bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Systematic Review and Meta-Analysis on the Epidemiology of Hepatitis B and Hepatitis C Virus among Beta-Thalassemia Major Patients in Pakistan
Authors: Waheed Usman , Saba Noore , Wazeer Akhlaaq , Ahmed Saeed 
Published: June 2021

AbstractBeta-thalassemia major patients are the leading consumers of blood transfusions in Pakistan and, therefore, have a greater risk of acquiring transfusion-transmitted infections, most notably hepatitis B and C virus (HBV and HCV). The present study includes a comprehensive review on the status of HBV and HCV in beta-thalassemia major patients in Pakistan. For this purpose, we examined original articles assessing the epidemiology of HBV and HCV in transfusion-dependent thalassemia patients.We searched 10 major subscription databases from January through February 2020, that is, Medline, PakMediNet, CINAHL, Scopus, PubMed, Web of Science, Embase, Science Direct, Google Scholar, and Directory of Open Access Journals. The World Health Organization resources were also explored for relevant reports. The search criteria included published articles up to December 31, 2019, with no language restrictions. Articles identified were introduced into the Endnote version X9 software and then screened for relevance and duplication. The results were stated as the pooled prevalence for the overall study and also for region-wise subgroups.A total of 33 studies conducted from 1995 to 2019 were included in the review. All 33 articles yielded information on HCV prevalence, while 19 of them provided information on HBV prevalence. The overall sample size was 8,554 that tested the prevalence of HCV in thalassemia patients. The sample size from the 19 studies that tested the prevalence of HBV was 6,184. The overall pooled prevalence of HBV was computed to be 4.13%, while the pooled prevalence of HCV was 29.79%. The majority of the studies were obtained from the Punjab Province (33.33%), followed by Khyber Pakhtunkhwa Province (24.24%).The total sample size of 33 studies was less than 10% of the total number of estimated thalassemic patients, that is, 100,000. Further studies or a national baseline survey are imperative to confirm the actual frequency of HBV and HCV in thalassemia patients across the country.
Connecting structure and function from organisms to molecules in small-animal symbioses through chemo-histo-tomography
Authors: Geier Benedikt , Oetjen Janina , Ruthensteiner Bernhard , Polikarpov Maxim , Gruber-Vodicka Harald R. , Liebeke Manuel 
Published: June 2021

SignificanceMetabolites mediate the establishment and persistence of most interkingdom symbioses. Still, to pinpoint the metabolites each partner displays upon interaction remains the biggest challenge in studying multiorganismal assemblages. Addressing this challenge, we developed a correlative imaging workflow to connect the in situ production of metabolites with the organ-scale and cellular three-dimensional distributions of mutualistic and pathogenic (micro)organisms in the same host animal. Combining mass spectrometry imaging and micro-computed X-ray tomography provided a culture-independent approach, which is essential to include the full spectrum of naturally occurring interactions. To introduce the potential of combining high-resolution tomography with metabolite imaging, we resolved the metabolic interactions between an invertebrate host, its symbiotic bacteria, and tissue parasites at unprecedented detail for model and nonmodel symbioses.
Is there really a Hubble tension?
Authors: Rameez Mohamed , Sarkar Subir 
Published: June 2021

