bluuebunny/crossref_metadata_2025_split huggingface dataset:
Double-diffusive peristaltic MHD Sisko nanofluid flow through a porous medium in presence of non-linear thermal radiation, heat generation/absorption, and Joule heating
Authors: Abo-Dahab Sayed M. , Mohamed Ramadan A. , Abd-Alla Abdelmoaty M. , Soliman Mahmoud S. 
Published: January 2023

AbstractThis article studied a numerical estimation of the double-diffusive peristaltic flow of a non-Newtonian Sisko nanofluid through a porous medium inside a horizontal symmetric flexible channel under the impact of Joule heating, nonlinear thermal radiation, viscous dissipation, and heat generation/absorption in presence of heat and mass convection, considering effects of the Brownian motion and the thermophoresis coefficients. On the other hand, the long wave approximation was used to transform the nonlinear system of partial differential equations into a nonlinear system of ordinary differential equations which were later solved numerically using the fourth-order Runge–Kutta method with shooting technique using MATLAB package program code. The effects of all physical parameters resulting from this study on the distributions of velocity, temperature, solutal concentration, and nanoparticles volume fraction inside the fluid were studied in addition to a study of the pressure gradients using the 2D and 3D graphs that were made for studying the impact of some parameters on the behavior of the streamlines graphically within the channel with a mention of their physical meaning. Finally, some of the results of this study showed that the effect of Darcy number $$Da$$

Da

and the magnetic field parameter $$M$$
M
is opposite to the effect of the rotation parameter $$\Omega$$
Ω
on the velocity distribution whereas, the two parameters nonlinear thermal radiation $$R$$
R
and the ratio temperature $${\theta }_{w}$$

θ
w

works on a decrease in the temperature distribution and an increase in both the solutal concentration distribution, and the nanoparticle's volume fraction. Finally, the impact of the rotation parameter $$\Omega$$
Ω
on the distribution of pressure gradients was positive, but the effect of both Darcy number $$Da$$

Da

and the magnetic field parameter $$M$$
M
on the same distribution was negative. The results obtained have been compared with the previous results obtained that agreement if the new parameters were neglected and indicate the phenomenon's importance in diverse fields.
Genomic and epigenomic variation in Psidium species and their outcome under the yield and composition of essential oils
Authors: Silva Matheus Alves , Soares Fernanda Aparecida Ferrari , Clarindo Wellington Ronildo , Mendes Luiza Alves , Alves Luziane Brandão , Ferreira Adésio , da Silva Ferreira Marcia Flores 
Published: January 2023

AbstractDiploid and polyploid species derived from the euploid series x = 11 occur in the genus Psidium, as well as intraspecific cytotypes. Euploidy in the genus can alter the gene copy number, resulting in several “omics” variations. We revisited the euploidy, reported genomic (nuclear 2C value, GC%, and copy number of secondary metabolism genes) and epigenomic (5-mC%) differences in Psidium, and related them to essential oil yield and composition. Mean 2C values ranged from 0.90 pg (P. guajava) to 7.40 pg (P. gaudichaudianum). 2C value is intraspecifically varied in P. cattleyanum and P. gaudichaudianum, evidencing cytotypes that can be formed from euploid (non-reduced) and/or aneuploid reproductive cells. GC% ranged from 34.33% (P. guineense) to 48.95% (P. myrtoides), and intraspecific variations occurred even for species without 2C value intraspecific variation. Essential oil yield increased in relation to 2C value and to GC%. We showed that P. guajava (diploid) possesses two and P. guineense (tetraploid) four copies of the one specific TPS gene, as well as eight and sixteen copies respectively of the conserved regions that occur in eight TPS genes. We provide a wide “omics'' characterization of Psidium and show the outcome of the genome and epigenome variation in secondary metabolism.
Strain accumulation and release associated with the occurrence of SSEs in the subduction zones of the Japanese Islands
Authors: Kawabata Hiroki , Yoshioka Shoichi 
Published: January 2023

