bluuebunny/crossref_metadata_2025 huggingface dataset:
Dynamic changes in place-based measures of structural racism and preterm birth in the USA
Authors: Das Abhery , Casey Joan A , Gemmill Alison , Catalano Ralph , Lee Hedwig , Stolte Allison , Bustos Brenda , Bruckner Tim A
Published: June 2024

Background

Structurally racist systems, ideologies and processes generate and reinforce inequities among minoritised racial/ethnic groups. Prior cross-sectional literature finds that place-based structural racism, such as the Index of Concentration at the Extremes (ICE), correlates with higher infant morbidity and mortality. We move beyond cross-sectional approaches and examine whether a decline in place-based structural racism over time coincides with a reduced risk of preterm birth across the USA.

Methods

We used as the outcome count of preterm births overall and among non-Hispanic (NH) black and NH white populations across three epochs (1998–2002, 2006–2010, 2014–2018) in 1160 US counties. For our measure of structural racism, we used ICE race/income county measures from the US Census Bureau. County-level fixed effects Poisson models include a population offset (number of live births) and adjust for epoch indicators, per cent poverty and mean maternal age within counties.

Results

An SD increase in ICE (0.11) over time corresponds with a 0.6% reduced risk of preterm birth overall (incidence rate ratio (IRR): 0.994, 95% CI 0.990, 0.998), a 0.6% decrease in preterm risk among NH black births (IRR: 0.994, 95% CI 0.989, 0.999) and a 0.4% decrease among NH white births (IRR: 0.996, 95% CI 0.992, 0.999).

Conclusions

Movement away from county-level concentrated NH black poverty preceded reductions in preterm risk, especially among NH black populations. Our longitudinal design strengthens inference that place-based reductions in structural racism may improve perinatal health. These improvements, however, do not appear sufficient to redress large disparities.
Measuring lung diffusing capacity: an opportunity for improved medical surveillance and disability evaluation of coal miners
Authors: Go Leonard H T , Almberg Kirsten S , Friedman Lee S , Zell-Baran Lauren , Rose Cecile S , Cohen Robert A
Published: June 2024

Objectives

Spirometry is the primary lung function test utilised for medical surveillance and disability examination for coal mine dust lung disease. However, spirometry likely underestimates physiologic impairment. We sought to characterise abnormalities of single-breath diffusing capacity for carbon monoxide (DLCO) among a population of former coal miners.

Methods

Data from 3115 former coal miners evaluated at a West Virginia black lung clinic between 2006 and 2015 were retrospectively analysed to study the association between diffusion impairment (abnormally low DLCO), resting spirometry and the presence and severity of coal workers’ pneumoconiosis on chest radiography. We developed ordinary least squares linear regression models to evaluate factors associated with per cent predicted DLCO(DLCOpp).

Results

Diffusion impairment was identified in 20.2% of subjects. Ten per cent of all miners with normal spirometry had diffusion impairment including 7.4% of never smokers. The prevalence of diffusion impairment increased with worsening radiographic category of pneumoconiosis. Mean DLCOpp decreased with increasing small opacity profusion subcategory in miners without progressive massive fibrosis. Linear regression analysis also showed significant decreases in DLCOpp with increasing small opacity profusion and presence of large opacities.

Conclusions

Diffusion impairment is common among former coal miners, including among never smokers, miners without radiographic pneumoconiosis and miners with normal spirometry. These findings demonstrate the value of including DLCOtesting in disability examinations of former coal miners and an important role for its use in medical surveillance of working miners to detect early chronic lung disease.
Insight into the molecular basis of the soluble storage-state to fibrous-state structural transformation of spider pyriform silk
Authors: Ghimire Anupama , Phạm Trân Thanh Tâm , Reith Melissa A. , Rainey Jan K.
Published: June 2024

Pyriform (or piriform) silk is a fibrous spider silk used in a composite material to attach web silks to substrates and disparate silk types together. Argiope argentata pyriform silk is formed from a protein with a central repetitive region consisting of a 234-amino acid unit (the “Py unit”) repeated 21 times. We have previously shown that the Py unit behaves modularly, with a structured core of 6 α-helices that retains its structuring upon truncation of N- and C-terminal intrinsically disordered segments. Here, we apply solution-state nuclear magnetic resonance (NMR) spectroscopy to investigate the structured core of the Py unit. Based on 15N spin relaxation measurements and reduced spectral density mapping at two field strengths, the α-helical core of the Py unit exhibits minimal backbone motion beyond the tumbling of the globular domain except for one inter-helical linker that exhibits a notably higher degree of dynamics. Evaluation of rotational diffusion based on 15N spin relaxation and translational diffusion by pulsed field gradient diffusion NMR demonstrates that the core of the Py unit behaves as a compact structure, with hydrodynamic behaviour consistent with a well-packed protein. Pyriform silk protein undergoes a structural transformation upon conversion from the soluble-state to the fibrous-state, with a loss of α-helical content and gain of β-sheet content. The more dynamic segment we observe midway through the structured core of the Py core, especially in the context of the intrinsically disordered segments that flank the core, would provide an initiation point for decompaction, structural transformation, and/or intermolecular interactions.
Massive propagating modes of torsion
Authors: Denk Vladimir , Vasak David , Kirsch Johannes
Published: June 2024

