bluuebunny/crossref_metadata_2025 huggingface dataset:
Light baryon resonances from a coupled-channel study including $$\mathbf {K\Sigma }$$ photoproduction
Authors: Rönchen D. , Döring M. , Meißner U.-G. , Shen C.-W.
Published: November 2022

The Jülich-Bonn dynamical coupled-channel approach is extended to include $$K\Sigma $$

K
Σ

photoproduction off the proton. Differential cross section and (double) polarization data for $$K^+\Sigma ^0$$

K
+

Σ
0

and $$K^0\Sigma ^+$$

K
0

Σ
+

are analysed simultaneously with the pion- and photon-induced production of $$\pi N$$

π
N

, $$\eta N$$

η
N

, $$K\Lambda $$

K
Λ

, and $$K\Sigma $$

K
Σ

final states, totaling almost 72,000 data points for center-of-mass energies $$W<2.4$$

W
<
2.4

 GeV. Based on the fit results the spectrum of $$N^*$$

N
∗

and $$\Delta $$
Δ
resonances is extracted in terms of pole positions and residues. We discuss the impact of the $$\gamma p\rightarrow K\Sigma $$

γ
p
→
K
Σ

channels in detail and investigate the influence of recent polarization data for $$\eta p$$

η
p

photoproduction.
Tachyonic cosmology with cubic contractions of the Riemann tensor
Authors: Marciu Mihai
Published: November 2022

A new cosmological theory is proposed in the theoretical framework of modified gravity theories which is based on a tachyonic field non-minimally coupled with a specific topological invariant constructed with third order contractions of the Riemann tensor. After proposing the action of the cosmological model, the modified Friedmann relations and the Klein–Gordon equations are obtained, describing the corresponding geometrical corrections to the Einstein–Hilbert action. The physical features of the cosmological system are investigated by adopting the dynamical system analysis in the case of an exponential function for the geometrical coupling term. The investigation revealed that the cosmological system can explain the current accelerated expansion of the Universe and the matter dominated epoch, showing a high compatibility to the recent history of our Universe for various values of the coupling coefficients.
Thin accretion disks around a black hole in Einstein-Aether-scalar theory
Authors: He Tong-Yu , Cai Ziqiang , Yang Rong-Jia
Published: November 2022

We consider the accretion process in the thin disk around a supermassive black hole in Einstein-aether-scalar theory. We probe the effects of the model parameter on the physical properties of the disk. The results show that with increasing value of the parameter, the energy flux, the radiation temperature, the spectra cut-off frequency, the spectra luminosity, and the conversion efficiency of the disk decrease. The disk is hotter and more luminous than that in general relativity for negative parameter, while it is cooler and less luminous for positive parameter. We also find some values of the parameter allowed by the theory are excluded by the physical properties of the disk.
How barrow entropy modifies gravity: with comments on Tsallis entropy
Authors: Di Gennaro Sofia , Xu Hao , Ong Yen Chin
Published: November 2022

Barrow proposed that the area law of the horizon entropy might receive a “fractal correction” $$S\propto A^{1+\Delta /2}$$

S
∝

A

1
+
Δ
/
2

due to quantum gravitational effects, with $$0\leqslant \Delta \leqslant 1$$

0
⩽
Δ
⩽
1

measures the deviation from the standard area law. While such a modification has been widely studied in the literature, its corresponding theory of gravity has not been discussed. We follow Jacobson’s approach to derive the modified gravity theory (interpreted as an effective theory), and find that in the stationary case the resulting theory only differs from general relativity by a re-scaled cosmological constant. Consequently in asymptotically flat stationary spacetimes the theory is identical to general relativity. The theory is not applicable when there is no horizon; the multi-horizon case is complicated. We emphasize on the importance of identifying the correct thermodynamic mass in a theory with modified thermodynamics to avoid inconsistencies. We also comment on the Hawking evaporation rate beyond the effective theory. In addition, we show that the Bekenstein bound is satisfied if the thermodynamic mass is used as the energy, up to a constant prefactor. We briefly comment on the Tsallis entropy case as well. Interestingly, for the latter, the requirement that Bekenstein bound holds imposes a lower bound on the non-extensive parameter: $$\delta > 1/2$$

δ
>
1
/
2

, which unfortunately rules out the previously suggested possibility that the expansion of the universe can accelerate with normal matter field alone.
Compatibility of Poisson–Lie transformations and symmetries of generalized supergravity equations
Authors: Hlavatý Ladislav
Published: November 2022

We investigate two types of transformations that keep NS–NS generalized supergravity equations satisfied: $$\chi $$
χ
-symmetry (20) that shifts dilaton and gauge transformations (30) that change both dilaton and vector field J. Due to these symmetries there is a large set of dilatons and vector fields J that (for a fixed metric and B-field) satisfy generalized supergravity equations but only some of them can be be used as input for Poisson–Lie transformations. Conditions that define the admissible dilatons are given and examples are presented.
LEARNING TO BE OVERCONFIDENT AND UNDERCONFIDENT
Authors: LU YUANZHU , HU JINMING , GONG YAXIAN
Published: November 2022