AbstractWe investigated the spatiotemporal changes in strain associated with the occurrence of slow slip events (SSEs) in the subduction zones of the Japanese Islands and compared the spatial distribution of both the amount of strain accumulated for the period before and during the SSEs release using time series data from the Global Navigation Satellite System (GNSS). In this study, four SSEs were analysed: the Tokai long-term SSE (2000–2005), the Boso-Oki short-term SSE (2007), and the Bungo Channel long-term SSEs (2009–2011 and 2018–2019). As a result, we found strong negative correlations for all four dilatations before and during SSE occurrence. For these dilatations, we estimated the amount of strain released at the time of occurrence of the SSE relative to that accumulated during the period prior to the SSE. The result indicates that not all the accumulated strain before the SSEs was released when the SSEs occurred. Moreover, it is highly likely that the strain released by SSE is not only due to the strain accumulation just below the SSE occurrence region, but also due to the strain accumulation on the shallower plate boundary, which is a seismogenic zone for a future megathrust earthquake.
Activation of L-lactate oxidase by the formation of enzyme assemblies through liquid–liquid phase separation
Authors: Ura Tomoto , Kagawa Ako , Sakakibara Nanako , Yagi Hiromasa , Tochio Naoya , Kigawa Takanori , Shiraki Kentaro , Mikawa Tsutomu 
Published: January 2023

AbstractThe assembly state of enzymes is gaining interest as a mechanism for regulating the function of enzymes in living cells. One of the current topics in enzymology is the relationship between enzyme activity and the assembly state due to liquid–liquid phase separation. In this study, we demonstrated enzyme activation via the formation of enzyme assemblies using L-lactate oxidase (LOX). LOX formed hundreds of nanometer-scale assemblies with poly-L-lysine (PLL). In the presence of ammonium sulfate, the LOX-PLL clusters formed micrometer-scale liquid droplets. The enzyme activities of LOX in clusters and droplets were one order of magnitude higher than those in the dispersed state, owing to a decrease inKMand an increase inkcat. Moreover, the clusters exhibited a higher activation effect than the droplets. In addition, the conformation of LOX changed in the clusters, resulting in increased enzyme activation. Understanding enzyme activation and assembly states provides important information regarding enzyme function in living cells, in addition to biotechnology applications.
Household energy-saving behavior, its consumption, and life satisfaction in 37 countries
Authors: Piao Xiangdan , Managi Shunsuke 
Published: January 2023

AbstractSince energy consumption became an important contributor to climate change owing to carbon emissions, energy-saving behavior and expenditure at the household level have been attracting scholars’ and policymakers’ attention. This study identified whether greenhouse gas emissions at the household level can be reduced through purchase of energy-saving goods and whether the energy-saving behavior enhanced with household income increase. We conducted a large-scale survey across 37 nations using internet-based and face-to-face approaches, collecting 100,956 observations. The wealth effect on energy consumption expenditure at the household level was found to be positive across countries, confirming that energy consumption increases with household wealth improvement. Furthermore, households show a positive association between household energy expenditure and life satisfaction in 27 out of 37 countries, including China, India, the United States, and Germany. Additionally, the favorable effects of household energy-saving behavior are confirmed. However, purchase of household energy-saving products has a limited effect on energy consumption expenditure, compared with that of energy-curtailment behavior. In conclusion, achieving a carbon–neutral household by reducing energy consumption expenditure at the household level is challenging; thus, along with the use of energy-saving goods, alternative energy sources, such as renewable energies, are recommended.
A macro to micro analysis to understand performance in 100-mile ultra-marathons worldwide
Authors: Thuany Mabliny , Weiss Katja , Villiger Elias , Scheer Volker , Ouerghi Nejmeddine , Gomes Thayse Natacha , Knechtle Beat 
Published: January 2023