The dynamics of the torsion field is analyzed in the framework of the Covariant Canonical Gauge Theory of Gravity (CCGG), a De Donder–Weyl Hamiltonian formulation of gauge gravity. The action is quadratic in both, the torsion and the Riemann–Cartan tensor. Since the latter adds the derivative of torsion to the equations of motion, torsion is no longer identical to spin density, as in the Einstein–Cartan theory, but an additional propagating degree of freedom. As torsion turns out to be totally anti-symmetric, it can be parametrised via a single axial vector. It is shown in this paper that, in the weak torsion limit, the axial vector obeys a wave equation with an effective mass term which is partially dependent on the scalar curvature. The source of torsion is thereby given by the fermion axial current which is the net fermionic spin density of the system. Possible measurable effects and approaches to experimental analysis are addressed. For example, neutron star mergers could act as a dipoles or quadrupoles for torsional radiation, and an analysis of radiation of pulsars could lead to a detection of torsion wave background radiation.
When climate variables improve the dengue forecasting: a machine learning approach
Authors: da Silva Sidney T. , Gabrick Enrique C. , Protachevicz Paulo R. , Iarosz Kelly C. , Caldas Iberê L. , Batista Antonio M. , Kurths Jürgen
Published: June 2024

Dengue is a viral vector-borne infectious disease that affects many countries worldwide, infecting around 390 million people per year. The main outbreaks occur in subtropical and tropical countries. We, therefore, study here the influence of climate on dengue. In particular, we consider dengue and meteorological data from Natal (2016–2019), Brazil, Iquitos (2001–2012), Peru, and Barranquilla (2011–2016), Colombia. For the analysis and simulations, we apply machine learning (ML) techniques, especially the random forest (RF) algorithm. We utilize dengue disease cases and climate data delayed by up to one week to forecast the cases of dengue. In addition, regarding as feature in the ML technique, we analyze three possibilities: only dengue cases (D); climate and dengue cases (CD); humidity and dengue cases (HD). Depending on the city, our results show that the climate data can improve or not the forecast. For instance, for Natal, the case D induces a better forecast. For Iquitos, it is better to use all the climate variables. Nonetheless, for Barranquilla, the forecast is better, when we include cases and humidity data. Another important result is that each city has an optimal region based on the training length. For Natal, when we use more than 64% and less than 80% of the time series for training, we obtain results with correlation coefficients (r) among 0.917 and 0.949 and mean absolute errors (MAE) among 57.783 and 71.768 for the D case in forecasting. The optimal range for Iquitos is obtained when 79% up to 88% of the time series is considered for training. For this case, the best case is CD, having a minimum r equal to 0.850 and maximum 0.887, while values of MAE oscillate among 2.780 and 4.156. For Barranquilla, the optimal range occurs between 72% until 82% of length training. In this case, the better approach is HD, where the measures exhibit a minimum r equal to 0.942 and maximum 0.953, while the minimum and maximum MAE vary among 6.085 and 6.669. We show that the forecast of dengue cases is a challenging problem and climate variables do not always help. However, when we include the mentioned climate variables, the most important one is the humidity.
On Kodaira–Spencer’s problem on almost Hermitian 4-manifolds
Authors: Sillari Lorenzo , Tomassini Adriano
Published: June 2024

In 1954, Hirzebruch reported a problem posed by Kodaira and Spencer: on compact almost complex manifolds, is the dimension [Formula: see text] of the kernel of the Dolbeault Laplacian independent of the choice of almost Hermitian metric? In this paper, we review recent progresses on the original problem and we introduce a similar one: on compact almost complex manifolds, find a generalization of Bott–Chern and Aeppli numbers which is metric-independent. We find a solution to our problem valid on almost Kähler [Formula: see text]-manifolds.
Blanchfield pairings and Gordian distance
Authors: Friedl Stefan , Kitayama Takahiro , Suzuki Masaaki
Published: June 2024

A lower bound of the Gordian distance is presented in terms of the Blanchfield pairing. Our approach, in particular, allows us to show at least for [Formula: see text] pairs of unoriented nontrivial prime knots with up to [Formula: see text] crossings that their Gordian distance is equal to [Formula: see text], most of which are difficult to treat otherwise.
Fractal version of average Fermat distance on some small-world hierarchical networks
Authors: Peng Lulu , Chen Dirong , Zeng Cheng , Xue Yumei , He Huixia
Published: June 2024

Fermat–Wiener index based on topological Wiener index is the total sum of Fermat distance over all the triplets for vertices. In this paper, we construct a class of hierarchical graphs based on hierarchical product generalized from Cartesian product. We study some critical properties of the hierarchical networks by investigating its topological indices. Applying the finite pattern method, we analytically deduce the dominant term of average Fermat distance and obtain its asymptotic formula, which implies small-world property. We finally exhibit a close connection between Fermat–Wiener index and related graph invariants like average geodesic distance, Wiener index and eigenvalues of Laplacian matrix.
LABOR OUTSOURCING AND THE COST OF DEBT
Authors: WU YING
Published: June 2024

