which can easily cause neurological disorder and strongly affect life quality in terms of neuromotor and cognitive performance. Especially, at the neonatal stage, the best cure time can be easily missed because PWMD is not conducive to the diagnosis based on current existing methods. The lesion of PWMD is relatively straightforward on T1-weighted Magnetic Resonance Imaging (T1 MRI), showing semi-oval, cluster or linear high signals. Diffusion Tensor Magnetic Resonance Image (DT-MRI, referred to as DTI) is a noninvasive technique that can be used to study brain microstructures in vivo, and provide information on movement and cognition-related nerve fiber tracts. Therefore, a new method was proposed to use T1 MRI combined with DTI for better neonatal PWMD analysis based on DTI super-resolution and multi-modality image registration. First, after preprocessing, neonatal DTI super-resolution was performed with the three times B-spline interpolation algorithm based on the Log-Euclidean space to improve DTIs’ resolution to fit the T1 MRIs and facilitate nerve fiber tractography. Second, the symmetric diffeomorphic registration algorithm and inverse b0 image were selected for multi-modality image registration of DTI and T1 MRI. Finally, the 3D lesion models were combined with fiber tractography results to analyze and predict the degree of PWMD lesions affecting fiber tracts. Extensive experiments demonstrated the effectiveness and super performance of our proposed method. This streamlined technique can play an essential auxiliary role in diagnosing and treating neonatal PWMD.
Artificial Intelligent Human–Computer Dialogue Support Platform for Hospitals
Authors: Xia Xin , Ma Yunlong , Luo Ye , Lu Jianwei
Published: October 2023

To design a dialogue model and standard artificial programming interface (API), this paper designs an intelligent dialogue support for medical service systems and improving hospital intelligent serviceability, which combines patient pre-diagnosis, diagnosis, and post-diagnosis services with artificial intelligence depth. This is done via an intelligent man–machine dialogue support platform (MMDSP) suitable for medical services based on a multi-dimensional disease model and outpatient knowledge base with artificial intelligence. As a result of the intelligent service capability of the hospital service systems and platforms, patients’ medical experiences have significantly improved. The platform standardizes the multi-channel service process, improves patient service efficiency, and reduces the cost of human resources and business knowledge learning. In addition, the integration of intelligent multi-system service information provides data support for hospitals to serve patients accurately and has good application and promotion value.
Collaborative Inference Acceleration Integrating DNN Partitioning and Task Offloading in Mobile Edge Computing
Authors: Xu Wenxiu , Yin Yin , Chen Ningjiang , Tu Huan
Published: October 2023

In mobile edge computing environment, intelligent inference services driven by DNN are highly sensitive to latency. Recently, collaborative inference between User Devices and Edge Servers (ESs) based on Deep Neural Networks (DNN) partition has achieved success in service acceleration. However, most of the existing collaborative acceleration schemes are partitioned for a single DNN inference task, which cannot quickly make partition decisions for a set of concurrent inference tasks, and often sacrifice inference accuracy. In addition, due to the limited resources of ESs, there is resource competition among concurrent requests, which makes the partitioned tasks cannot be offloaded to ESs in time for processing. Therefore, designing an efficient offloading scheme becomes essential. The task offloading schemes based on deep reinforcement learning can solve complex decision-making problems in high-dimensional state space, but they have problems such as insufficient sample diversity and easily falling into local optimum. In this paper, a Collaborative Inference Acceleration Scheme integrating DNN Partitioning and Task Offloading (CIAS-PnO) is proposed. First, while ensuring inference accuracy, the Collaborative DNN Layer Partitioning (CDLP) algorithm is designed with the goal of optimal latency. CDLP can reduce the problem scale of concurrent inference tasks partition by pruning operation and determine the partition decisions in time. Then, the Distributed Soft Actor-Critic (SAC)-based Partition Task Offloading algorithm (DSACO) is designed. DSACO supports SAC Agents to explore samples in parallel and share learning experiences, and uses the automatic entropy adjustment mechanism to improve the exploration efficiency of Agents, so as to avoid falling into local optimum and achieve efficient offloading of partition tasks. Experimental results on DNN benchmarks show that compared with the baseline acceleration schemes, CIAS-PnO achieves more than 19.8% acceleration performance improvement, and has higher convergence performance and task success rate.
EFSM Model-Based Testing for Android Applications
Authors: Wang Weiwei , Guo Junxia , Li Beite , Shang Ying , Zhao Ruilian
Published: October 2023