This paper analyzes the overconfident and underconfident trading behavior simultaneously in the context extended from Gervais and Odean ( 2001 ) [Learning to be overconfident. Review of Financial Studies, 14(1), 1–27]. We find that the overconfidence level will be first decreasing, then increasing and finally decreasing as the number of the successful predictions increases when the underconfident behavior is sufficiently prominent and the expected trading volume in the future will first decrease then increase and finally decrease as the number of successes increases. Furthermore, the insider’s expected profits in the future are a monotonically increasing function of the number of successes when the number of successes is sufficiently small or large but monotonically decreasing function of this number when it is in the intermediate range. This completes the analysis of the investors’ biased behavior.
Quaternionic fermionic field
Authors: Giardino Sergio
Published: November 2022

The second quantization of the quaternionic fermionic field is undertaken using the real Hilbert space approach to quaternionic quantum mechanics ([Formula: see text]QM). The solution responds to an open problem of quaternionic quantum theory, and launches the basis to the development of the quaternionic interaction theory.
Uncertainties in neutrino oscillation parameter sensitivity due to resonance processes at NOνA
Authors: Deka Paramita , Hazarika Nilavjyoti , Bora Kalpana
Published: November 2022

The long baseline (LBL) neutrino experiments use heavy nuclear targets for neutrino scattering in which nuclear effects give rise to complications in measuring the neutrino oscillation parameters up to high precision. These nuclear effects are not yet fully understood and therefore need to be quantified as they contribute to the systematic uncertainties. Precision reconstruction of neutrino energy is one of the main components in measuring the oscillation parameters, and it is required that the neutrino energy is reconstructed with very high precision. In this work, we investigate the effects of the resonance (RES) interaction process using two models for carbon target for [Formula: see text] disappearance channel of the NO[Formula: see text]A experiment, on neutrino-nucleus scattering cross-section, events, and neutrino oscillation parameter sensitivity. We also incorporate the realistic detector specifications of NO[Formula: see text]A. To quantify the systematic uncertainties due to RES interactions, we compare the cross-sections, events, and sensitivity analysis for two models of RES processes—Rein–Sehgal (RS) and Berger–Sehgal (BS), and comment on which model produces more precision. We observe that RES processes contribute significantly, and should be included carefully in models while extracting neutrino oscillation parameters.
Exploring 2 + 2 answers to 3 + 1 questions
Authors: Heckman Jonathan J. , Joyce Austin , Sakstein Jeremy , Trodden Mark
Published: November 2022

We explore potential uses of physics formulated in Kleinian (i.e. 2 + 2) signature spacetimes as a tool for understanding properties of physics in Lorentzian (i.e. 3 + 1) signature. Much as Euclidean (i.e. 4 + 0) signature quantities can be used to formally construct the ground state wavefunction of a Lorentzian signature quantum field theory, a similar analytic continuation to Kleinian signature constructs a state of low particle flux in the direction of analytic continuation. There is also a natural supersymmetry algebra available in 2 + 2 signature, which serves to constrain the structure of correlation functions. Spontaneous breaking of Lorentz symmetry can produce various [Formula: see text] supersymmetry algebras that in 3 + 1 signature correspond to nonsupersymmetric systems. We speculate on the possible role of these structures in addressing the cosmological constant problem.
On the curvature invariants of the massive Banados–Teitelboim–Zanelli black holes and their holographic pictures
Authors: Ghodrati Mahdis , Gregoris Daniele
Published: November 2022

In this paper, the curvature structure of a ([Formula: see text])-dimensional black hole in the massive-charged-Born–Infeld gravity is investigated. The metric that we consider is characterized by four degrees of freedom which are the mass and electric charge of the black hole, the mass of the graviton field, and a cosmological constant. For the charged and neutral cases separately, we present various constraints among scalar polynomial curvature invariants which could invariantly characterize our desired space–times. Specially, an appropriate scalar polynomial curvature invariant and a Cartan curvature invariant which together could detect the black hole horizon would be explicitly constructed. Using algorithms related to the focusing properties of a bundle of light rays on the horizon which are accounted for by the Raychaudhuri equation, a procedure for isolating the black hole parameters, as the algebraic combinations involving the curvature invariants, would be presented. It will be shown that this technique could specially be applied for black holes with zero electric charge, contrary to the cases of solutions of lower-dimensional nonmassive gravity. In addition, for the case of massive ([Formula: see text])-dimensional black hole, the irreducible mass, which quantifies the maximum amount of energy which could be extracted from a black hole would be derived. Therefore, we show that the Hawking temperatures of these black holes could be reduced to the pure curvature properties of the space–times. Finally, we comment on the relationship between our analysis and the novel roles it could play in numerical quark–gluon plasma simulations and other QCD models and also black hole information paradox where the holographic correspondence could be exploited.
The NNLO QCD analysis of gluon density at small-x
Authors: Devee Mayuri , Sarma J. K.
Published: November 2022