Abstract
The heliocentric redshifts (z
hel) reported for 150 type Ia supernovae in the Pantheon compilation are significantly discrepant from their corresponding values in the JLA compilation. Both catalogues include corrections to the redshifts and magnitudes of the supernovae to account for the motion of the heliocentric frame relative to the ‘CMB rest frame’, as well as corrections for the directionally coherent bulk motion of local galaxies with respect to this frame. The latter is done employing modelling of peculiar velocities which assume the ΛCDM cosmological model but nevertheless provide evidence for residual bulk flows which are discordant with this model (implying that the observed Universe is in fact anisotropic). Until recently such peculiar velocity corrections in the Pantheon catalogue were made at redshifts exceeding 0.2 although there is no data on which to base such corrections. We study the impact of these vexed issues on the 4.4σ discrepancy between the Hubble constant of H
0 = 67.4 ± 0.5 km s−1 Mpc−1 inferred from observations of CMB anisotropies by Planck assuming ΛCDM, and the measurement of H
0 = 73.5 ± 1.4 km s−1 Mpc−1 by the SH0ES project which extended the local distance ladder using type Ia supernovae. Using the same methodology as the latter study we find that for supernovae whose redshifts are discrepant between Pantheon and JLA with Δz
hel > 0.0025, the Pantheon redshifts favour H
0 ≃ 72 km s−1 Mpc−1, while the JLA redshifts favour H
0 ≃ 68 km s−1 Mpc−1. Thus the discrepancies between SNe Ia datasets are sufficient to undermine the claimed ‘Hubble tension’. We further note the systematic variation of H
0 by ∼6–9 km s−1 Mpc−1 across the sky seen in multiple datasets, implying that it cannot be measured locally to better than ∼10% in a model-independent manner.
Quantifying entropy production in active fluctuations of the hair-cell bundle from time irreversibility and uncertainty relations
Authors: Roldán Édgar , Barral Jérémie , Martin Pascal , Parrondo Juan M R , Jülicher Frank 
Published: June 2021

Abstract
We introduce lower bounds for the rate of entropy production of an active stochastic process by quantifying the irreversibility of stochastic traces obtained from mesoscopic degrees of freedom. Our measures of irreversibility reveal signatures of time’s arrow and provide bounds for entropy production even in the case of active fluctuations that have no drift. We apply these irreversibility measures to experimental recordings of spontaneous hair-bundle oscillations in mechanosensory hair cells from the ear of the bullfrog. By analyzing the fluctuations of only the tip position of hair bundles, we reveal irreversibility in active oscillations and estimate an associated rate of entropy production of at least ∼3k
B/s, on average. Applying thermodynamic uncertainty relations, we predict that measuring both the tip position of the hair bundle and the mechano-electrical transduction current that enters the hair cell leads to tighter lower bounds for the rate of entropy production, up to ∼103
k
B/s in the oscillatory regime.
Color halo scenario of charmonium-like hybrids *
Authors: Ma Yunheng , Sun Wei , Chen Ying , Gong Ming , Liu Zhaofeng 
Published: June 2021

Abstract
The internal structures of

charmonium-like hybrids are investigated under lattice QCD in the quenched approximation. We define the Bethe-Salpeter wave function (

) in the Coulomb gauge as the matrix element of a spatially extended hybrid-like operator (

) between the vacuum and n-th state for each

, with r being the spatial separation between a localized

component and the chromomagnetic strength tensor. These wave functions exhibit some similarities for states with the aforementioned different quantum numbers, and their r-behaviors (no node for the ground states and one node for the first excited states) imply that r can be a meaningful dynamical variable for these states. Additionally, the mass splittings of the ground states and first excited states of charmonium-like hybrids in these channels are obtained for the first time to be approximately 1.2-1.4 GeV. These results do not support the flux-tube description of heavy-quarkonium-like hybrids in the Born-Oppenheimer approximation. In contrast, a charmonium-like hybrid can be viewed as a “color halo” charmonium for which a relatively localized color octet

is surrounded by gluonic degrees of freedom, which can readily decay into a charmonium state along with one or more light hadrons. The color halo picture is compatible with the decay properties of

and suggests LHCb and BelleII to search for

charmonium-like hybrids in

and

final states.
The entrance channel effect on the synthesis of a superheavy element 296119
Authors: Naderi D. , Sharifi B. 
Published: June 2021

Abstract
In this study, we investigated the entrance channel effect on the evaporation residue cross section of a superheavy element 296119. Using 29 projectile-target combinations, we investigated the role of the entrance channel on the 3n and 4n evaporation channels in hot combinations. This effect can be evaluated based on the entrance channel asymmetry and Q value of complete fusion. We calculated the variation of the maximum evaporation residue cross sections (

and

) with

for the reactions

,

,

, and

. With an increase in

,

and

increase. In addition, we studied the role of asymmetry and mean fissility parameters in the synthesis of the superheavy element. The obtained results in this study can be utilized in future studies.
An Artificial Intelligence Security Framework
Authors: Jing Huiyun , Wei Wei , Zhou Chuan , He Xin 
Published: June 2021