Model-based testing provides an effective means for ensuring the quality of Android apps. Nevertheless, existing models that focus on event sequences and abstract them into Finite State Machines (FSMs) may lack precision and determinism because of the different data values of events that can result in various states of Android applications. To address this issue, a novel model based on Extended Finite State Machines (EFSMs) for Android apps is proposed in this paper. The approach leverages machine learning to infer data constraints on events and annotates them on state transitions, leading to a more precise and deterministic model. Additionally, a state abstraction strategy is presented to further refine the model. Besides, test diversity plays a vital role in enhancing test suite effectiveness. To achieve high coverage and fault detection, test cases are generated from the EFSM model with the help of a Genetic Algorithm (GA), guided by test diversity. To evaluate the effectiveness of our approach, this paper carries out experiments on 93 open-source apps. The results show that our approach performs better in code coverage and crash detection than the existing open-source model-based testing tools. Particularly, the 19 unique crashes that involve complex data constraints are detected by our approach.
On the Measures of Success in Replication of Controlled Experiments with STRIDE
Authors: Mbaka Winnie , Tuma Katja
Published: October 2023

To avoid costly security patching after software deployment, security-by-design techniques (e.g. threat analysis) are adopted in organizations to find and mitigate security issues before the system is ever implemented. Organizations are ramping up such (heavily manual) activities, but there is a global gap in the security workforce. Favorable performance indicators would result in cost savings for organizations with scarce security experts. However, past empirical studies were inconclusive regarding some performance indicators of threat analysis techniques, thus practitioners have little evidence for choosing the technique to adopt. To address this issue, we replicated a controlled experiment with STRIDE. Our study aimed to measure and compare the performance indicators (productivity and precision) of two STRIDE variants (per-element and per-interaction). Since we made some similar observations to the original study, we conclude that the two approaches are not different enough to make a practical impact. To this end, the choice of which variant to adopt should be informed by the needs of the organization performing threat analysis. We conclude by discussing some of the unexplored yet relevant topic domains in the context of STRIDE that will be considered in future work.
SYNTHESIS AND CHARACTERIZATION OF Al-DOPED ZnO THIN FILMS AS ANTI-REFLECTION COATINGS FOR SOLAR CELL APPLICATIONS
Authors: ABDULGAFOUR H. I. , ZAINULABDEEN FATEN SH. , KARAM GHADA S. , MAGID HAYIM CH. , NAJIM AUS A. , HASSAN FAEZ M.
Published: October 2023

In this work, we have synthesized ZnO:Al thin films by pulsed laser deposition technique and investigated their microstructural and optical properties. The XRD study confirmed a polycrystalline structure of wurtzite ZnO in all films. Further, Al doping has improved the crystallinity and decreased the crystal size and volume of the unit cell. The surface morphology was homogeneous with nanoscopic crystals clustered to form granular nanoparticles. The optical properties significantly improved by increasing the Al doping concentration. The produced thin films are excellent candidates for use as an anti-reflection layer in solar cells due to their outstanding properties.
GJO-MLP: A NOVEL METHOD FOR HYBRID METAHEURISTICS MULTI-LAYER PERCEPTRON AND A NEW APPROACH FOR PREDICTION OF WEAR LOSS OF AZ91D MAGNESIUM ALLOY WORN AT DRY, OIL, AND h-BN NANOADDITIVE OIL
Authors: ALTAY OSMAN , GURGENC TURAN
Published: October 2023

In this study, the AZ91D magnesium alloy was worn at different wear conditions (dry, oil, and h-BN nanoadditive oil), loads (10–60 N), sliding speeds (50–150 mm/s) and sliding distances (100–1000 m). Wear losses increased with the increase of applied load, sliding speed, and sliding distance. Wear losses were decreased in the h-BN nanoadditive oil conditions. For the first time, the wear losses were predicted using the hybrid golden jackal optimizer-multi-layer perceptron (GJO-MLP) method proposed in this study, using the experimentally obtained data. In addition, the performance of the proposed method was compared with the whale optimization-MLP (WOA-MLP), genetic algorithm-MLP (GA-MLP) and ant lion optimization-MLP (ALO-MLP) methods, which are widely used in the literature. The results showed that GJO-MLP outperformed other methods with a performance of 0.9784 in [Formula: see text] value.
Train Load Identification of the Medium-Small Railway Bridge using Virtual Axle Theory and Bayesian Inference
Authors: Mao Jianxiao , Zhu Xiaojie , Wang Hao , Guo Xiaoming , Pang Zhenhao
Published: October 2023