AbstractThe purposes of this study were (i) to describe differences in participation in 100-mile ultra-marathons by continent; (ii) to investigate differences in performance between continents; and (iii) to identify the fastest runners by continent and country. Data from 148,169 athletes (119,408 men), aged 18–81 years, and finishers in a 100-miles ultra-marathon during 1870–2020 were investigated. Information about age, gender, origin, performance level (top three, top 10, top 100) was obtained. Kruskal–Wallis tests and linear regressions were performed. Athletes were mostly from America and Europe. A macro-analysis showed that the fastest men runners were from Africa, while the fastest women runners were from Europe and Africa. Women from Sweden, Hungary and Russia presented the best performances in the top three, top 10 and top 100. Men from Brazil, Russia and Lithuania were the fastest. The lowest performance and participation were observed for runners from Asia. In summary, in 100-miles ultra-marathon running, the majority of athletes were from America, but for both sexes and performance levels, the fastest runners were from Africa. On a country level, the fastest women were from Sweden, Hungary and Russia, while the fastest men were from Brazil, Russia and Lithuania.
Fracture analysis-based mode-I stress intensity factors of crack under fracture grouting in elastic–plastic soils
Authors: Li Long , Deng Yousheng 
Published: January 2023

AbstractFor the interaction of crack on the soil–grout interface under fracture grouting, an approximate method to determine the stress intensity factor (SIF) of crack on the soil–grout interface was proposed based on the conservation J2-integral. With this method, the energy release rate of crack propagation under fracture grouting can be defined by the parameters of elastic–plastic soils and the grouting pressure. In order to study the change of strain energy near the crack of elastic–plastic soil under fracture grouting, a mechanical model of elastic–plastic soil with crack was established based on non-associated Mohr–Coulomb criterion model, and the SIF of crack with spring boundary was investigated. The influence of the crack depth ratio and crack aspect ratio on the SIF of cracks under the spring boundary were analyzed, and revealed the rule of crack growth under fracture grouting in elastic–plastic soils. The results showed that the variation of the crack depth ratio and crack aspect ratio had an effect on the change of the SIF of cracks. Increasing the crack depth ratio and crack aspect ratio caused an increase in the SIF of the crack. The results can provide the reference for foundation reinforcement in elastic–plastic soils.
A deep convolutional neural network for diabetic retinopathy detection via mining local and long‐range dependence
Authors: Luo Xiaoling , Wang Wei , Xu Yong , Lai Zhihui , Jin Xiaopeng , Zhang Bob , Zhang David 
Published: January 2023

AbstractDiabetic retinopathy (DR), the main cause of irreversible blindness, is one of the most common complications of diabetes. At present, deep convolutional neural networks have achieved promising performance in automatic DR detection tasks. The convolution operation of methods is a local cross‐correlation operation, whose receptive field determines the size of the local neighbourhood for processing. However, for retinal fundus photographs, there is not only the local information but also long‐distance dependence between the lesion features (e.g. hemorrhages and exudates) scattered throughout the whole image. The proposed method incorporates correlations between long‐range patches into the deep learning framework to improve DR detection. Patch‐wise relationships are used to enhance the local patch features since lesions of DR usually appear as plaques. The Long‐Range unit in the proposed network with a residual structure can be flexibly embedded into other trained networks. Extensive experimental results demonstrate that the proposed approach can achieve higher accuracy than existing state‐of‐the‐art models on Messidor and EyePACS datasets.
Feature selection: Key to enhance node classification with graph neural networks
Authors: Maurya Sunil Kumar , Liu Xin , Murata Tsuyoshi 
Published: January 2023

