bluuebunny/crossref_metadata_2025_split huggingface dataset:
A modified 3D EfficientNet for the classification of Alzheimer's disease using structural magnetic resonance images
Authors: Zheng Bowen , Gao Ang , Huang Xiaona , Li Yuhan , Liang Dong , Long Xiaojing 
Published: August 2022

AbstractStructural magnetic resonance imaging (MRI) provides useful information for biomarker exploration and intelligent classification of Alzheimer's disease (AD). Machine learning and deep learning methods have been used in feature extraction and computer‐aided diagnosis or prediction of AD. In this research, a new deep learning model is developed to detect or predict AD in an effective manner. A modified 3D EfficientNet with a sequentially connected 3D mobile inverted bottleneck convolution (MBConv) block is proposed to explore the multiscale characteristics of brain MR images for AD classification. The 3D MBConv block consists of depthwise convolution and a squeeze‐and‐excitation module to transform the input features into more compact features with fewer parameters than those in standard convolution. The proposed method was evaluated considering four classification tasks: (1) NC versus AD, (2) NC versus all MCI, (3) NC versus pMCI, and (4) sMCI versus pMCI. The proposed model achieved accuracies of 95.00%, 86.67%, and 83.33% for the classification of NC versus AD, NC versus pMCI, and sMCI versus pMCI, respectively, and exhibited a high performance in comparison with the classical networks and several existing methods. Efficient deep learning networks are powerful tools for the early diagnosis and prediction of AD.
A two‐step image stabilisation method for promoting visual quality in vision‐enabled maritime surveillance systems
Authors: Huang Yanhong , Liu Ryan Wen , Liu Jingxian 
Published: August 2022

AbstractMaritime surveillance systems have been commonly exploited in vessel traffic services. The maritime visual information can be obtained through shore‐borne, ship‐borne or air‐borne cameras. However, the obtained visual data often suffers from blur effects due to the shaky imaging devices in wild conditions (e.g. wind, waves and currents). It is necessary to develop image stabilisation methods to promote visual quality. In this work, we propose a two‐step image stabilisation method by introducing the blind deblurring technology. In particular, we first propose a hybrid regularised blur kernel estimation method to robustly and accurately capture the motion trajectory of imaging devices during shaking. Once the estimation of motion trajectory is obtained, we then present a robust non‐blind deblurring method in the second step to implement restoration of latent sharp image (i.e. image stabilisation). All non‐convex and non‐smooth minimisation problems related to blur kernel estimation and non‐blind deblurring are effectively solved using the alternating direction method of multipliers‐based numerical methods. Extensive experiments on both synthetic and realistic blurred images have been performed. All experimental results have demonstrated the satisfactory performance of our image stabilisation method under different imaging conditions. Moreover, the comparisons on other state‐of‐the‐art methods have also indicated that our method could provide a good representation of promoting object detection in vision‐enabled maritime surveillance systems.
Specific emitter identification based on the multi‐discrepancy deep adaptation network
Authors: Wang Tianchi , Yu Lu , Wang Wenyu , Wei Jianyu 
Published: August 2022

AbstractSpecific emitter identification task often encounters the problem of channel inconsistency between the collected signal and the signal to be recognised, that is, different channel environments would cause inconsistency in the sample distribution, which would result in a significant decrease in recognition accuracy; the same problem is encountered in transfer learning. The authors focus on an important category of methods in transfer learning called domain adaptation to solve the above problems. Motivated by the idea of the Fisher discriminant and metric learning, a novel domain adaptation method called the multi‐discrepancy deep adaptation network is proposed. In contrast to the current approach of reducing the discrepancies between the source and target domain distributions without considering category information, the basic idea of the proposed method is to increase interclass discrepancies between the source and target domains while decreasing interclass discrepancies. To adjust the weights of interclass and interclass discrepancies, a dynamic balancing factor that adaptively adjusts the weights between the interclass variance and interclass variance according to the latest trends of both variances is introduced, which is effective in improving performance. Dynamic balancing and learning weight factors, which are used to adjust the training weights of interclass and interclass discrepancies during the training process are introduced. The authors applied the network to a specific emitter identification problem under different channels on the ORACLE radio frequency Fingerprinting Data set and demonstrated a maximum domain adaptability increase of 15.4%, which outperformed existing domain adaptation methods.
An improved triple‐frequency cycle slip detection and repair method based on wavelet packet transform and adaptive threshold for BeiDou System satellite
Authors: Su Mingkun , Yang Yanxi , Qiao Lei , Liu Erxiao , Song Huina , Wu Chao , Zhang Huan 
Published: August 2022