Accurately identifying the axle loads of the moving train on the railway bridge can provide reliable information for assessing the safety of the train–bridge system. Bridge weigh-in-motion, namely, BWIM, is an effective approach for identifying the positions and weights of the train axles based on the monitored bridge responses. Existing BWIM methods generally focus on identifying the probable value of the axle weights instead of quantifying the identification uncertainty. To address this issue, a novel two-stage train load identification framework for the medium-small railway bridge is developed by combining the virtual axle theory and Bayesian inference. In the first stage, the axle configuration including the axle number, axle spacing and axle weight of the moving train, are estimated according to the modified virtual axle theory in which a clustering algorithm is embedded to automatically determine the axle number. In the second stage, the most probable value (MPV) and the uncertainty of the train axle weight are accurately identified using the Bayesian inference method which takes five types of error patterns into consideration. Finally, the proposed framework is verified using the data from numerical simulations and an in-situ railway bridge. Results show that the proposed framework can improve the accuracy of train load identification after quantifying the uncertainty of estimated axle weights and can confirm the confidence interval of the individual axle weight and gross train weight.
Hybrid Finite Element Method in Nonlinear Dynamic Analysis of Trusses
Authors: Dao Ngoc Tien , Thi Thuy Van Tran
Published: October 2023

This paper presents a dynamic analysis of trusses with an initial length imperfection of the elements, considering geometrical nonlinearity. In the nonlinear analysis of trusses, the hybrid finite-element formulation considers the initial length imperfection of the elements as a dependent boundary constraint in the master equation of stiffness. Moreover, it was incorporated into the establishment of a modified system of equations. To overcome the mathematical complexity of dealing with initial length imperfections, this study proposes a novel approach for solving nonlinear dynamic problems based on a hybrid finite-element formulation. In this study, the unknowns of the dynamic equilibrium equations were displacements and forces, which were obtained using virtual work. The hybrid matrix of elements of the truss is established based on the hybrid variation formulation with length imperfections of elements, considering large displacements. The authors applied Newmark integration and Newton–Raphson iteration methods to solve the dynamic equations with geometrical nonlinearity. An incremental iterative algorithm and calculation programming routine were developed to illustrate the dynamic responses of trusses with initial-length imperfections. The results verified the accuracy and effectiveness of the proposed approach. The uniqueness of the proposed method is that the length imperfection of the truss element is included in the stiffness matrix and is considered a parameter that affects the dynamic response of the system. This helps to solve the problem of the dynamic response of trusses with length imperfections becoming simpler. The numerical results show that the effect of length imperfection on the dynamic response of the trusses is significant, particularly on the dynamic limit load. In addition, to completely evaluate the behavior of the trusses, this study also developed formulas and analyses to consider the inelastic and local buckling of the truss structures, named ‘Inelastic post-buckling analysis (IPB).’
Seismic Performance of Steel-SMA Reinforced Columns: Numerical Investigation
Authors: Liu Xiaoxian , Zhang Xuejian , Wang Jingfeng , Xiang Nailiang , He Min
Published: October 2023

The residual displacement of a bridge column governs its functionality after a severe earthquake. A box girder bridge was selected as a case study. Pushover analysis, quasi-static cyclic analysis, incremental dynamic analysis and fragility analysis were conducted to compare the seismic performance of the reinforced concrete column, the unbonded prestressed reinforced concrete column (UBPRC column) and the unbonded prestressed reinforced concrete column using superelastic shape memory alloy (UBPRC-SMA column). The threshold loading plateau axial load ratio was recommended in designing a UBPRC-SMA column, thereby ensuring the self-centering performance of a bridge column with fewer superelastic SMA bars. The self-centering performance was considered in the fragility analysis, and the results show that the UBPRC-SMA column suffers the least damage for the collapse damage state.
Sustainable Finance Factors in Indian Economy: Analysis on Policy of Climate Change and Energy Sector
Authors: Kumar Rakesh , Goel Richa , Singh Tilottama , Mohanty Sachi Mohanty , Gupta Deepak , Alkhayyat Ahmed , Khanna Rupa
Published: October 2023

In the current era, entire global economies are transitioning to sustainable development because of global warming and climate change. Due to turbulence in environmental issues such as weather shocks, climate change and basic infrastructure and industrial planning, many countries are changing their approach and taking green steps. This paper assesses sustainable finance in India and the ways in which India can mitigate climate changing risk toward zero carbon policy and supporting SDGs 2030. It talks about the physical and transitional climate risks in India like surface temperature, heat wave concourse, etc., and provides a comprehensive analysis of how the corporate sector is imparting its role in sustainable nature through corporate social responsibility (CSR). India is an emerging economy where energy is an essential component. This study analyzes about supply of energy and how India is shifting from traditional energy sources to renewal energy sources.