In this paper, a next-to-next-to-leading order (NNLO) quantum chromodynamics (QCD) calculation of gluon distribution function at small-[Formula: see text] is presented. The gluon distribution function is explored analytically in the Dokshitzer–Gribov–Lipatov–Altarelli–Parisi approach by a Taylor expansion at small-[Formula: see text] as two first-order partial differential equations in two variables: Bjorken [Formula: see text] and [Formula: see text][Formula: see text]. We have solved the system of equations at LO, NLO and NNLO, respectively, by Lagrange’s method. The resulting analytical expressions are compared with the available global parton distribution function fits as well as with the results of the Block–Durand–McKay model. We have further performed an [Formula: see text] test to check the compatibility of our predictions and observed that our results can be consistently described in the context of perturbative QCD. A comparative analysis of the obtained results at LO, NLO and NNLO reveals that the NNLO approximation has a significant contribution to the gluon distribution function particularly in the small-[Formula: see text] region.
The fate of infrared divergences in a finite formulation of field theory: QED revisited
Authors: Mathiot Jean-François
Published: November 2022

Within the framework of the recently proposed Taylor–Lagrange regularization procedure, we reanalyze the calculation of radiative corrections in quantum electrodynamics (QED) at next to leading order. Starting from a well-defined local bare Lagrangian, the use of this regularization procedure enables us to manipulate fully finite elementary amplitudes in the ultra-violet (UV) as well as infrared (IR) regimes, in physical [Formula: see text] space–time dimensions and for physical massless photons, as required by gauge invariance. We can thus separately calculate the electromagnetic form factors of the electron and the cross-section for real photon emission, each quantity being finite in these physical conditions. We then discuss the renormalization group (RG) equations within this regularization procedure. Thanks to the taming of IR divergencies, the RG equation associated to the (physical) effective charge exhibits an UV stable fixed point at [Formula: see text], showing an asymptotic freedom-type behavior. We finally consider the case of two mass scales, one low and one heavy, paying particular attention to the natural decoupling properties between heavy and light degrees of freedom. As a direct consequence, the fine structure constant should be zero in the limit of massless electrons.
Twist-4 T-even proton TMDs in the light-front quark–diquark model
Authors: Sharma Shubham , Dahiya Harleen
Published: November 2022

We have dealt with the twist-4 T-even transverse momentum dependent parton distributions (TMDs) for the case of proton in the light-front quark–diquark model (LFQDM). By decoding the unintegrated quark–quark correlator for the semi-inclusive deep inelastic scattering (SIDIS), we have specifically obtained the overlap form for the unpolarized [Formula: see text], longitudinally polarized [Formula: see text] and transversely polarized ([Formula: see text] and [Formula: see text]) proton TMDs. We have provided the explicit expressions for both the cases of the diquark being a scalar or a vector. Average transverse momenta and the average square transverse momenta for the TMDs have been calculated and the results have been tabulated with corresponding leading twist TMDs. In addition, the value of average transverse momentum and average square transverse momentum for TMD [Formula: see text] has been compared with the available light-front constituent quark model (LFCQM) results. From TMDs, we have also obtained and discussed the transverse momentum-dependent parton distribution functions (TMDPDFs). The model relations of the twist-4 T-even TMDs with the available leading twist T-even TMDs have also been obtained.
Accretion around cloud of strings in 4D Einstein–Gauss–Bonnet black hole
Authors: Long Feng , Yang Mengying , Chen Juhua , Wang Yongjiu
Published: November 2022

In this paper, we study the accretion process of a charged black hole in the background of cloud of strings in the framework of 4D Einstein–Gauss–Bonnet (EGB) gravity theory. Firstly, the steady spherical accretion process of ideal fluid on 4D cloud of strings EGB black hole is studied from the aspects of the radial velocity, the energy density, the mass accretion rate and the sound speed. Then, the general analytical expressions of the accretion process are determined, and the effects of the black hole parameters on the radial velocity, the energy density, the mass accretion rate and the sound velocity are discussed. When the GB coupling constant increases, the energy density and mass accretion rate increase, and the sound velocity and radial speed decrease. EGB gravity and charge have similar physical effects on the accretion process of black hole.
Automated SAR Image Segmentation and Classification Using Modified Deep Learning
Authors: Srinitya G. , Sharmila D. , Logeswari S. , Raja S. Daniel Madan
Published: November 2022