AbstractCycle slip detection and repair is one of the key factors of Global Navigation Satellite System carrier phase high precision positioning. Although various methods have been proposed to detect and repair the cycle slip, they are still limited by kinds of factors and the effect is not ideal, especially in real‐time triple‐frequency high precise positioning applications for BeiDou Systems (BDSs). Traditional methods only improve the algorithm from the detection level, but the observation level and the threshold of detection always be ignored. Research indicates that the noise of observation seriously affects the success rate of cycle slip detection, and the threshold of detection largely depends on the satellite type and data sampling rate. A new triple‐frequency cycle slip detection and repair method, based on wavelet packet transform and adaptive threshold strategy, is proposed to detect and repair the cycle slip for real‐time BDS triple‐frequency positioning applications. The key idea of the proposed method is the use of both the wavelet packet transform and elevation model to mitigate random noise and the satellite‐induced code bias from the observation level, and the adaptive threshold strategy to adjust the threshold of detection based on satellite type and data sampling rate in the detection level. Real datasets are collected to evaluate the performance of the proposed method. Experimental results indicated that the proposed method can effectively detect and repair all types of cycle slips, such as single‐frequency small cycle slip, large cycle slip, and particular cycle slip, improve the success rate and reliability, and lay a solid foundation for BDS high‐precision positioning.
Identifying driver modules based on multi‐omics biological networks in prostate cancer
Authors: Chen Zhongli , Liang Biting , Wu Yingfu , Zhou Haoru , Wang Yuchen , Wu Hao 
Published: August 2022

AbstractThe development of sequencing technology has promoted the expansion of cancer genome data. It is necessary to identify the pathogenesis of cancer at the molecular level and explore reliable treatment methods and precise drug targets in cancer by identifying carcinogenic functional modules in massive multi‐omics data. However, there are still limitations to identifying carcinogenic driver modules by utilising genetic characteristics simply. Therefore, this study proposes a computational method, NetAP, to identify driver modules in prostate cancer. Firstly, high mutual exclusivity, high coverage, and high topological similarity between genes are integrated to construct a weight function, which calculates the weight of gene pairs in a biological network. Secondly, the random walk method is utilised to reevaluate the strength of interaction among genes. Finally, the optimal driver modules are identified by utilising the affinity propagation algorithm. According to the results, the authors’ method identifies more validated driver genes and driver modules compared with the other previous methods. Thus, the proposed NetAP method can identify carcinogenic driver modules effectively and reliably, and the experimental results provide a powerful basis for cancer diagnosis, treatment and drug targets.
Preventive Treatment of Migraine
Authors: Todd Candice M. , Sandoe Claire H. , Lay Christine 
Published: August 2022

AbstractMigraine significantly impacts individuals from all walks of life and from all around the globe. Chronic or high-frequency episodic migraine has similar disability and burden on the healthcare system and can be challenging to manage. The focus of this article is to provide an outline of the available pharmacological and nonpharmacological evidence-based strategies that clinicians can employ to build a “toolbox” for their patients.
Superficial Femoral Artery Rupture “Bailed Out” Using Novel Design of Supera Stent
Authors: Shah Pratik , Someshwar Vimal , Mundada Krishna 
Published: August 2022