Thus, the objective of this study is to focus on the initiatives taken by the Indian government for sustainable finance through green bond policy at national and international platforms using the Panchamrit framework adopted by India thereby focusing on India’s sustainable policy support for SDGs 2030. Also, this research proposes numerous recommendations for future sustainable finance research in the context to India, which includes developing and diffusing innovative sustainable financing instruments, magnifying, and managing the profitability and returns of sustainable financing, making sustainable finance more sustainable, and leveraging the power of new-age technologies for sustainable finance.
Relaxation Dynamics and Finite-Size Effects in a Simple Model of Condensation
Authors: Gotti Gabriele , Iubini Stefano , Politi Paolo
Published: October 2023

In this paper, we consider a simple, purely stochastic model characterized by two conserved quantities (mass density a and energy density h) which is known to display a condensation transition when [Formula: see text]: in the localized phase a single site hosts a finite fraction of the whole energy. Its equilibrium properties in the thermodynamic limit are known and in a recent paper [G. Gotti, S. Iubini and P. Politi, Finite-size localization scenarios in condensation transitions, Phys. Rev. E 103 (2021) 052133] we studied the transition for finite systems. Here, we analyze finite-size effects on the energy distribution and on the relaxation dynamics, showing that extremely large systems should be studied in order to observe the asymptotic distribution and even larger systems should be simulated in order to observe the expected relaxation dynamics.
Effect of Nitrogen Ion Diffusion Jumps in Nanometer-Sized Si3N4 Memristors Investigated by Low-Frequency Noise Spectroscopy
Authors: Yakimov Arkady V. , Klyuev Alexey V. , Filatov Dmitry O. , Gorshkov Oleg N. , Antonov Dmitry A. , Mikhaylov Alexey N. , Kochergin Viktor S. , Vasileiadis Nikolaos , Dimitrakis Panagiotis
Published: October 2023

The elementary jumps in the electron current through conducting filaments of two nanometer-sized virtual memristor structures consisting of a contact of a conductive atomic force microscope probe to the Si3N4 layer with the thickness of 6[Formula: see text]nm deposited onto the [Formula: see text]-Si(001) conductive substrates are investigated. These structures are: (S1) the Si3N4/Si film; (S2) the Si3N4/SiO2/Si stack, a similar structure with 2[Formula: see text]nm SiO2 sublayer between the film and the substrate. Usually, such investigations are performed by the analysis of the waveform of this current with the aim of extracting the random telegraph noise (RTN). Here, we develop a new indirect method, which is based on the measurement of the spectrum of the low-frequency flicker noise in the current without extracting the RTN. We propose that the flicker noise is caused by the motion (drift/diffusion) of nitrogen ions via vacancies within and around the filament. The number of these ions is estimated by taking into account the geometrical parameters of the filament. This allows us to estimate the root mean square magnitude [Formula: see text] of the current jumps, which are caused by random jumps of nitrogen ions, and the number M of these ions. This is fundamental for understanding the elementary mechanisms of the electron current flowing through the filament and the resistive switching in memristor devices.
The impact of noise on Burgers equations
Authors: Wei Jinlong , Lv Guangying
Published: October 2023

We study two types of one-dimensional stochastic Burgers equations: Burgers equations with stochastic fluxes and Burgers equations perturbed by transport noise. Using the methods of stochastic characteristics and the characteristics perturbed by noise, respectively, we obtain the probabilities for the occurrence of shocks before and after a given time. Compared with the deterministic equations, in case of small initial data the occurrence time of shocks for Burgers equations with stochastic fluxes will be delayed with large probability, but this conclusion is only true for Burgers equations perturbed by the transport noise with large initial data.
The diameter of commuting graph of matrix ring of division rings
Authors: Dorbidi H. R.
Published: October 2023

The commuting graph of a non-commutative ring [Formula: see text] denoted by [Formula: see text] is a graph whose vertices are non-central elements of [Formula: see text] and two distinct vertices [Formula: see text] and [Formula: see text] are adjacent if [Formula: see text]. Let [Formula: see text] be a division ring, [Formula: see text] and [Formula: see text]. In this paper, we show that if [Formula: see text] or [Formula: see text] and the field [Formula: see text] has no extension of degree [Formula: see text] then [Formula: see text] is a connected graph whose diameter is less than five. Also we prove that the diameter of [Formula: see text] is four where [Formula: see text] is a quaternion algebra over a field [Formula: see text] which has no extension of degree [Formula: see text] and [Formula: see text].
q-Crossed modules and q-capability of Lie algebras
Authors: Khmaladze Emzar , Ladra Manuel
Published: October 2023