Synthetic Aperture Radar (SAR) represents a type of active remote sensing technology that uses microwave electromagnetic radiation to produce and send data to the surface of a target location. SAR imaging is frequently used in national security applications since it is unaffected by weather, geographical location, or time. In this system, many approaches are examined, to improve automation for segmentation and classification. The utilization of Deep Neural Networks (DNNs) to classify SAR images has gotten a lot of attention, and it usually requires several layers of deep models for feature learning. With insufficient training data, however, the DNN will get affected by the overfitting issue. The major purpose of this work is to make a development on introducing a new framework for SAR image segmentation and categorization using deep learning. Owing to the coherent nature of the backscattering signal, SARs create speckle noise in their images. If the image has noisy material, classification becomes more challenging. Hence, the pre-processing of the images is employed by linear spatial filtering to remove the noise. Further, the Optimized U-Net is used for the segmentation. For the segmented images, the Binary Robust Independent Elementary Features (BRIEF) concept is adopted as the feature descriptor. These features are inputted to the Convolutional Neural Network (CNN) with Tuned Weight DNN (C-TWDNN) for the classification. In both segmentation and classification, the parameter tuning is employed by the combination of Galactic Swarm Optimization (GSO) and Deer Hunting Optimization Algorithm (DHOA) called the Self-adaptive-Galactic Deer Hunting Optimization (SA-GDHO). Experiments are conducted on a variety of public datasets, demonstrating that our method is capable of outperforming various expert systems and deep structured architectures.
Unison Sound Separation Using Localized Extended Common Amplitude Modulation
Authors: Gong Yukai , Dai Longquan
Published: November 2022

Musical source separation isolates one or more musical instruments from a polyphonic mixture. The main challenge is to separate the source partials overlapped in the same time–frequency region. For the unison case, the source separation task is quite difficult because no source has nonoverlapping partials. Owing to the lack of effective methods in monaural unison sound separation, this paper proposes a localized extended common amplitude modulation (LECAM) method. Our strategy assumes that partials from the same source have correlated amplitude envelopes in a period of time and use a multi-band co-processing way for separating each source partial. Extensive experiments are conducted on unison mixture samples drawn from the Iowa University Musical Instrument Database. Results demonstrate that our LECAM achieves the overall best separation performance.
H∞ Filtering Controller for Discrete Time-Varying Delay System with Missing Measurements
Authors: Darouiche Fatima Zahra , Tissir El Houssaine
Published: November 2022

The aim of this paper is to address the analysis and design problem of [Formula: see text] filtering for discrete time-varying delay systems with missing measurements. Our attention is focused on the filter design, using Scaled Small Gain (SSG) approach, guaranteeing the asymptotic stability of the augmented system. A transformation model is obtained via three-term approximation method and Input–Output (IO) approach based on the SSG theorem. The use of SSG theorem for the stability of discrete time-varying delayed systems with missing measurements has not been studied elsewhere in the literature. This represents the main innovation of this paper. Less conservative results are obtained, compared with previous results, and are established in terms of LMIs. Numerical examples illustrate the applicability of the proposed methodology.
Modified Dual Mode Transmission Gate Diffusion Input Logic for Improving Energy Efficiency
Authors: Yadav Neetika , Pandey Neeta , Nand Deva
Published: November 2022

This paper presents a modified energy-efficient Dual Mode Transmission Gate Diffusion Input (DMTGDI) design and is termed as M-DMTGDI. A contention issue in dynamic mode operation of existing DMTGDI design and DMPL design is identified and illustrated through mathematical formulation and simulations. To resolve this concern, the pre-charge/pre-discharge transistor in existing DMTGDI design is replaced by dual mode inverter in the proposal. The functional verification and performance comparison of NAND, NOR, XOR gates and 1-bit full adder based on proposed M-DMTGDI is carried out using 90 nm BSIM4 model card for bulk CMOS using Symica DE tool. The performance of the circuits is evaluated in terms of power, delay and Power Delay Product (PDP) in both static and dynamic modes. The variation of PDP with the ratio of the time the circuit is designed to run in dynamic mode against static mode is also investigated to analyze the energy efficiency of the M-DMTGDI design. The proposed approach offers maximum PDP reduction of 33.52%, 99.39% and 96.61% for 2-input gates as compared to their footed DML, DMPL and DMTGDI counterparts, respectively. The reduction in PDP is quite significant in 1-bit full adder circuit where the corresponding values are 94.18%, 99.41% and 99.79%, respectively.
A Hybrid Neural Network-Based Intelligent Forecasting Approach for Capacity of Photovoltaic Electricity Generation
Authors: Zhang Yinjuan , Wang Yongke
Published: November 2022

In recent years, photovoltaic power generation technology has become the key planning direction of the country. It is important to effectively predict photovoltaic (PV) electricity generation capacity, so that the administrators can well schedule resource allocation. Currently, most of the photovoltaic electricity generation forecasting models took meteorological data as the input parameters of neural network. However, the input parameters and redundant data cause neural network to converge difficultly. Besides, single types of neural network models cannot well capture the comprehensive characteristics, which may influence forecasting effect in evolving process. As a result, we propose a hybrid neural network-based intelligent forecasting approach for PV electricity generation capacity. First, convolution neural network (CNN) is adopted to extract the connection between features and data from the perspective of convolution operations. And then, the extracted feature vector of time series is sent into the long short-term memory (LSTM) model. Finally, the forecasting values are predicated by training the outlined LSTM network. The experimental results indicate that such a hybrid CNN-LSTM model can significantly improve the precision of PV electricity generation prediction and provide an effective way to forecast generation power of PV system.
Research on Calibration Method of Rail Profile Measurement System
Authors: Wang Ning , Wang Hao , Wang Shengchun , Zhao Xinxin , Wang Fan , Hao Jinfei
Published: November 2022