AbstractGraphs help to define the relationships between entities in the data. These relationships, represented by edges, often provide additional context information which can be utilised to discover patterns in the data. Graph Neural Networks (GNNs) employ the inductive bias of the graph structure to learn and predict on various tasks. The primary operation of graph neural networks is the feature aggregation step performed over neighbours of the node based on the structure of the graph. In addition to its own features, for each hop, the node gets additional combined features from its neighbours. These aggregated features help define the similarity or dissimilarity of the nodes with respect to the labels and are useful for tasks like node classification. However, in real‐world data, features of neighbours at different hops may not correlate with the node's features. Thus, any indiscriminate feature aggregation by GNN might cause the addition of noisy features leading to degradation in model's performance. In this work, we show that selective aggregation of node features from various hops leads to better performance than default aggregation on the node classification task. Furthermore, we propose a Dual‐Net GNN architecture with a classifier model and a selector model. The classifier model trains over a subset of input node features to predict node labels while the selector model learns to provide optimal input subset to the classifier for the best performance. These two models are trained jointly to learn the best subset of features that give higher accuracy in node label predictions. With extensive experiments, we show that our proposed model outperforms both feature selection methods and state‐of‐the‐art GNN models with remarkable improvements up to 27.8%.
Deep transformer and few‐shot learning for hyperspectral image classification
Authors: Ran Qiong , Zhou Yonghao , Hong Danfeng , Bi Meiqiao , Ni Li , Li Xuan , Ahmad Muhammad 
Published: January 2023

AbstractRecently, deep learning has achieved considerable results in the hyperspectral image (HSI) classification. However, most available deep networks require ample and authentic samples to better train the models, which is expensive and inefficient in practical tasks. Existing few‐shot learning (FSL) methods generally ignore the potential relationships between non‐local spatial samples that would better represent the underlying features of HSI. To solve the above issues, a novel deep transformer and few‐shot learning (DT‐FSL) classification framework is proposed, attempting to realize fine‐grained classification of HSI with only a few‐shot instances. Specifically, the spatial attention and spectral query modules are introduced to overcome the constraint of the convolution kernel and consider the information between long‐distance location (non‐local) samples to reduce the uncertainty of classes. Next, the network is trained with episodes and task‐based learning strategies to learn a metric space, which can continuously enhance its modelling capability. Furthermore, the developed approach combines the advantages of domain adaptation to reduce the variation in inter‐domain distribution and realize distribution alignment. On three publicly available HSI data, extensive experiments have indicated that the proposed DT‐FSL yields better results concerning state‐of‐the‐art algorithms.
Power allocation for offset spatial modulation
Authors: Zhang Lechen , Lei Xia , Xiao Yue , Li You 
Published: January 2023

AbstractOffset spatial modulation (OSM) is an attractive variant in the family of spatial modulation technology, which is capable of reducing the frequency of radio frequency chain switching in practical implementations. This paper elaborates on the benefits of adaptive power allocation (PA) conceived for OSM systems. First, a closed‐form solution of the optimal PA algorithm is derived for the case of two transmit antennas, which maximizes the minimum Euclidean distance (ED) between the received signal points. Moreover, based on the above solutions, a low‐complexity iterative PA algorithm is proposed for larger numbers of transmit antennas, by exploiting the EDs of a few dominant error vectors. Furthermore, for striking a flexible trade‐off between the bit error performance and complexity, an iterative convex approximation based PA algorithm is also developed. Finally, simulation results are presented to show that the proposed PA algorithms provide considerable improvements on the original OSM in terms of the bit error rate.
Semi‐dynamic Markov approximation‐based base station sleep with user association for heterogeneous networks
Authors: Li Xiaohui , Zhang Chenghong 
Published: January 2023

AbstractEnergy efficiency (EE) in the communication industry is the general trend of green communication development, and the base station sleep (BSS) strategy is crucial to improving EE. However, how to maximize the cell's EE and optimize the performance of users in the sleeping area after the BSS is a challenging problem. The sub‐6GHz and millimeter‐wave (mmWave) integrated networks are considered in this paper. The users’ backhaul of the cell is jointly provided by the sub‐6 GHz band and the mmWave band. User reaccess algorithm based on multiple parameters access criterion is adopted when their severed base stations (BSs) are shut down. The authors also consider a resource allocation algorithm based on the semi‐dynamic Markov approximation (MA) algorithm, which is proposed to quickly allocate sub‐channels to reaccessed users and ensure the maximum throughput. The simulation results show that the proposed algorithm can improve the EE of the heterogeneous network and promptly meet the users’ needs when some BSs are shut down.
A distributed parallel optimization algorithm via alternating direction method of multipliers
Authors: Liu Ziye , Guo Fanghong , Wang Wei , Wu Xiaoqun 
Published: January 2023