Given a non-negative integer [Formula: see text], we study two different notions of the [Formula: see text]-capability of Lie algebras via the non-abelian [Formula: see text]-exterior product of Lie algebras. The first is related to the [Formula: see text]-crossed modules and inner [Formula: see text]-derivations, and the second is the Lie algebra version of the [Formula: see text]-capability of groups proposed by Ellis in 1995.
Smooth torus quotients of Richardson varieties in the Grassmannian
Authors: Bakshi Sarjick
Published: October 2023

Let [Formula: see text] and [Formula: see text] be positive coprime integers with [Formula: see text]. Let [Formula: see text] denote the subgroup of diagonal matrices in [Formula: see text]. We study the GIT quotient of Richardson varieties [Formula: see text] in the Grassmannian Gr[Formula: see text] by [Formula: see text] with respect to a [Formula: see text]-linearized line bundle [Formula: see text] corresponding to the Plücker embedding. We give necessary and sufficient combinatorial conditions for the quotient variety [Formula: see text] to be smooth.
Hybrid model for brain age prediction on MRI images with modified texture features
Authors: Vishnupriya G. S. , Rajakumari S. Brintha
Published: October 2023

Machine learning (ML) and diffusion magnetic resonance imaging (dMRI) approaches can be employed to identify individual brain aging conditions in both healthy people and patients with brain diseases. This research establishes a new brain age prediction system, which comprises different phases like pre-processing, feature extraction, feature selection, and prediction. The original magnetic resonance imaging (MRI) picture is first carried out in a pre-processing stage, which enhances image quality as well as visual appearances. Following that, the shape, intensity, as well as texture-based characteristics are retrieved. Furthermore, texture features like modified entropy, as well as modified correlation are retrieved along with the traditional features. Then, a modified principle component analysis (PCA) method is utilized for feature selection stage. In the prediction phase, hybrid classifiers such as multi-layer perception (MLP) as well as long short term memory (LSTM) are used. The weight of LSTM and MLP is optimally tuned with the aid of an implemented self-updated red deer algorithm (SURDA) model to make an accurate prediction. Moreover, the suggested work outperforms other traditional works in terms of MSE, MAPE, MSLE, and MAE, correspondingly.
Special affine stockwell transform: Theory, uncertainty principles and applications
Authors: Dar Aamir H. , Bhat M. Younus
Published: October 2023

In this paper, we combine the benefits of the well-known special affine Fourier and Stockwell transforms into a novel integral transform dubbed as special affine Stockwell transform and investigate the associated constant Q-property in the joint time–frequency domain. We do this by using the convolution structure of the special affine Fourier transform. The derivation of the basic properties, Rayleigh’s energy theorem, the inversion formula and the range theorem are all included in the preliminary analysis. Besides, we also derive a direct relationship between the recently introduced special affine scaled Wigner distribution and the proposed SAST. Furthermore, we establish Heisenberg’s uncertainty principle, logarithmic uncertainty principle and Nazarov’s uncertainty principle associated with the proposed SAST. Towards the culmination of this paper, some potential applications with simulation are presented.
C-Level Managers’ Perspectives on Firms’ Digital Transformation: A Qualitative Analysis Through the Lens of Business Model Innovation
Authors: Menth Percy , Hnilica Jiri
Published: October 2023

Given a mismatch between traditional paths and the opportunities resulting from new digital technologies, the aim of this paper is to understand why companies’ digital transformation may fail even before it starts. We analyze interviews with 20[Formula: see text]C-level managers from 15 traditional DAX-listed German companies that face digital transformations. Our objective is to integrate the different areas that have been studied in the field of digital transformation. We offer top management teams standpoints, as they concern how business decisions, including digital-transformation decisions, are made. We review the role of top management in digital business model innovation and identify value creation, leadership challenges, and culture development as the main factors that support or hinder business model innovation in a digital world. We further show that taking outside-in perspectives, implementing cross-sectional strategies, and having transformational capabilities represent important drivers on business model innovation. Employees are the most important factor. They should be brought in and guided by top managers to support the digital transformation. The patterns we identify might provide guidance for top managers engaging in digital business model innovation.
Corrections to general relativity with higher-order invariants and cosmological applications
Authors: Bajardi Francesco , D’Agostino Rocco
Published: October 2023