The rail profile measurement system is used to obtain the full section profile of the rail, which is the core of the wheel/ rail interaction, based on the principle of infrared structured light. The system calibration is the key as to whether the accuracy is high enough to guide the railway maintenance. In this study, we propose a convenient and efficient checkerboard plane target calibration method based on the partition-based calibration. This method can theoretically solve the three unavoidable factors that affect the accuracy in the traditional method and is very easy to use in the field with the designed equipment. The test shows that this method has higher accuracy. We propose a correction method for the stitching calibration of double-sided cameras. Based on the standard block and high-precision stitching of rail, full section profile is achieved. Finally, through ingeniously designed field tests, it is proved that the original accuracy is significantly improved from 0.3[Formula: see text]mm to 0.1[Formula: see text]mm, and the repeatability is obviously improved as well. The method proposed in this study can also be extended to similar systems, improving system accuracy and simplifying the calibration procedures.
An Artificial Neural Network-Based Intelligent Prediction Model for Financial Credit Default Behaviors
Authors: Chen Zhuo , Wu Zihao , Ye Wenwei , Wu Shuang
Published: November 2022

With the rapid development of intelligent techniques, smart finance has become a hot topic in daily life. Currently, financial credit is facing increasing business volume, and it is expected that investigating the intelligent algorithms can help reduce human labors. In this area, the prediction of latent credit default behaviors can help deal with loan approval affairs, and it is the most important research topic. Machine learning-based methods have received much attention in this area, and they can achieve proper performance in some scenarios. However, machine learning-based models cannot have resilient objective function, which can cause failure in having stable performance in different problem scenarios. This work introduces deep learning that has the objective function with high freedom degree, and proposes an artificial neural network-based intelligent prediction model for financial credit default behaviors. The whole technical framework is composed of two stages: information encoding and backbone network. The former makes encoding toward initial features, and the latter builds a multi-layer perceptron to output prediction results. Finally, the experiments are conducted on a real-world dataset to evaluate the efficiency of the proposed approach.
On the primality and elasticity of algebraic valuations of cyclic free semirings
Authors: Jiang Nancy , Li Bangzheng , Zhu Sophie
Published: November 2022

A cancellative commutative monoid is atomic if every non-invertible element factors into irreducibles. Under certain mild conditions on a positive algebraic number [Formula: see text], the additive monoid [Formula: see text] of the evaluation semiring [Formula: see text] is atomic. The atomic structure of both the additive and the multiplicative monoids of [Formula: see text] has been the subject of several recent papers. Here we focus on the monoids [Formula: see text], and we study its omega-primality and elasticity, aiming to better understand some fundamental questions about their atomic decompositions. We prove that when [Formula: see text] is less than [Formula: see text], the atoms of [Formula: see text] are as far from being prime as they can possibly be. Then we establish some results about the elasticity of [Formula: see text], including that when [Formula: see text] is rational, the elasticity of [Formula: see text] is full (this was previously conjectured by Chapman, Gotti and Gotti).
Lattice characterization of some classes of groups by series of subgroups
Authors: Grulović Milan , Jovanović Jelena , Šešelja Branimir , Tepavčević Andreja
Published: November 2022

In this paper, we characterize several classes of groups by the properties of their weak congruence lattices. Namely, we give necessary and sufficient conditions for the weak congruence lattice of a group, under which this group is a [Formula: see text]-group, [Formula: see text]-group, metacyclic, cocyclic, hyperabelian, polycyclic, [Formula: see text]-group and [Formula: see text]-group. We also discuss groups for which all subgroups are simple, like the Tarski monsters, and we show that they represent a class of non-Dedekind groups with a particular embedding property for lattices of normal subgroups. All the mentioned characterized groups are related to (different) series of subgroups, and we represent these series as chains of intervals in the weak congruence lattice. The corresponding conditions are formulated in a purely lattice-theoretic language.
Blockchain and Artificial Intelligence-based Solutions for Healthcare Management: Liver Disease Detection as a Case Study
Authors: Tarek Zahraa , Elhoseny Mohamed , El-Hasnony Ibrahim M.
Published: November 2022

The issue of privacy in clinical data restricts data sharing among various organizations because of legal and ethical concerns. Every medical organization (hospital, research center, testing lab, etc.) needs to protect personal and medical data privacy and confidentiality while also sharing data with efficient and accurate learning models for various diseases. This paper addresses a method that combines machine learning approaches on blockchain network for classification of patients with liver disease or not, while maintaining the privacy and enabling data sharing. The contribution of this paper is five-folds: (i) To deal with the liver disease dataset, data preprocessing phases are utilized (i.e., missing data treatment, data normalization, and data transformation). (ii) For feature reduction, two feature selection models are used: correlation feature selection (CFS) and wrapper metaheuristic (PSO+KNN). For training the proposed global model, the selected features (10, 4, 3) from the three models (all features, CFS, PSO+KNN) are distributed to the shared blockchain network. (iii) To detect liver disease in the preprocessed dataset, three machine learning methods are proposed: random forest, decision tree (J48), and Naïve Bayes. (iv) The distributed network (blockchain) will publish the results of the liver disease diagnosis on the network. (v) The smart contract shares the data and diagnosis between the medical organizations for future processing. An empirical study is executed to validate the relevance of our suggested framework for early diagnosis of liver disease using blockchain and machine learning models. The experimental results showed that feature selection using the wrapper metaheuristic (PSO+KNN) with a random forest model achieves the best performance with the minor features for detecting liver disease with an accuracy of 99.9 compared to 99.2, 89.2 for Naïve Bayes, and J48, respectively.
Ensemble Learning Based Gene Regulatory Network Inference
Authors: Peignier Sergio , Sorin Baptiste , Calevro Federica
Published: November 2022