Abstract
With the overall acceleration of the scale construction and application of artificial intelligence worldwide, the security risks of artificial intelligence infrastructure, design and development, and integration applications are becoming increasingly prominent. Major countries have developed AI security governance by formulating AI ethical norms and improving laws and regulations and industry management. Artificial intelligence security technology system is an essential part of artificial intelligence security governance, critical support for implementing artificial intelligence ethical norms, meeting legal and regulatory requirements. It is also an important guarantee for the artificial intelligence industry’s healthy and orderly development. This article in view of the problem of lacking artificial intelligence security framework worldwide, focusing on the current artificial intelligence prominent security risks, proposes an AI security framework that covers AI security goals, graded capabilities of AI security, and AI security technologies and management systems. We look forward to providing useful references for the community to improve the safety and protection capabilities of artificial intelligence.
The optimization of machining cutting zone based on improved genetic algorithm
Authors: Ji S C , Lu D X , Deng L 
Published: June 2021

Abstract
The processing accuracy in the machining cutting zone is uneven. The condition of processing parts is most sharply worsened, when the guides junction occurs opening (the graph of pressure in the guides’ surfaces is not distributed over their entire length). The aim of this paper is optimization of the effective cutting zone (ECZ) of machining tool, in which graph of the guides pressure is always distributed on all surfaces. The layout of machining tools must ensure the largest zone of ECZ. The optimization of the objective function could change these parameters of layout, such as the vector of cutting forces, the weighting centre of the support, the coordinates of applied force from driving system, the width and length of guides. The task of optimization is a nonlinear extreme. According to the structural parameters of the machine tool, the pressure equation of the guide rail is established. For finding the optimal value, the method for determining extremum of the objective function used improving genetic algorithm (GA). Application of the method GA has allowed approximately ten times to raising the speed of determining of the layout parameters that ensure the largest ECZ.
An intelligent computing and control model of topological relation between spatial objects based on fuzzy theory
Authors: Xiang Jun 
Published: June 2021

Abstract
The technological progress in the field of artificial intelligence (AI) has brought new opportunities and challenges to the intelligent development and innovative research in fuzzy spatial relations, fuzzy theory is the basic theory of intelligent information processing, and the paper gives a brief analysis of fuzzy calculation method in spatial analysis and spatial relation calculation. In particular, the spatial relations of fuzzy objects are more difficult to express and describe accurately. This paper proposes a method to calculate the topological relations between fuzzy objects with 4-Intersection model and 9-Intersection model, in the analysis of spatial relations, the extension from deterministic entity to uncertain entity is realized with fuzzy set theory, the fuzzy space matrix is constructed, then fuzzy topological relations and fuzzy membership are calculated and output, the model simplifies many complex relations, and it can describe eight topological relations including disjoint, meet, overlap, covers, contains, covered-by, inside and equal. In practical application, the position of spatial objects can be controlled and adjusted according to topological relations. Through analysis of algorithm and fuzzy membership calculation, the model is effective in theory.
An Automotive Unknown-Environment Explorer Robot Based on Braitenberg Vehicle Four
Authors: Xu Wenhao , Wang Yibo , Zhang Yuheng 
Published: June 2021