In this paper, we review the main features of modified theories of gravity containing higher-order curvature invariants in the action. After summarizing the main features of these theories, we consider their applications to cosmology, pointing out the differences with respect to general relativity that can eventually solve issues exhibited by the latter at low and high energy scales. Specifically, we explore a gravitational action that incorporates both the Ricci scalar [Formula: see text] and the topological Gauss–Bonnet term, denoted as [Formula: see text]. Our investigation revolves around the cosmological properties of a specific category of modified gravity theories, chosen upon symmetry considerations. Within the framework of a spatially flat, homogeneous and isotropic cosmic background, we demonstrate that it is possible to account for the presently observed acceleration of the Universe by means of the extra geometric terms carried by the selected [Formula: see text] model. This approach offers a way to address the issues associated with the cosmological constant. To achieve this, we first examine the energy conditions and find that, under certain choices for the values of the cosmographic parameters, these conditions are all violated. In the second part of the work, to assess the feasibility of the selected [Formula: see text] model, we place observational constraints on its free parameters through a Bayesian Monte Carlo technique applied to late-time cosmic data. Our findings reveal that the [Formula: see text] model can effectively reproduce observations at low redshifts, providing an alternative to the standard [Formula: see text]CDM scenario.
Scaling symmetries and canonoid transformations in Hamiltonian systems
Authors: Azuaje R. , Bravetti A.
Published: October 2023

In this paper, we investigate various types of symmetries and their mutual relationships in Hamiltonian systems defined on manifolds with different geometric structures: symplectic, cosymplectic, contact and cocontact. In each case, we pay special attention to non-standard (non-canonical) symmetries, in particular scaling symmetries and canonoid transformations, as they provide new interesting tools for the qualitative study of these systems. Our main results are the characterizations of these non-standard symmetries and the analysis of their relation with conserved (or dissipated) quantities.
An Investigation of Free Vibration Characteristics of a DFG-CNTRC Thin Laminated Shell in Thermal Environment
Authors: Li Chaofeng , Miao Xueyang , Pan Yuchen , Yang Kang
Published: October 2023

A dynamic model of dual-functional gradient carbon nanotube-reinforced composite (DFG-CNTRC) laminated shell in a thermal gradient environment is established. The carbon nanotubes (CNTs) are supposed to be FG distribution in the functionally graded material (FGM) consisting of metal and ceramic components, and its traveling wave vibration in thermal gradient environment environments is studied. The temperature between the internal and external sides of laminated shell varies linearly. Considering the impact of the thermal environment on material properties, the orthogonal polynomials are used as admissible function, and the vibration differential equation of the DFG-CNTRC laminated shell is obtained by using the Rayleigh–Ritz method. First-order shear deformation theory (FSDT) and artificial spring technique are applied to establish a general model of free vibration of rotating DFG-CNTRC laminated shells under arbitrary boundary in the thermal gradient environment. The effects of rotational speed, the environmental temperature, the thickness of the middle layer, and volume fraction of CNTs on the traveling waves are discussed.
A model for the transmission dynamics of pneumococcal pneumonia and influenza co-infection
Authors: Ali Mohsin , Khan Adnan , Mirza Shaper , Imran Mudassar
Published: October 2023

Synergistic interaction between influenza and pneumonia is well established in the literature. In this study, we present a model for the transmission dynamics of co-infection with influenza and pneumococcal pneumonia, with the goal of assessing the effects of influenza co-infection on the transmission of pneumonia. We derive an expression for the basic reproductive number [Formula: see text] where [Formula: see text] and [Formula: see text] are, respectively, the reproductive numbers for flu and pneumonia. We show that in the case [Formula: see text], infection with influenza is driven to extinction while pneumonia is endemic, with the endemic state being globally asymptotically stable. The converse result holds in the case where [Formula: see text]. We also show the existence of the co-infection equilibrium. In this case, we show that the presence of co-infection results in a possible backward bifurcation in the system at [Formula: see text]; epidemiologically, this means that the spread of the infection will be harder to control. Numerical simulations are presented to verify the analytic results and gain further insights.
Stability and bifurcation analysis of a nonlinear dynamical model studying the decline of vulture population
Authors: Tandon Abhinav , Dutta Vaishnudebi , Mishra Yuvraj
Published: October 2023

A nonlinear dynamical model is developed in this paper that depicts interactions among vultures, human, animals and their carcasses. Diseases such as plague, anthrax and rabies are spreading due to the cascade impact caused by the catastrophic drop in the vulture population, particularly in Africa and Asia. The built model is theoretically studied using qualitative differential-equation theory to demonstrate the system’s rich dynamical features, which are critical for maintaining the ecosystem’s equilibrium. According to the qualitative findings, depending on the parameter combinations, the system not only displays stability of many equilibrium states but also experiences transcritical and Hopf bifurcations. By keeping an eye on the variables causing the decline of the vulture population, the model’s outputs may assist in maintaining balance with the prevention of the spread of disease through carcasses. Hopf-bifurcation results in the bifurcation of the limit cycle through the threshold, supporting the idea that interactions between humans and vultures may also be periodic.
Spatial and temporal periodic patterns in a delayed diffusive plant–pollinator model with memory-based diffusion
Authors: Tang Xiaosong , Zhou Shan , Luo Jieying
Published: October 2023