Using the Chinese A-share listed enterprises from 2015 to 2022, this paper investigates the impact of labor outsourcing on the cost of debt. I find that labor outsourcing reduces the cost of debt. The research conclusion is still valid after a series of robustness tests. In terms of economic significance, labor outsourcing reduces the cost of debt by 9.43%. The mechanism tests suggest that labor outsourcing can reduce the cost of debt by improving corporate performance and information transparency. Further analyses find that the relationship between labor outsourcing and the cost of debt is more prominent for non-state-owned enterprises and firms located in regions with lower banking competition. This paper is the first empirical study on the impact of labor outsourcing on the cost of debt, which has important theoretical and practical significance.
Heat engine efficiency for four-dimensional charged AdS black holes in Rastall gravity
Authors: Long Siying , Jian Siyu , Chen Juhua , Wang Yongjiu
Published: June 2024

In this paper, we analyze the [Formula: see text] criticality and the heat engine efficiency of two black holes, one is the four-dimensional charged AdS black hole in Rastall gravity and the other is the four-dimensional charged AdS black hole surrounded by quintessence in Rastall gravity. For the four-dimensional charged AdS black hole in Rastall gravity, the ratio [Formula: see text] is related to the Rastall parameter [Formula: see text]. When [Formula: see text] the ratio becomes [Formula: see text], which is same as the van der Waals liquid-gas system. Additionally, as the Rastall parameter [Formula: see text] increases, the heat engine efficiency [Formula: see text] of the black hole will increase. Moreover, the efficiency [Formula: see text] decreases rapidly at first and then increases with the entropy [Formula: see text]. But the efficiency ratio [Formula: see text] decreases with the Rastall parameter [Formula: see text]. For the four-dimensional charged AdS black hole surrounded by quintessence in Rastall gravity, as the charge q increases, the critical specific volume [Formula: see text] and the efficiency ratio [Formula: see text] also increase, however, the critical temperature [Formula: see text] and the critical pressure [Formula: see text] gradually decrease. Moreover, the heat engine efficiency [Formula: see text] and the efficiency ratio [Formula: see text] of the black hole are similar to the four-dimensional charged AdS black hole in Rastall gravity.
Dark energy as a geometrical effect in geodetic brane gravity
Authors: Rojas Efraín , Cruz G. , Natividad J. C.
Published: June 2024

Within the framework of the modified geodetic brane gravity, conformed by the Regge–Teitelboim model and enhanced with a linear term in the extrinsic curvature of the brane, the possibility that under an FRW geometry this theory emulates the so-called dark energy is discussed. The cosmological behavior of this model displays a self-(non-self)-accelerated expansion of this universe which is caused by a combination of usual matter and gravitational geometric effects controlled by a [Formula: see text] parameter that accompanies the correction K term. Indeed, the self-accelerated branch, provided by the trace K model raises the question of whether the extrinsic curvature correction terms might be suitable for dark energy candidates. We discuss the analytical expression obtained for [Formula: see text] in addition to the main cosmological parameters such as the state parameter [Formula: see text] and the deceleration parameter q. Moreover, when we call for the contribution of dark radiation-like energy to be switched off, [Formula: see text], we find the same acceleration behavior, as well as the same dark energy content provided by the DGP theory. The relationship of our findings to the analysis for [Formula: see text] performed by Davidson and Gurwich within the unified brane cosmology is briefly discussed.
IoT Computing Collaboration and Data-Aware Routing Algorithm for Edge Computing and DL
Authors: Li Bo , Tang JinHong , Yang Zhihe , Jiang Qing , Wei Jingyang
Published: June 2024

With the development of mobile edge computing and neural network Deep Learning (DL), more and more scholars are studying the combination of the two. This paper mainly studies the application of mobile edge computing and neural network DL in IoT computing collaboration and data-aware routing algorithms. Therefore, this paper proposes the deployment options of MEC technology and ETSIMEC in mobile edge computing, combining mobile edge computing with DL, designs an optimization algorithm based on Markov decision process and feature expression learning, and then analyzes and optimizes IoT computing and VANET routing algorithm. In order to have a clearer direction for the optimization algorithm, this paper also designs the edge computing model training and experiment comparison, the DL algorithm comparison experiment, and the routing algorithm simulation experiment and performance analysis. Combined with the experimental results, it is optimized and compared with traditional IoT computing and routing algorithms. Finally, it is concluded that the computing efficiency of IoT computing based on edge computing and DL designed in this paper is 21.33% higher than that of traditional IoT computing. The efficiency of the routing algorithm based on edge computing and DL designed in this paper is 9.29% higher than that of the traditional routing algorithm.
A Diffusion Neural Network-Enhanced Object Tracking Approach Under Sports Scenarios
Authors: Li Wen , Hu Yingyue , Liu Ruixiang , Shi Xiaofeng , Su Xuefeng
Published: June 2024