In the machine learning field, the technique known as ensemble learning aims at combining different base learners in order to increase the quality and the robustness of the predictions. Indeed, this approach has widely been applied to tackle, with success, real world problems from different domains, including computational biology. Nevertheless, despite their potential, ensembles combining results from different base learners have been understudied in the context of gene regulatory network inference. In this paper we applied genetic algorithms and frequent itemset mining, to design small but effective ensembles of gene regulatory network inference methods. These ensembles were evaluated and compared to well-established single and ensemble methods, on both real and synthetic datasets. Results showed that small ensembles, consisting of few but diverse base learners, enhance the exploration of the solution space, and compensate base learners biases, outperforming state-of-the-art methods. Results advocate for the use of such methods as gene regulatory network inference tools.
The embedded homology of hypergraph pairs
Authors: Ren Shiquan , Wu Jie , Zhang Mengmeng
Published: November 2022

In this paper, we generalize the embedded homology groups of hypergraphs initially given in [S. Bressan, J. Li, S. Ren and J. Wu, The embedded homology of hypergraphs and applications, Asian J. Math. 23(3) (2019) 479–500] and study the relative embedded homology groups of hypergraph pairs. We prove some long exact sequences as well as a Mayer–Vietoris sequence for the relative embedded homology groups of hypergraph pairs. Moreover, we briefly discuss the two-dimensional persistence for the relative embedded homology groups of hypergraph pairs.
Determinants of twisted generalized hybrid weaving knots
Authors: Joshi Sahil , Prabhakar Madeti
Published: November 2022

This paper presents a formula for the determinant of the twisted generalized hybrid weaving knot [Formula: see text] which is a closed 3-braid. As a corollary, we prove Conjecture 2 given in Singh and Chbili [Nuclear Phys. B 980 (2022) 115800].
The one-row-colored 𝔰𝔩3 Jones polynomials for pretzel links
Authors: Kawasoe Kotaro
Published: November 2022

The colored [Formula: see text] Jones polynomials [Formula: see text] are given by a link and an [Formula: see text]-irreducible representation of [Formula: see text]. In general, it is hard to calculate [Formula: see text] for an oriented link [Formula: see text]. However, we calculate the one-row-colored [Formula: see text] Jones polynomials [Formula: see text] for three-parameter families of oriented pretzel links [Formula: see text] by using Kuperberg’s linear skein theory by setting [Formula: see text]. Furthermore, we show the existence of the tails of [Formula: see text] for the alternating pretzel knots [Formula: see text].
A NUMERICAL AND STATISTICAL APPROACH OF DRILLING PERFORMANCE ON MACHINING OF Ti–6Al–4V ALLOY
Authors: UĞUR LEVENT
Published: November 2022

Drilling, which constitutes one third of the machining operations, is widely used in many areas of the manufacturing industry. Various difficulties are encountered in the drilling process since the chip is formed in a closed limited chip flows. These difficulties directly affect the output parameters such as energy consumption, surface quality, and cutting force. Therefore, it is necessary to determine the ideal processing parameters to achieve the best performance. However, experimental research on machining processes requires both a long time and a high cost. For these reasons, machining outputs can be estimated by conducting drilling simulations with the finite element method. In this study, the finite element method is used in order to investigate the influence of different cutting parameters and different helix angles on the power and thrust force of Ti–6Al–4V (grade 5) alloy that is commonly used in the aviation industry. The study selected three different cutting speeds, feed rates, and helix angles as the cutting parameters. The experimental design was made according to the response surface method (RSM) Box–Behnken design in the Design-Expert program. Drilling simulations were performed using the ThirdWave AdvantEdgeTM software. The lowest thrust force measured is 1241.39 N at 40° helix angle, 2000-rpm revolution rate, and 0.05-mm/rev feed rate, while the lowest power consumed is 765.025 W at 30° helix angle, 1500-rpm revolution rate, and 0.05-mm/rev feed rate. As a result, it was determined that the most effective parameter for power and thrust force was the feed rate.
INFLUENCE OF VOLTAGE ON ANODE GAS COMPOSITIONS DURING PLASMA ELECTROLYTIC OXIDATION OF 60 VOL.% SiCp/2009 ALUMINUM MATRIX COMPOSITE
Authors: LIAO YIZHAO , WANG XINGPING , XU CHI , WEI KEJIAN , GAO CHUANLI , DU JIANCHENG , JIN XIAOYUE , JIANG FUBIN , XUE WENBIN , ZHANG YONGZHONG
Published: November 2022