AbstractPeripheral artery disease is a condition that occurs due to narrowing or occlusion of arterial lumen usually secondary to atherosclerosis. Endovascular treatments are minimally invasive procedures that have become popular for recanalization of such calcified/sclerosed arteries. However, heavily calcified arteries make these procedures challenging and are more prone to complications like balloon rupture and bleeding. Herein, we report a novel case of rupture of superficial femoral artery and its management using self-expanding Supera stent.
Imaging in Uterine Artery Pseudoaneurysm: A Rare, Potentially Fatal Cause of Secondary Post-partum Hemorrhage
Authors: Mule Prajakta M. , Nair Sanjota Satish , Bhargava Rajat N. 
Published: August 2022

AbstractSecondary postpartum hemorrhage is one of the important cause of postpartum morbidity and mortality. Uterine artery pseudoaneurysm is a rare, potentially fatal but treatable cause of secondary post-partum hemorrhage. If not diagnosed timely, it can lead to life-threatening hemorrhage. We report the case of a 41-year-old woman who presented with profuse vaginal bleeding on 32nd day of cesarean section. On imaging a left uterine artery pseudoaneurysm was found in the uterine wall with blood clots in the uterine cavity. Patient was managed with aggressive fluid resuscitation and immediate interventional radiology procedure of selective embolization of pseudoaneurysm. High index of suspicion is needed to search for rare vascular causes like pseudoaneurysm.
Beyond the Hip Labrum: A Pictorial Review
Authors: Baren James P. , Thaker Siddharth , Fawcett Richard , Gupta Harun 
Published: August 2022

AbstractMagnetic resonance arthrography and 3T magnetic resonance imaging of the hip are a technique commonly performed in young, physically active patients presenting with pain relating to the hip, with the focus on assessing for the presence of labral tears and femoroacetabular impingement. Abnormal signal within the labrum can be misleading, however, as labral tears are a frequent incidental finding and have been identified in a large proportion of the asymptomatic population. A range of extralabral conditions can cause hip-related pain in young patients, including pathology related to the bones, joints, and periarticular soft tissues. It is vital that the radiologist is aware for these pathologies and examines for them even in the presence of a confirmed labral tear. In this article, we review a range of common extralabral pathologies responsible for hip pain and highlight review areas that aid in their diagnosis.
FEA simulations for low-frequency multi-layer magnetically shielded rooms
Authors: Yang Songnan , Zhang Xiaohui , Gao Jiuxiang , Liu Yuanyuan , Zhang Jinsheng , Xi Xiaoli 
Published: August 2022

This paper proposes using Finite Element Analysis (FEA) simulations to optimize the design structure for low-frequency Magnetically Shielded Rooms (MSRs). In constructing a multi-layer MSR, the different characteristics of the material and laminated structure will bring different levels of magnetic Shielding Effectiveness (SE). The theoretical SE of an MSR can be determined quickly. By using the method used in this paper, the ideal laminated material structure can be found without increasing the MSR construction cost. According to the simulation results and the actual MSR measurement results we built, the optimized MSR design structure can improve the SE by 13 dB. In the area where the external measurement magnetic field is 37 820 nT, the magnetic field in the MSR is as low as 28 nT, and the SE of the MSR is higher than 57.3 dB. The method proposed by this research can provide the theoretical basis for optimal design structure and the FEA simulation method for engineering practice, which can effectively improve the SE of shielded rooms and save the construction cost. The FEA simulations used in this paper can be obtained from the following URL: https://github.com/YuukiAsuna/-Finite-element-simulation-of-material-lamination-sequence.
A toolbox for easy entry low wavenumber in situ atomic layer deposition transmission FTIR spectroscopy studies
Authors: Bin Afif Abdulla , Dadlani Anup L. , Flaten Andreas , Lid Markus Joakim , Ofstad Johannes , Erbe Andreas , Köllensperger Peter , Torgersen Jan 
Published: August 2022