In this paper, incorporating memory-based diffusion and delay, we propose a partly diffusive plant–pollinator model under Neumann boundary condition. Then, we investigate the effects of memory-based diffusion and delay on the dynamics of this model through discussing the corresponding characteristic equation. And we find that Turing bifurcations and Hopf bifurcations can be induced by memory-based diffusion and delay, respectively. By performing some numerical simulations, stable spatially homogeneous periodic solutions and inhomogeneous steady state solutions are obtained, which illustrates and expands our results in this paper. Moreover, the unstable spatially inhomogeneous periodic solutions occur only for some time, then they eventually converge to a spatially homogeneous periodic solutions.
Dynamics of a reaction–diffusion three-species food chain model: Effect of space-time white noise
Authors: Qi Haokun , Liu Bing , Li Shi
Published: October 2023

This paper is devoted to analyzing the influence of space-time white noise on the dynamics of biological mathematical models in spatiotemporal scenarios based on stochastic partial differential equations (SPDEs). Here, we propose a stochastic reaction–diffusion three-species food chain model with various functional response functions. The motivation of the SPDEs model construction is mainly twofold: (1) when species migrate in space, space-time white noise is a factor that cannot be ignored; (2) functional response function is an essential indicator for directly measuring the relationship between species in biological mathematical models. To discuss the long-term behaviors of the SPDEs model in spatial heterogeneous environment, we first analyze the well-posedness of mild and strong solutions, respectively. Then, the critical conditions for determining the permanence and extinction of populations are given, which reveal that high-intensity white noise can lead to the extinction of predator populations. The validity of the theoretical results is also performed by numerical simulation. In particular, this new theoretical method may be extended to the study of other stochastic biological mathematical models in spatiotemporal scenarios, such as eco-epidemiological models, high-dimensional population models and epidemic models.
Effect of sodium nitroprusside on the microrheological properties of red blood cells in different media
Authors: Ermolinskiy Petr , Maksimov Matvey , Lugovtsov Andrei , Muravyov Alexey , Tikhomirova Irina , Priezzhev Alexander
Published: October 2023

Red blood cell (RBC) aggregation as well as their deformation significantly affects blood microrheology. These processes depend on various factors, one of which is concentration of the nitric oxide, one of the main signaling molecule in the bloodstream. The purpose of this study was to investigate the effect of nitric oxide on the microrheological properties of red blood cells (RBCs) in RBC samples of various media after the addition of nitric oxide donor sodium nitroprusside in vitro. Microrheological properties were measured using laser aggregometer and ektacytometer based on diffuse light scattering and diffraction of laser light on a suspension of RBCs, respectively. The study found that heparin-stabilized blood showed increased RBC aggregation and deformation with sodium nitroprusside concentrations of 100, and 200[Formula: see text][Formula: see text]M, while EDTA-stabilized blood showed slightly decreased aggregation and unchanged deformation. With washed RBCs in dextran solution, the addition of sodium nitroprusside (in the concentrations of 100, and 200[Formula: see text][Formula: see text]M) resulted in decreased aggregation and increased deformation. These findings aid in our understanding of nitric oxide’s effect on RBC microrheological properties.
Porous pyroelectric material for waste heat harvesting
Authors: Wang Qingping , Luo Haifeng , Xu Zhanxiang , Wu Tian
Published: October 2023

The utilization of pyroelectric materials to harvest waste heat from the ambient environment has gained much interest. However, pyroelectric energy harvesting technology still faces the challenge of low output voltage. In this paper, a porous pyroelectric ceramic with 0.3 wt.% poly(methyl methacrylate) (PMMA) as the additive was prepared via a conventional solid-state reaction technique. Our experimental results indicated that the porous PMN–PMS–PZT:0.3PMMA ceramic had a decrease in both relative permittivity and volume heat capacity at a temperature of 44ˆ∘C, compared to that of the dense sample. Additionally, the porous ceramic demonstrated an enhanced voltage responsivity from 0.50 to 0.52 m2/C and a higher figure of merit from 0.64 to 0.65 nm3/J for energy harvesting, compared to the dense sample. When 0.3 wt.% PMMA was added, the voltage generated by the device increased by 17.01% due to the presence of pores, which suggests a potential application in the field of waste heat harvesting and sensing.
Ethyl cellulose–graphene oxide composite dense membranes: Kinetic and thermodynamic studies of dye adsorption
Authors: Sethu Lakshmi M. B. , Sundaran Suja P. , Sujith A. , Francis Bincy , Ravindran Lakshmipriya , Jacob Sunil , Anilkumar S.
Published: October 2023