Plasma electrolytic oxidation (PEO) was performed on 60 vol.% SiCp/2009 aluminum matrix composite under different voltages in silicate solution and NaF solution, respectively. Anode gas evolutions under different conditions during the PEO process were evaluated by the gas chromatograph, optical emission spectroscopy, scanning electron microscope, X-ray diffraction and inductively coupled plasma atomic emission spectroscopy. The anode gas released at different voltages in both solutions contained H2, O2 and trace CO. The H2 concentration increased with the increase of voltage in the silicate solution, and then it was kept at 75–80 vol.% in the range from [Formula: see text]480 V/–0 V to [Formula: see text]520 V/–0 V, which was related to the appearance of strong discharge sparks. The H2 concentration of the anode gas in NaF solution was much lower than that in the silicate solution due to the weak discharge. The excessive H2 was caused by nonfaradaic reactions in the plasma discharge region such as thermal decomposition of water. Meanwhile, the O2 in anode gas mainly came from thermal decomposition of water in plasma discharge region and traditional electrochemical reactions in nondischarge region. In addition, SiC reinforcement particles were oxidized in plasma discharge channels with the temperature up to 5000 K, accompanied by the release of trace CO. Furthermore, CO2 was hardly detected due to the effect of H2 reduction in the discharge channels.
Structurally Nonlinear Fluttering of a Three-Degree-Freedom Wing with Random Disturbances
Authors: Hao Ying , Du Xuewen , Ma Chao
Published: November 2022

The differential equations of motion are established for a three-degree-freedom wing dynamic model subjected to unsteady aerodynamic loads and random perturbations. The system is dimensionally reduced by the improved average method to obtain the standard equations. Flutter problems of the deterministic wing system with high-order structural nonlinearity are studied using Hopf bifurcation theory and numerical simulation, the critical flutter speed is obtained and the effectiveness of the improved average method in the process of dimensionality reduction is verified. The stochastic P-bifurcation behaviors of the system are analyzed considering the effects of random perturbations of the longitudinal airflow by examining the qualitative variations of the probability density function curves. The results show that the deterministic wing system has a secondary bifurcation, a bistable phenomenon in which the equilibrium and the limit cycle oscillations coexist. The random disturbances significantly increases the critical flutter speed of the wing system, and the amplitude of limit cycle oscillations increases after including random perturbations for the same incoming flow speed.
Modeling of a Porous Piezoelectric Nano Energy Harvester Based on Timoshenko-Beam Theory
Authors: Fan Tao
Published: November 2022

Collecting electric power from the vibration of piezoelectric beams is practical and has been widely used for decades. This paper investigates a porous piezoelectric cantilever Timoshenko-beam energy harvester at nanoscale. The aim is to propose an optimized Timoshenko beam in order to gain more power with the same working conditions. For this purpose, the width of the beam is assumed to be exponentially changing and pores are also introduced into the beam to relieve the inherent brittleness of piezoelectric materials. Based on Timoshenko beam theory and porous piezoelectric elasticity, the uncoupled motion equations of the porous piezoelectric nanoTimoshenko beam are deduced. The analytical solutions to the output voltage and power density are obtained. According to the numerical calculation, it can be concluded that the electrical output can be improved by increasing the section parameter. Moreover, the surface effects and pore properties on the energy harvesting characteristics are discussed. In addition, when there is a concentrated mass at the free end of the beam, the displacements and output power are studied.
Analysis on the Vibration Performance of Spruce Structure with Variable Cross-Section Under Snow Load by Semi-Analytical Method
Authors: Meng Jie , Mu Yongxiang , Ma Xiaochang , Guo Jiaxuan
Published: November 2022

Trees have various forms and structures, most of which have excellent mechanical properties. Spruce has a stable structure and excellent resistance to wind and snow loads. In this paper, the vibration performance of spruce is studied by the semi-analytical method. Based on the vibration theory of Euler–Bernoulli beam, the vibration mechanical model of the spruce trunk with variable cross-section is established by using the segmental equivalence method. Then, the natural frequency and modal function of the trunk are analyzed and the displacements are solved under snow load within one hour. The results show that the first four natural frequencies are 120.417[Formula: see text]rad/s, 188.414[Formula: see text]rad/s, 237.699[Formula: see text]rad/s and 288.964[Formula: see text]rad/s, respectively. During the continuous loading stage, the displacements increase over time. During the static load stage, the displacements change in a harmonic form. The above results are verified by an experimental measurement. This paper provides a reference for the study of the vibration performance of similar structures.
Derivations of quantum and involution generalized Weyl algebras
Authors: Kitchin Andrew P.
Published: November 2022

In this paper, we classify the derivations of degree-one generalized Weyl algebras over a univariate Laurent polynomial ring. In particular, our results cover the Weyl–Hayashi algebra, a quantization of the first Weyl algebra arising as a primitive factor algebra of [Formula: see text], and a family of algebras which localize to the group algebra of the infinite group with generators [Formula: see text] and [Formula: see text], subject to the relation [Formula: see text].
Locally standard measure algebras
Authors: Bezushchak Oksana , Oliynyk Bogdana
Published: November 2022