Object tracking for motion scenes is a common research concern in field of computer vision. Its goal is to accurately track targets in different time periods and predict their future states by utilizing the motion information in video sequences. However, traditional target-tracking methods in motion scenes often face challenges such as target blur, occlusion, and changes in lighting. To deal with this issue, this paper proposes a diffusion neural network-enhanced object-tracking approach under sports scenarios. In order to further improve tracking performance, the diffusion convolution operation is introduced, which propagates features at different time steps to enhance the modeling ability of target motion. Then, suitable influencing factors are selected based on motion scene object feature parameters. Finally, a target tracking method is established by integrating these two methods. In the experiment, we used a large number of real motion scene datasets to evaluate the proposed method. The experimental results show that by comparing with traditional moving object tracking methods, the proposal achieves significant improvement in tracking accuracy and methodology robustness. In addition, we also conducted stability experiments, proving that this method has good stability for models with varying kernel numbers.
A Low Power PLL with 1-V Supply Voltage and Two-Stage Ring Oscillator in 180-nm CMOS
Authors: Zeng Yejuan , Dai Yuehua
Published: June 2024

This paper proposes a low-power charge pump PLL (CPPLL) with 1-V supply voltage in 180-nm CMOS technology, which serves as a low-cost clock generator for heterogeneous integration. Tradeoffs between power consumption, jitter performance and limited loop bandwidth in the conventional CPPLL have been analyzed first, followed by the explanations on reference spur issues in wide bandwidth architectures. A novel two-stage ring oscillator with low voltage capability and linear control gain has been proposed and analyzed in detail, which facilitates the implementation of this 1-V design. Fabricated in SMIC 180-nm technology, the designed PLL occupies a die area of 0.177 mm2 with an integrated loop filter. The PLL draws 1.8 mA when working at 480 MHz, and shows a rms jitter of 7.2 pS, which is 20 times more power efficient compared with PLLs with similar frequency and technology node. The design shows potential for heterogeneous integration.
Resource Control in Active IRS-Aided 6G IoT Networks with Use Case in Smart Indoor Communication
Authors: Taneja Ashu , Rani Shalli , Shabaz Mohammad , Khan Muhammad Attique , Alzahrani Ahmed Ibrahim , Alalwan Nasser
Published: June 2024

The IoT ecosystem involves connected smart devices that support massive amount of data for processing and further analysis. The proliferating massive IoT network demands network connectivity, robust communication links and computational resources which puts huge load on the network. To overcome the communication overhead in the IoT landscape while offering optimal fault tolerance is the main challenge. This paper presents an intelligent solution for improving the communication efficiency of IoT network using active IRS technology. An active IRS aided communication framework is proposed which offers enhanced network connectivity by enabling controlled reflection amplitude. An algorithm is proposed which associates optimal active IRS to each AP-node link such that signal-to-interference-plus-noise ratio (SINR) is maximized. It is observed that the proposed association scheme in active IRS system offers an improvement of 19.04% in achievable rate over random association at AP transmit power [Formula: see text] of 20[Formula: see text]dBm and IRS amplification power [Formula: see text] of 4[Formula: see text]dBm. Furthermore, the system outage probability is carried out with change in [Formula: see text] and amplification gain [Formula: see text]. The mean channel power is also evaluated for different IRS densities and AP densities under different IRS reflecting elements [Formula: see text], [Formula: see text] and [Formula: see text]. In the end, the performance comparison with passive IRS system and system with no IRS assistance is carried out. A use case scenario of active IRS-aided system in smart indoor communication is also discussed.
Is the Page-time paradox paradoxical?
Authors: Costa Bruno Arderucio
Published: June 2024

I discuss how five reasonably sounding assumptions lead to a dilemma — the Page-time paradox — which appears to challenge a conventional statistical mechanical underpinning of black hole thermodynamics. By inspecting the conceptual subtleties behind each hypothesis, I list questions that require clarification before the puzzle can be deemed paradoxical. I devote particular attention to using thermodynamic arguments for a system that never reaches equilibrium. As a proof of concept, I show that the paradox is absent in a modified setting that admits an equilibrium thermodynamics formulation.
A symmetry-centric perspective on the geometry of the string landscape and the swampland
Authors: Rudelius Tom
Published: June 2024

As famously observed by Ooguri and Vafa nearly 20 years ago, scalar field moduli spaces in quantum gravity appear to exhibit various universal features. For instance, they seem to be infinite in diameter, have trivial fundamental group, and feature towers of massive particles that become light in their asymptotic limits. In this paper, we explain how these features can be reformulated in more modern language using generalized notions of global symmetries. Such symmetries are ubiquitous in nongravitational quantum field theories, but it is widely believed that they must be either gauged or broken in quantum gravity. In what follows, we will see that the observations of Ooguri and Vafa can be understood heuristically as consequences of such gauging or breaking.
Methods for Estimating Parameters of the Common Cause Failure Model Based on Data with Uncertainty
Authors: Nguyen Huu Du , Gouno Evans
Published: June 2024