AbstractAlternating direction method of multipliers (ADMM) has been widely used for solving the distributed optimisation problems. This paper proposes a novel distributed ADMM algorithm to solve the distributed optimisation problems consisting of convex cost functions under an undirected connected graph. The proposed algorithm adopts the concepts of predecessors and successors in the distributed sequential ADMM algorithm, but changes the sequential updating manner to a parallel one, which allows the agents to update their local states and dual variables in a completely distributed and parallel manner. This brings some benefits when solving large‐scale optimisation problems. Variational inequality is applied to analyse the convergence of agents' states. It is proved that the states of all the agents converge to the optimal point, and the global cost function converge to the optimal value at a rate of . Numerical experiments are given to show the effectiveness and suitability of the proposed algorithm.
Synthesis of a polarisation‐rotating surface with reflective filtering response based on orthogonally inserted coupled slot‐lines
Authors: Wei Tao , Li Bo , Zhu Lei , Cheng Chong‐Hu 
Published: January 2023

AbstractIn this article, a three‐dimensional polarisation‐rotation surface (PRS) with reflective filtering response based on two orthogonally inserted coupled slot‐line is investigated, which can reflect a vertically/horizontally polarised incident wave by 90°. Each unit cell of the PRS is composed of a pair of meandered slot‐line sections with open‐short‐ends etched on the vertically and horizontally inserted single‐layer printed circuit boards. Under the incidence of a linearly polarised plane wave along the vertical/horizontal direction, the plane wave is converted into the guided wave by the open‐circuited end of the slot‐line section, and then the guided wave is obstructed by the short end of the slot‐line section and coupled to the other slot‐line section, thus leading to 90° polarisation rotation. To simplify the design procedure, a matrix coupling theory is applied to synthesise and design the proposed PRS. A sample with fractional bandwidth of 20% at the centre frequency of 5 GHz and return loss of 20 dB is designed, fabricated, and measured for verification. The measured and simulated results are in good agreement with the theoretical ones. The results confirm that the proposed PRS has low insertion loss, high polarisation conversion ratio, and stable filtering performance for oblique incident angle up to 60°.
A novel high‐efficient step‐up converter with continuous input current, common ground, and minimum stress on semiconductors
Authors: Asgarnia Reza , Afjei Ebrahim 
Published: January 2023

AbstractThis study proposes a comprehensive analysis of a novel non‐isolated step‐up converter with continuous input current and common ground. The proposed topology provides high voltage gain besides insignificant voltage and current stress across switches and diodes. Consequently, using switches and diodes with low current and voltage withstanding is achievable, leading to high converter efficiency and cost reduction. The voltage and current stress besides steady‐state and efficiency analysis are surveyed. Moreover, the converter's non‐ideal voltage gain analysis employing different components is discussed and compared with recently suggested converters. Additionally, the component losses, efficiency, normalized voltage, and current stresses of the studied converters are collected in tables to simplify the comparison between different topologies. Finally, a 100 W prototype converter is implemented to confirm theoretical performance, and the results are investigated in detail.
A new array extension configuration method based on nesting and minimum redundancy
Authors: Ma He , Mao Xingpeng , Wang Xiuhong , Gao Yang 
Published: January 2023

AbstractWhile the uniform linear array (ULA) is a well‐known array configuration being widely used in various practical application scenarios, it also encounters numerous challenges in the field of direction‐of‐arrival (DOA) estimation. Specifically, it is difficult for the ULA to achieve a satisfactory DOA estimation accuracy, especially in the case of closely spaced sources. That is because that the resolvability of ULA is severely restricted by its limited DOA. To circumvent this issue and further improve the DOA estimation performance, a new array geometry is designed. Inspired by the fact that some linear sparse co‐arrays can yield higher DOFs and larger array apertures, the proposed array configuration is developed by nesting two or more minimum‐redundant arrays in a dedicated way. The simulation results indicate that the proposed array configuration can significantly increase the DOFs and the length of virtual array apertures, and an improved estimation accuracy can be accepted.