Graphene oxide (GO) is extensively used in dye adsorption from wastewater. Polymer–GO composite membranes exhibits improved surface wettability and dye adsorption capacity. In this study, ethyl cellulose (EC)–GO nanocomposite dense membranes (EG membranes) are prepared by the solvent casting method. The morphology and physicochemical properties of the developed nanocomposite membranes are characterized using field emission scanning electron microscopy, Fourier transform infrared spectroscopy, X-ray diffraction studies, thermogravimetric analysis, static contact angle measurements, and UV–visible spectroscopy. The derivative thermogravimetry curves indicate the complete degradation of the composites below [Formula: see text]C. The results confirm the homogeneous dispersion of GO in the EC matrix. The addition of GO to the EC matrix leads to a remarkable increase in surface wettability which decreases the contact angle to [Formula: see text] for the membrane with a 0.7% addition of GO. The prepared membranes are used for the separation of methylene blue from water. The adsorption properties of the prepared membranes are found to be varying in accordance with the contact angle values. The equilibrium data fit well for the Langmuir model and the adsorption follows pseudo-second-order kinetics.
Transversal total hop domination in graphs
Authors: Bonsocan Maria Andrea O. , Jamil Ferdinand P.
Published: October 2023

Let [Formula: see text] be a finite simple graph. A set [Formula: see text] is a total hop dominating set of [Formula: see text] if for every [Formula: see text], there exists [Formula: see text] such that [Formula: see text]. Any total hop dominating set of [Formula: see text] of minimum cardinality is a [Formula: see text]-set of [Formula: see text]. A total hop dominating set [Formula: see text] of [Formula: see text] which intersects every [Formula: see text]-set of [Formula: see text] is a transversal total hop dominating set. The minimum cardinality [Formula: see text] of a transversal total hop dominating set in [Formula: see text] is the transversal total hop domination number of [Formula: see text]. In this paper, we initiate the study of transversal total hop domination in graphs. First, we characterize a graph [Formula: see text] of order [Formula: see text] for which [Formula: see text] is [Formula: see text] or [Formula: see text], and also we determine the specific values of [Formula: see text] for some special graphs [Formula: see text]. Next, we solve some realization problems involving [Formula: see text] with other parameters of [Formula: see text]. Finally, we investigate the transversal total hop domination in the complementary prism, corona, and lexicographic product of graphs.
Event-Triggered Distributed Observer for a Rigid Body Leader System Over Acyclic Switching Networks and its Application
Authors: Wang Tianqi , Huang Jie
Published: October 2023

The distributed observer for a rigid body leader system plays a key role in solving the leader-following consensus problem of multiple rigid body systems. Recently, the authors of this paper established an event-triggered distributed observer over jointly connected networks, which consumes less communication and actuator energy compared with the analog distributed observer. However, a drawback of this event-triggered distributed observer is that the upper bounds of two key design parameters were only shown to exist without giving an explicit estimate of the upper bounds. In this paper, by assuming that the communication network is acyclic, we further show that these two design parameters can take any positive value by choosing other parameters appropriately. Furthermore, we will apply the event-triggered distributed observer to solve the leader-following consensus problem of multiple uncertain rigid body systems.
Two-Dimensional Super-Resolution Direction-of-Arrival Estimation for Arbitrary Planar Array Geometries
Authors: Yang Yang , Yang Yongxin , Chu Zhigang
Published: October 2023

The two-dimensional grid-free compressed sensing method with planar microphone arrays is expected to achieve super-resolution direction-of-arrival (DOA) estimation for acoustic sources in the hemispherical space in front of array. The existing methods are not yet well compatible with arbitrary planar array geometries. In this paper, we aim to break this limitation and explore a novel method applicable to arbitrary planar array geometries. First, the covariance between source-induced signals at arbitrary two microphones is formulated as related to the two-dimensional inverse Fourier transform of the source strength. Then, a mathematical model with a source sparsity constraint is built in the continuous domain to denoise the covariances of measured signals, which can be solved by decoupled positive semidefinite programming. Finally, the DOAs are extracted from the solution of the mathematical model via a matrix pencil and pairing method. Simulation and experimental results demonstrate the effectiveness of the proposed method.