In this paper, we propose a new method to deal with uncertain data in the context of Common Cause Failure (CCF) analysis. Uncertain CCF data refer to the data for which the number of components involved in the failure events is not exactly known. We introduce a new formalism to describe uncertain CCF data to avoid subjective probabilities for the number of failed components in each CCF event that are used in classical methods such as the impact vector method. The parameters of the [Formula: see text]-factor model are estimated using the maximum likelihood method relying on properties of the nested Dirichlet distribution and grouped Dirichlet distribution. A data augmentation technique with an expectation-maximization algorithm is also developed for some schemes of data with uncertainty. Finally, we evaluate the performance of the proposed method through numerical simulations and illustrate its application using an example from the literature.
BIOMEHANICAL AND POSTURAL EVALUATION OF OPTIMAL BIKE FIT FOR NON-TRAUMATIC INJURY PREVENTION AMONG CYCLISTS: A NARRATIVE REVIEW
Authors: Miraj Mohammad , Gupta Aparna , Kalra Sheetal , Khanna Archana , Ajmera Puneeta
Published: June 2024

This review article assesses the evidence for the efficacy of bike fit and its impact on cyclist’s posture in averting overuse injuries in cycling and provides a summary of research using a biomechanical approach to give evaluations of joint kinematics, kinetics, or muscle activity. Databases were searched for published material like Medline, Scopus, Web of Science, and Google Scholar between 1980 and 2023. Posture, bike fit, and biomechanics of cycling were few keywords used. Twenty-four published articles were included in this review. Clearance of 1–2 inches should be present between the ground and tyres when the bike is lifted while straddling it, for straight and parallel to ground top tubes and sloping top tubes, respectively. Handlebar height should be 1–2 inches below the top of the saddle. The reach of the handlebars should be measured by placing an elbow on the tip of saddle and extended fingers should touch the transverse part of the handlebars. The ball of foot should sit over the pedal axis. In cyclist’s seated position, the knee flexion angle of the extended leg at 6 o’clock position should be 25–30°. With pedals at 3 and 9 o’clock, the front of the patella should be directly in line with the front of the crank arm. About 10 to 15° anterior saddle tilt significantly reduces low back discomfort.
A Novel Weak-Form Plane Frame Quadrature Element and its Application to Bridge Analysis
Authors: Wang Kai , Feng Chuang , Zhou Ding
Published: June 2024

A novel weak-form plane frame quadrature element (WPFQE) is developed. A complex structure can be divided into several non-homogeneous (or homogeneous) elements with large size. The Chebyshev–Lobatto differential quadrature dealing with differentiation and the Gauss–Lobatto quadrature dealing with integration have the same integration points including the ends of each element. Based on the energy variational principle, the diagonal mass matrix and positive definite real symmetric stiffness matrix for the element can be obtained. The unknown quantities at the internal quadrature points of the element can be represented by those at the endpoints of the element based on the principle of static equal effect anterior to the development of global matrices, which significantly reduces the sizes of modified element matrices while maintaining sufficient accuracy, thereby obtaining the small-sized global matrices. Assembly of elements can be performed efficiently just as that in the finite element (FE) method. In the case study, the static and dynamic performances of a three-span high-pier rigid-frame bridge with variable cross-section are studied by applying the proposed method. The results indicate that the orders of structural matrices and calculation time obtained by the WPFQE method are much smaller than those of the FE method.
Group gradings on the filiform Lie superalgebras Lm,n
Authors: Xie Wenjuan , Liu Wende
Published: June 2024

In this paper, we classify the gradings up to equivalence on the filiform Lie superalgebras [Formula: see text] over an algebraically closed field of characteristic 0. Moreover, by the relation between a grading and a standard grading, we describe all pairwise inequivalent gradings and their universal groups of [Formula: see text].
Cohomology of the Lie conformal algebra 𝒲(a,b)
Authors: Wang Jinrong , Yue Xiaoqing
Published: June 2024

The Lie conformal algebra [Formula: see text] with two parameters [Formula: see text] is a free [Formula: see text]-module generated by [Formula: see text] and [Formula: see text] satisfying [Formula: see text] and [Formula: see text], which is the semi-direct sums of Virasoro Lie conformal algebra and its nontrivial conformal modules of rank one. In this paper, we determine the basic and reduced cohomology groups of [Formula: see text] for the case of [Formula: see text] with coefficients in its module. In particular, the low-dimensional basic cohomology groups with trivial coefficients are completely determined.
Low-Temperature Synthesis of CuO:ZnO Nanocomposite Catalyst
Authors: Thien Trinh Duc , Thanh Hoang Van , Cham Le T. M. , Phong Kieu Xuan , Nam Dinh Hoai , Tuan Nguyen Huu , Tuan Duong Anh , Duong Pham Van , Minh Pham Hong , Lam Nguyen Dinh
Published: June 2024