A detailed description of a flexible and portable atomic layer deposition (ALD) system is presented for conducting in situ Fourier transform infrared (FTIR) absorption spectroscopy studies during the evolution and growth of ALD films. The system is directly integrated with a commercial FTIR spectrometer (Bruker Vertex 80V) to avoid the necessity of an external optical path to the instrument, thereby mitigating complexity and optical losses. In this work, we use potassium bromide (KBr) with a 5 nm layer of sputtered Si as a substrate due to higher infrared transmittance when compared to a single-side polished Si wafer. The FTIR absorption study is conducted at normal incidence in transmission mode using a deuterated L-alanine doped triglycine sulfate (DTGS) detector owing to its potential applicability for reliable measurements at wavenumbers below ∼700 cm−1. We demonstrate this by measuring ex situ the transverse optical phonon of bulk Al2O3 centered at 680 cm−1. The integrity and functionality of the system to track the nucleation stage are validated by conducting in situ FTIR absorption measurements of Al2O3 using tri-methyl aluminum (TMA) and H2O. The measured IR absorption spectra for the Al2O3 growth after each cycle of TMA and H2O show the formation and removal of CH3 (2800–3000 cm−1) groups on the substrate surface and CH4 (3016 and 1306 cm−1) molecules in the reactor, thus confirming the successful tracking of ligand exchange. Thus, this instrument, together with the choice of KBr as substrate, can enable straightforward ALD nucleation studies using a DTGS detector having sufficient signal without additional optical setup and modifications to off-the-shelf FTIR systems that allow low wavenumber experiments.
What can research on indirect translation do for Translation Studies?
Authors: Pięta Hanna , Ivaska Laura , Gambier Yves 
Published: August 2022

Abstract
This special issue is about indirect translation (ITr). To counter the traditional disinterest of Translation Studies in
researching ITr, it explores and showcases what research on the topic can do for our discipline as a whole. This introductory article
prepares the ground for and provides an overview of what is discussed in the seven articles included in the special issue. Before
introducing the contributions to this issue, we briefly explain the terminology and definitions used throughout this issue. In the spirit of
transparency, and making this special issue useful to everyone in Translation Studies, this introduction also devotes space to discussing
how this issue came into being, sharing some of the lessons learnt through guest editing.
Laser-induced fluorescence spectroscopy on xenon atoms and ions in the magnetic nozzle of a helicon plasma thruster
Authors: Vinci Alfio E , Mazouffre Stéphane , Gómez Víctor , Fajardo Pablo , Navarro-Cavallé Jaume 
Published: August 2022

Abstract
The dynamics of xenon atoms and ions expanding in the magnetic nozzle (MN) of a helicon plasma thruster is studied by means of near-infrared laser-induced fluorescence spectroscopy on resonant and metastable states. Fluorescence spectra are measured for several operating conditions inside and outside the thruster discharge chamber. In the near-field plume, the relatively intense magnetic field induces Zeeman effect on the probed optical transitions. Hence, modeling of the atomic lineshapes is addressed to accurately compute the Doppler shift and infer the velocity. The first direct measurements of the neutral flow in a MN reveal that atoms are accelerated to supersonic velocities behind the thruster exit. The ions acceleration region extends several centimeters downstream the exit plane. Larger axial ion speeds are attained when the thruster operates at lower mass flow rates and higher levels of input power.
Periodic cosmic evolution in f(Q) gravity formalism
Authors: Sahoo Parbati , De Avik , Loo Tee-How , Sahoo P K 
Published: August 2022

Abstract
We study the periodic cosmic transit behavior of the accelerated universe in the framework of symmetric teleparallelism. The exact solution of field equations is obtained by employing a well-known deceleration parameter (DP) called periodic varying DP,

q
=
m
cos
kt
−
1

. The viability and physical reliability of the DP are studied by using observational constraints. The dynamics of periodicity and singularity are addressed in detail with respect to time and redshift parameter. Several energy conditions are discussed in this setting.
A novel maximum likelihood and moving weighted average based adaptive Kalman filter
Authors: Fu Hongpo , Cheng Yongmei 
Published: August 2022