Abstract
Environment exploration is an essential task in robotics, but it requires lots of high-tech sensors, which will make the robot very costly. To complete the exploration, a huge number of robots are required. Then, how to explore an unknown environment using simple robots with simple sensors is a significant problem to be studied. In this paper, robots are built based on Braitenberg Vehicle 4 and the robots are made to explore an unknown environment without a human. Braitenberg Vehicles are a series concept created by V. Braitenberg. Braitenberg Vehicle 4, particularly, is a robot that only has reflection level intelligence. The Robot’s logic is only four parts, going straight, turning left, turning right, and turning around. The simplicity of the design allows putting the Robot into mass production. MATLAB is used to simulate the working process of the Robot to test the Robot’s feasibility. Then, the map drawn by the Robot with the actual environment is compared. The result has shown that the map we got is almost the same as the real surroundings.
Energy Efficiency Hybrid Precoding for UAV Inspection Communication System
Authors: Minzheng Li , Jiaqing Zhai 
Published: June 2021

Abstract
In order to reduce the communication power consumption during UAV power line inspection, a energy efficiency hybrid recoding scheme based on one phase shifter is proposed in its communication subsystem. The solution is realized by using a partially connected hybrid precoder architecture in the UAV communication terminal, and using a beam combiner at the wireless network access point. At the same time, in order to reduce the complexity of hybrid precoding and combiner beam optimization design, convolutional neural networks are used to dynamically design and select the optimized beam required for UAV inspection and communication. Under the premise of efficiency, the communication energy efficiency can be improved as high as possible, thereby effectively improving the battery life cycle and cruise time of the UAV. The simulation results show that, compared with the manifold optimization and orthogonal matching pursuit algorithms, the proposed algorithm can significantly improve the energy efficiency of communication coding and battery life cycle.
A surrogate-assisted hybrid optimization algorithm enhanced by opposition-based learning and its variants
Authors: Ling Zhaoqi 
Published: June 2021

Abstract
Surrogate-Assisted Evolutionary Algorithms (SAEAs) are effective approaches to solve computationally expensive optimization problems by remarkably reducing real fitness evaluations. In this work, we proposed a surrogate-assisted hybrid optimization algorithm via combining a famous hierarchical SAEA Framework ESAO and a hybrid teaching-learning based optimization (TLBO) algorithm TLBO-SM. In addition, opposition-based learning (OBL) and its variants are used to enhance the global search ability. Experimental results on benchmark problems show that our method can outperform state-of-the-art SAEAs on most benchmark problems with the significant enhancement made by a recently proposed OBL variant.
Research on anxiety detection based on personalized data markers
Authors: Tan Yuyang , Zeng Qinwei , Zhang Hongchang 
Published: June 2021

Abstract
The use of machine learning methods to detect human anxiety has become the mainstream. However, the label of current data usually relies on the subject’s manual labeling, and there are strong subjective factors. In addition, traditional methods have the disadvantages of insufficient feature extraction, inaccurate classification results, and insufficient generalization ability. In response to the above problems, we propose an objective data labeling method, which extracts features on the basis of maintaining the characteristics of the original physiological signals, constructs a more complete feature set, and builds a long short-term memory network (LSTM) model on this basis perform an anxiety state detect. Experiments show that after processing the data by our method, the performance of all models has been greatly improved, among which LSTM shows the best performance compared with traditional algorithms.
A 3D medical image registration method based on multi-scale feature fusion
Authors: Zhang Jinshuo , Liu Fangquan , Yu Xuedou , Ma Yingjun , Zhao Xiuyang 
Published: June 2021

Abstract
Deformable medical image registration refers to finding a certain transformation so that the corresponding points of two medical images can be aligned in space. This has important clinical applications. In this article, we propose an unsupervised end-to-end medical image registration method. In this method, the fixed image and the moving image are concatenated in series and input into the convolution neural network to obtain the feature images of different scales. In order to improve the ability of neural network to capture global and local information, we fuse feature maps of different scales. The spatial transformation network uses the deformation field to deform the moving image, so as to realize the registration of the two pairs. We validate our method in the ABIDE data set and compare it with some classic state-of-the-art methods. The experimental results show that our method improves the registration accuracy of image pairs.
Linear correlation analysis of ammunition storage environment based on Pearson correlation analysis
Authors: Yang Qingxi , Kang Qiaokun , Huang Qingyang , Cui Zenghui , Bai Yu , Wei Huanan 
Published: June 2021