CuO:ZnO nanocomposite photocatalyst with tunable ratios of CuO was synthesized using a low-temperature-assisted co-precipitation method, which is suitable for industrial-scale production. Analytical techniques, including XRD, FE-SEM, HR-TEM, FTIR, XPS and UV–Vis, were utilized to investigate the structure, morphological characteristics, chemical composition and optical properties of the CuO:ZnO nanocomposite. The XRD analysis reveals that the samples exhibit a single phase, characterized by a wurtzite hexagonal structure of ZnO and a monoclinic structure of CuO. The average crystal size changed from [Formula: see text][Formula: see text]nm to [Formula: see text][Formula: see text]nm when CuO varied from 0% to 5% in the CuO:ZnO nanocomposite. The scanning electron microscope (SEM) images reveal that the nanocomposite particles exhibit a high degree of uniformity, with an average size of approximately 50[Formula: see text]nm. HR-TEM shows the width of lattice plane families consistent with X-ray diffraction for CuO and ZnO materials. The ZnO exhibits a unique hexagonal shape. Furthermore, there is a slight correlation between the CuO fraction and an increase in grain size. FTIR analysis revealed the specific vibrational modes of ZnO and CuO at wavenumbers of 564, 619, 651, 673 and 488, 607[Formula: see text][Formula: see text], respectively. XPS shows secondary valences of Cu and Zn indicating the formation of CuO and ZnO while the high Ov peak indicates the presence of Oxygen defects in the crystal lattice. The absorption results clearly demonstrate the presence of two absorption edges corresponding to ZnO and CuO, as well as the broadening of the absorption spectrum of the nanocomposite sample up to a wavelength of 840[Formula: see text]nm. The photocatalytic degradation of RhB yielded remarkable outcomes, as the concentration of RhB declined by 98.6% after 20[Formula: see text]min of illumination using a CuO:ZnO (3:97) nanocomposite. The photocatalytic efficiency is significantly influenced by changing the CuO ratio in CuO:ZnO nanocomposites. This can be attributed to the tradeoff between the effectiveness of the heterogeneous contact layer and the limited ability of CuO to catalyze photochemical reactions. Based on the scavenger test, hydroxyl and superoxide radicals are primarily responsible for the decolorization of RhB dye. Results of evaluating the reusability and stability of the material show that, after fifth recycling, the decomposition efficiency still reaches over 90% after 30[Formula: see text]min of illumination.
Using Machine Learning Techniques to Predict the Surface Roughness of Titanium Alloys
Authors: Salem Hossam Eldin
Published: June 2024

Production engineering focuses on designing, optimizing, and managing manufacturing processes to produce goods efficiently. Turning is a machining process where a cutting tool removes material from a rotating workpiece to create cylindrical shapes. Key parameters include cutting speed, feed rate, and depth of cut. Surface roughness is a key challenge in turning, impacting product quality. Achieving the desired finish is crucial for tight tolerance and performance. Engineers use optimization techniques to minimize roughness. Advancements in tool materials and technology help address roughness challenges for improved efficiency in turning. Predictive models for surface roughness are vital for optimizing machining processes, ensuring quality, and enhancing performance. They guide decision-making, improve efficiency, and drive innovation in manufacturing. In this paper, 25 machine learning models have been used and optimized to accurately predict the surface roughness of the turning process of five previous studies on Titanium alloy. Resulting in the best performance with the lowest MSE was for the artificial neural network with 3 hidden layers: the first has 5 neurons, the second has 10 neurons and the last one has 5 neurons. The MSEs are 0.053072, 0.555763, 0.059667, 0.051867, and 0.554829 for the five studies, respectively.
Information consistency of dependent convolved Gaussian processes regression
Authors: Cui Wenquan , Li Jianbo , Xu Jianjun
Published: June 2024

This paper presents a non-parametric Bayesian approach for modeling multiple response variables using a Gaussian process regression (GPR) model. The response functions are modeled using a dependent Gaussian process (GP) prior, and the estimation, prediction, and inference issues are discussed within this framework. To establish the information consistency of the dependent GPs prediction strategy, a stretching-restriction method is proposed. The covariance structure is constructed using convolved Gaussian processes (CGPs) to illustrate the results. Simulations and real data analyses show that the proposed dependent GPR yields reasonably good prediction accuracy.
Preparation of fidelity-robust quantum entanglement with error-detected blocks based on quantum-dot spins inside optical microcavities
Authors: Chen Shu-Yang , Fan He-Qiang , Fan Ling , Cao Cong
Published: June 2024

Effective schemes are proposed for the generation of bipartite Bell states and theoretically scaling up to arbitrary multiparticle Greenberger–Horne–Zeilinger, cluster, and W states among quantum-dot (QD) spins. They are realized based on the interaction between an single incident photon and single QD spin. Errors from system nonuniformity and defective photon scattering are transformed into detectable photon losses. In the event of a failed experiment, the system allows for the reinjection of a single photon and the reinitiation of the quantum circuit, until a successful outcome is achieved. This loss-prediction and experiment-repeatability approach ensures that the schemes are implemented with uniform and robust fidelity. Compared with the previous methods, these schemes significantly simplify experimental procedures and analysis processes. Furthermore, upon successful execution of the experiment, the use of single-photon detector can faithfully differentiate between various types of entangled states, depending on the initial states of the QD spins. An analysis of the feasibility of the schemes under current experimental parameters suggests high efficiency even in the weak coupling region.
Numerical Calculation of Three-Dimensional MHD Natural Convection Based on Spectral Collocation Method and Artificial Compressibility Method
Authors: Chang Jiapeng , Zhang Jingkui , Fan Yi , Li Qifen , Zhang Jiakai , Peng Cheng
Published: June 2024