We parameterize countable locally standard Boolean measure algebras by pairs of a Steinitz number and a real number greater or equal to [Formula: see text] This is an analog of the theorems of Dixmier and Baranov.
Fixed points and orbits in skew polynomial rings
Authors: Chapman Adam , Paran Elad
Published: November 2022

In this paper, we study orbits and fixed points of polynomials in a general skew polynomial ring [Formula: see text]. We extend results of the first author and Vishkautsan on polynomial dynamics in [Formula: see text]. In particular, we show that if [Formula: see text] and [Formula: see text] satisfy [Formula: see text], then [Formula: see text] for every formal power of [Formula: see text]. More generally, we give a sufficient condition for a point [Formula: see text] to be [Formula: see text]-periodic with respect to a polynomial [Formula: see text]. Our proofs build upon foundational results on skew polynomial rings due to Lam and Leroy.
Multiplicative anti-derivations of generalized n-matrix rings
Authors: Ferreira B. L. M. , Sandhu G. S.
Published: November 2022

In this paper, we prove that every multiplicative anti-derivation map of an arbitrary generalized [Formula: see text]-matrix ring is additive. Even more, as consequence, we get the same conclusion for the class of triangular [Formula: see text]-matrix rings, unital prime rings with a nontrivial idempotent, standard operator algebras and factor von Neumann algebras.
Flag-transitive 2-(v,k,λ) designs with λ prime and alternating socle
Authors: Zhang Yongli , Chen Jianfu , Zhou Shenglin
Published: November 2022

This paper is a contribution to the classification of 2-designs admitting a flag-transitive automorphism group. Let [Formula: see text] be a 2-[Formula: see text] design with [Formula: see text] prime and [Formula: see text] be a flag-transitive, point-primitive automorphism group of [Formula: see text]. We prove that if the socle of [Formula: see text] is an alternating group, then [Formula: see text] has parameters [Formula: see text] or [Formula: see text].
Block coordinate type methods for optimization and learning
Authors: Yu Zhan
Published: November 2022

We study nonconvex (composite) optimization and learning problems where the decision variables can be split into blocks of variables. Random block projection is a popular technique to handle this kind of problem for its remarkable reduction of the computational cost from the projection. This powerful method has not been well proposed for the situation that first-order information is prohibited and only zeroth-order information is available. In this paper, we propose to develop different classes of zeroth-order stochastic block coordinate type methods. Zeroth-order block coordinate descent (ZS-BCD) is proposed for solving unconstrained nonconvex optimization problem. For composite optimization, we establish the zeroth-order stochastic block mirror descent (ZS-BMD) and its associated two-phase method to achieve the complexity bound for the composite optimization problem. Furthermore, we also establish zeroth-order stochastic block coordinate conditional gradient (ZS-BCCG) method for nonconvex (composite) optimization. By implementing ZS-BCCG method, in each iteration, only (approximate) linear programming subproblem needs to be solved on a random block instead of a rather costly projection subproblem on the whole decision space, in contrast to the existing traditional stochastic approximation methods. In what follows, an approximate ZS-BCCG method and corresponding two-phase ZS-BCCG method are proposed. This is also the first time that a two-phase BCCG method has been developed to carry out the complexity analysis of nonconvex composite optimization problem.
Generalized Appell polynomials and Fueter–Bargmann transforms in the polyanalytic setting
Authors: De Martino Antonino , Diki Kamal
Published: November 2022

This paper deals with some special integral transforms in the setting of quaternionic valued slice polyanalytic functions. In particular, using the polyanalytic Fueter mappings, it is possible to construct a new family of polynomials which are called the generalized Appell polynomials. Furthermore, the range of the polyanalytic Fueter mappings on two different polyanalytic Fock spaces is characterized. Finally, we study the polyanalytic Fueter–Bargmann transforms.
A Review, Water-Soluble CuInS Quantum Dots, Strategies and Photoluminescence
Authors: Kamel Ola A. , Fouad M. , Ali Magdy
Published: November 2022

Water-soluble semiconductor quantum dots (QDs) have become a unique field of materials science with great potential for applications in biomedical and optoelectronic devices. However, the more stable and bright QDs are the conventional QDs that contain toxic heavy metals such as Pb, Cd and Hg or the QDs that were synthesized in an organic phase. Hence, it is important to find an alternative material with similar optical properties and low cytotoxicity among these materials. Recently, hydrophilic CuInS2 (CIS) QDs have attracted a lot of interest due to their direct bandgap in the infrared region, large optical absorption coefficient, hydrophilicity, low cost and low toxic composition. These factors make them a good material for biomedical applications. This review starts with the origin characteristics of CIS QDs followed by various synthetic strategies, including synthesis in aqueous solvents and transformation from organic phase to water-soluble phase QDs. Then the tuning of their optical properties is discussed. The review then considers the strategies to improve the photoluminescence performances of CIS QDs.