Abstract
The problem of the reliability of ammunition storage environment is a hot topic in the field of modern military research, and the key is to find out the main factors that affect the reliability of ammunition sensitive components. Grey relational entropy analysis method can find out the order of influencing factors, but it can’t judge the influence size and correlation. Pearson analysis method can analyze linear correlation factors better. Therefore, this paper proposes that for the complex problems such as the influence factors of ammunition storage environment, Pearson correlation analysis method can be used to find out the linear correlation factors. Then the grey correlation entropy method is used to find out the other factors. It can lay the foundation for the follow-up analysis of the main factors. Through the comparison and analysis of the actual examples, it is found that the ranking of the influencing factors ranking by the two methods has high consistency. But Pearson method can find the linear correlation factors.
Error Evaluation of the Crown Profile of Logarithmic Generatrix Roller
Authors: Yadong Zhang , Jianhua Wang , Hubing Du , Peili Yin 
Published: June 2021

Abstract
In order to realize the accurate assessment of the profile error of the crown of the bearing roller, according to the geometric characteristics and the definition of the shape error of the contour element of the logarithmic bus-type roller, based on the principle of least squares, the least squares piece-wise fitting and error evaluation method of the logarithmic bus-type (combined form of the two-segment logarithmic curve) bearing roller crown profile are studied. Firstly, the three-point method is used to determine the curvature of the discrete data points of the convexity curve, and the boundary point of the two logarithmic curves is determined by the curvature difference method. Secondly, the measuring points adjacent to both sides of the dividing point are selected as auxiliary dividing points; the auxiliary dividing points and the corresponding logarithmic curve segment measuring points are fitted together to fit a series of least squares curves and calculate the corresponding errors. Through comparison and judgment, the least square error of the logarithmic bus-type roller profile is finally determined. Finally, through comparison and judgment, the least square error of the logarithmic bus-type roller profile is finally determined. The example results show that the total error of the logarithmic bus-type roller crown profile curve is 0.0071mm. The method in this paper can effectively realize the fitting and error evaluation of the bearing crown profile error, and it also verifies that the logarithmic prime line can reduce the stress concentration and improve the service life of the bearing.
Research on Evaluation of Tower Vibration State Based on SCADA
Authors: Su Liancheng , Zhu Jiaojiao , Li Yingwei 
Published: June 2021

Abstract
Tower is very critical to the safe operation of wind turbines. In this paper, SCADA data is used to evaluate the vibration state of the tower. A tower vibration correlation analysis method based on denoising autoencoder (DAE) is proposed, which evaluates the impact of state parameters on tower vibration based on the reconstruction residual. The tower vibration is predicted based on the Long Short-Term Memory (LSTM) network, and then the tower vibration state is evaluated based on the Wasserstein distance. The actual SCADA data is used to verify the proposed method. The results show that the method accurately predicts the tower vibration trend and quantitatively evaluates the tower vibration state.
Study on Environmental Adaptability of Electric Vehicle based on WLTC cycle
Authors: Deng Bo , Li Lu , Ou Yang , Wang Yi , Zhao Zhichao , Meng Zaiqiang , Zhou Qianlu 
Published: June 2021

Abstract
By employing the energy-flow testing technique, this study probes into the environmental adaptability of electric vehicles based on the worldwide harmonized light duty driving test cycle. The following conclusions were reached. Compared with the conditions under normal temperatures, the AC system and the PTC consume 18%-20% energy of the battery, the mileage reduces by 32% to 48%, and the energy consumption per 100 km increases by 49% to 81%. From the perspective of single cycles, the total mileage divides into three stages, among which the first stage shows the largest cycle difference. A correction factor is proposed based on the energy equilibrium relations, and the correction factor for the first stage under normal, high and low temperatures are 1.022, 1.050 and 1.184 respectively. Meanwhile, the discharging internal resistance of the battery under low temperatures differs significant from those under high or normal temperatures, showing an increase by 2%-5%, while the charging internal resistance shows no significant differences.