The flow and heat transfer characteristics in a three-dimensional cavity filled with a conducting fluid are investigated in this study in the presence of a constant magnetic field. The three-dimensional Navier–Stokes equations and energy equation are solved directly using a self-developed method, SCM–ACM, which combines the spectral collocation method (SCM) with high-precision and exponential convergence, and the artificial compressibility method (ACM) with easy implementation and good numerical stability. In this paper, we examine the effects of Hartmann numbers (Ha) ranging from 0 to 100, magnetic field directions, and Grashof numbers (Gr) ranging from [Formula: see text] to [Formula: see text] on the structure of the flow and temperature fields, with a Prandtl number (Pr) of 0.71. The results show the Grashof and Hartmann numbers have a significant impact on the flow and temperature distribution in the middle of the cavity, but little effect on that near the walls. As the Grashof number increases, a stable thermal stratification is formed at the center of the cube, and thermal boundary layers are formed near the horizontal walls. The increase in Grashof number enhances the heat transfer rate and increases the temperature difference between the upper hot fluid and the lower cold fluid in the cube. Furthermore, the increase in Grashof number enhances the convective intensity between the isothermal walls, leading to the formation of more vortices, which move toward the corners due to the combined action of centrifugal force and inertia. The Hartmann number has stabilizing effects on the flow and weakens the heat transfer. With a higher Grashof number the magnetic effects become more notable. When [Formula: see text], the magnetic effects are no longer significant. The magnetic field [Formula: see text] perpendicular to the main circulation plane exhibits the strongest stability for the flow.
Innovative Skin Structures: Synthesis, Void Analysis, and Hysteresis Modeling of Zero Poisson’s Ratio Skin for Span Morphing Wing
Authors: Ahmad Dilshad , Gour Sankalp , Kumar Deepak , Ajaj Rafic M. , Zweiri Yahya
Published: June 2024

This paper explores the use of carbon fiber-reinforced elastomeric skins for advancing flexible morphing wing technologies, highlighting exceptional 1D morphing capabilities. The study focuses on synthesizing a specially engineered elastomer-based skin with a zero Poisson’s ratio, achieved through precise formulation and fabrication onto unidirectional carbon fiber. Poisson’s ratio of the 1D skin is confirmed to be zero via image analysis. Micro-CT tomography evaluates carbon fiber quality and voids under varied prestretch conditions, revealing proportional increases in void sizes. X-ray tomography also provides insights into void distribution and morphology during pre- and post-cyclic stretching. The innovative approach enables seamless 1D morphing, achieving an impressive 200% stretch with a slight increase in actuation force and hysteresis loss percentage. Inspired by continuum mechanics, the proposed “Exp-ln-ln” framework accurately models the loading–unloading stretching of the skin. An extensive parametric investigation assesses key parameters, advancing fiber-reinforced elastomeric materials for aerospace morphing skins.
Optimum Solar Cell Power Conversion Efficiency-Based Patterned Planar Solar Surface Morphology with Various Solar Cell Absorber Structures
Authors: Rashed A. N. Z. , Eid Mahmoud M. A. , Ahammad S. H.
Published: June 2024

This paper simulated the optimum solar cell power conversion efficiency-based planar solar surface morphology with various solar cell absorber structures. The spectral light intensity, reflected, absorbed, and transmission coefficients versus wavelength band spectrum varied from 300[Formula: see text]nm to 1300[Formula: see text]nm through the visible to near-infrared regions. The optimum solar cell performance parameters or key parameters are studied with different solar cell structure designs based on different surface contact and back contact layers. Cumulative generation current, cumulative electron–hole pair generation rate and electron–hole pair generation rate are clarified versus substrate depth for various solar cell structure designs. The absorbed current in substrate is optimized for various solar cell structure designs. Maximum power voltage and current are also optimized for the proposed solar cell structure design. The effective solar cell power efficiency is also demonstrated based on the optimized maximum power current and maximum power voltage.
Three-Dimensional Finite Element Analysis of Cement-Cup Junction in Total Hip Prosthesis: Mechanical Stress Distribution, Crack Initiation and Rupture Dynamics
Authors: Bounoua Noureddine , Belhouari Mohamed , Menni Younes , Alkhafaji Mohammed Ayad , Bayram Mustafa , Ikumapayi Omolayo M. , Chamkha Ali J.
Published: June 2024

Understanding the mechanical and rupture behavior of orthopedic cement fixing the cup of a total hip prosthesis (THP) to cortical bone is crucial for comprehending the conditions governing prosthesis stability and potential loosening. Consequently, this study employs a three-dimensional finite element method to investigate the mechanical behavior of cement with interfacial cracks at the junction between the cement and cup. Through stress distribution analysis, we identify the initiation points of cracks and examine how stress intensity factors (SIFs) vary across three modes of failure (I, II and III) throughout a walking cycle, particularly concerning the femoral head. Our findings reveal that loading stages cause stable variations in SIFs along the crack front, with the highest values consistently at the second end of the crack. Moreover, the propagation mechanism of interfacial cracks is complex, oscillating between modes of opening and plane shear, linked to the SIFs of modes I and II and the material properties of the cement and cup. Furthermore, mode III behavior mirrors that of mode II, with nearly linear increases in SIFs along the crack front, peaking near the crack’s terminus. Overall, mode III (out-of-plane shear) emerges as the primary fracture mode, indicating a risk of damage to the reconstructed acetabulum from fatigue, despite the SIF values being lower than the fracture toughness of both the cup and the cement.
Preparation of Nanosized Copper–Manganese Composite Oxides and Their Catalytic Performance in the Oxidation of Toluene
Authors: Zhang Nan , Dong Changqing , Yao Haizhou , Cai Youlin , Wu Baogang , Cheng Junfeng
Published: June 2024