Abstract
For the state estimation with inaccurate noise statistics, the existing adaptive Kalman filters (AKFs) usually have substantial computational complexity or are not easy to estimate online. Inspired by the fact, a new computationally efficient AKF based on maximum likelihood and moving weighted average (MMAKF) is proposed. Firstly, to reduce computational complexity, instead of estimating the noise covariance matrixes, the maximum likelihood principle is introduced to directly estimate the prediction error covariance matrix and innovation covariance matrix. Subsequently, a new moving weighted average algorithm is designed to optimize the estimated results. Then, a computationally efficient AKF is derived, and its convergence performance and application are discussed. Simulation results for the target tracking example illustrate that the proposed AKF can effectively reduce error caused by inaccurate noise statistics and basically keep simplicity and elegance of the classical KF.
Do we need more research on the environmental impacts of plastics?
Authors: Ryan Peter G , Chitaka Takunda Y 
Published: August 2022

Abstract
We question whether the rapid growth in research on the impacts of environmental plastics over the last decade has substantially improved our understanding of these impacts. By the mid-1990s, the major environmental and economic impacts of plastics were sufficiently well known to conclude that they posed a significant environmental threat. Accordingly, the focus of the Third International Marine Debris Conference shifted from researching impacts to devising solutions. We should re-embrace this message, and study how best to change the inappropriate human behaviours that lie at the heart of the plastics crisis. The main role of natural scientists should be to provide robust monitoring data to assess the success of the various mitigation efforts.
Impact of Urban Compactness, Architectural Form and Climatic Considerations: an Analysis in Traditional Islamic Buildings
Authors: Abdelalim Marwa F. 
Published: August 2022

Abstract
The special metropolitan texture of Islamic urban areas mirrored its social, political construction which was reflected in the architectural forms organized along the central avenue with the city’s mosques, Madrasahs, Sabils, and Bimaristans, worked as the public substance of the city and had their own particular arrangement of rules and guidelines. This was strongly echoed in the trademark design of the age, set inside a well-weave metropolitan texture of human extents a cityscape that served to enhance the central core of the Islamic cities. This paper reviews literature on the traditional Islamic city’s urban surroundings, architectural form, socio-cultural and climatic factors that influenced the formation of such unique Islamic Buildings, where these factors helped to shape the engineering styles and utilization of spaces inside traditional Muslim public buildings, especially the application of microclimatic modifiers such as open courtyards in Islamic houses, where in the middle age metropolitan places of Islamic urban areas were envisioned to make positive microclimatic conditions in their inside such as water fountains, Planted trees, Malqafs, Mashrabiyyahs, Semi open spaces, and Iwans. Consciousness of the multifactorial nature of the impacts on the Muslim view of houses and the utilization of spaces is essential for building planners, architects, and developers to be appropriately prepared to address the issues of customers. By offering alternatives for whatever is lowering people’s quality of life or efficiency. This research should contribute to Saudi Arabia’s 2030 Vision, which aims to implement more successful Sustainability ideas as those previously used in traditional Islamic cities.
Properties, Durability and Fields of Application of Polymer Concrete
Authors: Kamal Mounir , Etman Zeinab A. , Soliman Noha M. , Elbheary Mustafa R. 
Published: August 2022

Abstract
Polymer concrete is a type of special concretes which casting by using the polymeric resin replaces the Portland cement/water binder of conventional concrete. The aim of this paper is investigated the hardened properties and the micro structure of polymer concrete. The main variables of this study were the type of epoxies [Polymer modified repair mortar (sika top122) and epoxy (Euxit 50)], epoxy to aggregate percentage and sand to dolomite ratio and. Twenty-four concrete mixes were cast to carrying out the experimental program. Compression, tensile, flexure and bond strength were conducted to evaluate the properties and impact loads. At sika top122 use water had a constant ratio according to sika top 122 equal to 35% with all mix from 1:1 to 1:16 in sixteen concrete mixes. At Euxit 50 divided into three groups in eight concrete mixes, first group had four mixes with fine aggregate (natural sand) and Euxit 50 and without added any water and coarse aggregate. The second and third groups components were coarse aggregate (natural dolomite), fine aggregate (sand) and Euxit 50 (welded polymer material) with variable mix ratios. Each group mixes had the same Euxit 50 to aggregate (coarse and fine) 1:5 and 1:6 for second and third group respectively. Get the best mix ES4 with high properties Compression, tensile, flexure and bond strength were 1,040.00, 44.60, 262.5 and 14.95 respectively.