Nanosized Cu–Mn composite oxide catalysts were prepared from potassium permanganate, copper nitrate, n-butanol, and cetyltrimethylammonium bromide as a manganese source, copper source, reducing agent, and surfactant, respectively. The Cu[Formula: see text]–Mn sample possessed a small particle size (10–40[Formula: see text]nm) and a relatively high specific surface area ([Formula: see text]); its main components were Cu[Formula: see text]Mn[Formula: see text]O4 and Mn3O4. As a consequence, the Cu[Formula: see text]–Mn catalyst exhibited good catalytic activity in the oxidation of toluene. At a toluene concentration of 1000[Formula: see text]ppm and a space velocity of [Formula: see text], the [Formula: see text] and [Formula: see text] of the Cu[Formula: see text]–Mn catalyst toward toluene were 239[Formula: see text]C and 250[Formula: see text]C, respectively. Furthermore, even after 30[Formula: see text]h of operation at 275[Formula: see text]C, the conversion of toluene was 99% (at the space velocity of [Formula: see text]).
Some results for the incomplete Lauricella matrix functions of many variables
Authors: Verma Ashish , Yadav Komal Singh , Sharan Bhagwat
Published: June 2024

In this paper, we apply the incomplete Pochhammer matrix symbols to introduce incomplete Lauricella matrix functions (ILMFs) of [Formula: see text] variables. Additionally, the integral formula, recursion formula, differentiation formula, and matrix differential equation of ILMFs are all derivations of specific attributes. In addition, we demonstrate a connection between these matrix functions and other matrix functions, such as the incomplete gamma matrix function, the Laguerre, the Bessel, and the modified Bessel matrix functions.
The distribution of polynomials in monotone-independent elements
Authors: Banna Marwa , Tseng Pei-Lun
Published: June 2024

Building on the work of Arizmendi and Celestino (2021), we derive the ∗-distributions of polynomials in monotone independent and infinitesimally monotone independent elements. For non-zero complex numbers [Formula: see text] and [Formula: see text], we derive explicitly the ∗-distribution of [Formula: see text] whenever [Formula: see text] and [Formula: see text] are monotone or infinitesimally monotone independent elements. This encompasses both cases of the commutator and anti-commutator. This approach can be pushed to study more general polynomials. As applications, we derive the limiting distribution with respect to the partial trace of polynomials in a certain class of random matrices.
Statistical inference on kurtosis of independent component model
Authors: Zhou Bowen , Chen Hantao , Wang Cheng
Published: June 2024

Independent component model (ICM) is a widely-used population distribution in high-dimensional data analysis and random matrix theory. In this work, we study the kurtosis of the ICM, which is an important parameter in asymptotic distributions of many commonly used statistics and is also an important criterion for measuring the heavy-tailed nature of the data. Based on U-statistics, we develop an estimation method. Theoretically, we show that the proposed estimator is consistent under regular conditions, especially we relax the restriction that the data dimension and the sample size are of the same order. Furthermore, we derive the asymptotic normality of the estimator, which allows us to construct confidence intervals and hypothesis testing statistics. Computationally, we provide a fast and efficient algorithm by leveraging the matrix structure, where the computational complexity is essentially equivalent to computing the sample covariance matrix and the Gram matrix. Finally, the effectiveness of the proposed method is demonstrated through simulated data and real-world data.
Monocular Vision Sensor-Based Indoor Road and Stair Detection
Authors: Liu Pengzhan , Jin Wei , An Chunhua , Zhao Jianqiang
Published: June 2024

Road detection is an essential component of indoor robot navigation. Vision sensors have great advantages in road detection as they can provide rich information in terms of environmental perception. In this paper, a monocular vision sensor-based method for indoor road and stair detection is proposed, which detects feasible areas in indoor environments very fast without paying attention to detailed features of walls or other obstacles. More specifically, for a given indoor road image captured by an on-board vision sensor, the simple linear iterative clustering (SLIC) algorithm-based approach for efficient image segmentation is introduced. Then, according to the DBSCAN algorithm, the generated superpixels are clustered to form large areas of view. The initial road area is obtained through a safe window on the middle bottom of the image. In order to achieve a more accurate road segmentation, the initial image is processed by the binary search, edge detection based on the Canny operator and straight-line detection and location based on the Hough transform, which integrates edge and stair information into road detection. Several experiments are performed to evaluate the performance of the proposed method. The experimental results demonstrate that the proposed method could accurately detect road information and staircase information in images and succeeds in addressing the indoor road-detection problem.