bluuebunny/crossref_metadata_2025_split huggingface dataset:
Magnetoresistive effect in a quantum heterostructure with helical spacer: interplay between helicity and external electric field
Authors: Sarkar Suparna , Maiti Santanu K 
Published: May 2022

Abstract
Giant magnetoresistive effect in a multi-layered structure not only depends on the properties of magnetic systems, it also strongly depends on the type of non-magnetic spacer that is clamped between magnetic layers. In this work, we critically investigate the role of a helical spacer in presence of a transverse electric field. Two kinds of helical geometries, possessing short-range (SRH) and long-range hopping (LRH) of electrons, are taken into account mimicking single-stranded DNA and protein molecules respectively. Sandwiching the magnetic–non-magnetic–magnetic quantum heterostructure between source and drain contact electrodes, we investigate the properties of giant magnetoresistance (GMR) following the Green’s function formalism within a tight-binding framework. The interplay between SRHs and LRHs of electrons provides several nontrivial signatures in GMR, especially in the presence of transverse electric field, as it makes the system a deterministic disordered one, similar to the well-known Aubry–Andre–Harper from. The famous gapped nature of energy band structure in presence of cosine modulation leads to high degree of magnetoresistance at multiple Fermi energies, compared to the traditional spacers. The magnetoresistive effect can be monitored selectively by adjusting the electric field strength and its direction. Comparing the results between the SRH and LRH cases, we find that the later one is more superior. Finally, to make the system more realistic we include the effect of dephasing. Our analysis may provide some fundamental aspects of designing electronic and spintronic devices based on magnetoresistive effect.
A non-destructive and efficient transfer method for preparing 2D materials samples for transmission electron microscopy study
Authors: Lyu Fengjiao , Tang Bin , Li Xuan , Chen Qing 
Published: May 2022

Abstract
Studying two-dimensional (2D) materials using transmission electron microscopy (TEM) is necessary and very important in many aspects. However, some 2D materials are not resistant to acids or alkalis, which are widely used in normal wet transfer techniques to transfer the exfoliated 2D nanosheets onto the TEM grids. On the other hand, dry stamping method can damage the holey carbon film on the TEM grids. In this article, we present a non-destructive, efficient, and widely applicable transfer method for preparing the TEM samples of the exfoliated 2D materials. Our method only uses the heat-release tape, PMMA, and blue Nitto tape. Neither acid nor alkali is involved in our method, therefore, impurities and damage can be avoided to the greatest extent. The method is also very efficient and can be accomplished in less than 30 min after the exfoliation of the 2D materials. This method is particularly useful for preparing the TEM samples of the 2D materials that are not resistant to acids and alkalis. The present method is also applicable to various 2D materials and various substrates.
Green synthesis of DOX-loaded hollow MIL-100 (Fe) nanoparticles for anticancer treatment by targeting mitochondria
Authors: Zhang Yechuan , Gu Zhengxiang , Yun Seonho , Luo Kui , Bi Jingxiu , Jiao Yan , Zhang Hu 
Published: May 2022

Abstract
Fe-based metal-organic frameworks (MOFs) are promising drug delivery materials due to their large surface area, high stability, and biocompatibility. However, their drug loading capacity is constrained by their small pore size, and a further improvement in their drug capacity is needed. In this work, we report an effective and green structural modification strategy to improve drug loading capacity for Fe-based MOFs. Our strategy is to grow MIL-100 (Fe) on carboxylate-terminated polystyrene (PS-COOH) via a sustainable route, which creates a large inner cavity as well as exposure to more functional groups that benefit drug loading capacity. We employ the scanning electron microscope and transmission electron microscope to confirm the hollow structure of MIL-100 (Fe). Up to 30% of drug loading capacity has been demonstrated in our study. We also conduct cell viability tests to investigate its therapeutic effects on breast cancer cells (MDA-MB-231). Confocal laser scanning microscopy imaging confirms cellular uptake and mitochondrial targeting function of doxorubicin-loaded H-M (DOX@H-M) nanoparticles. JC-1 staining of cancer cells reveals a significant change in the mitochondrial membrane potential, indicating the mitochondrial dysfunction and apoptosis of tumor cells. Our study paves the way for the facile synthesis of hollow structural MOFs and demonstrates the potential of applying Fe-based MOFs in breast cancer treatment.
A deep residual inception network with channel attention modules for multi-label cardiac abnormality detection from reduced-lead ECG
Authors: Srivastava Apoorva , Pratiher Sawon , Alam Sazedul , Hari Ajith , Banerjee Nilanjan , Ghosh Nirmalya , Patra Amit 
Published: May 2022

Abstract

Objective. Most arrhythmias due to cardiovascular diseases alter the heart’s electrical activity, resulting in morphological alterations in electrocardiogram (ECG) recordings. ECG acquisition is a low-cost, non-invasive process and is commonly used for continuous monitoring as a diagnostic tool for cardiac abnormality identification. Our objective is to diagnose twenty-nine cardiac abnormalities and sinus rhythm using varied lead ECG signals. Approach. This work proposes a deep residual inception network with channel attention mechanism (RINCA) for twenty-nine cardiac arrhythmia classification along with normal ECG from multi-label ECG signal with different lead combinations. The RINCA architecture employing the inception-based convolutional neural network backbone uses residual skip connections with the channel attention mechanism. The inception model facilitates efficient computation and prevents overfitting while exploring deeper networks through dimensionality reduction and stacked 1-dimensional convolutions. The residual skip connections alleviate the vanishing gradient problem. The attention modules selectively leverage the temporally significant segments in a sequence and predominant channels for multi-lead ECG signals, contributing to the decision-making. Main results. Exhaustive experimental evaluation on the large-scale ‘PhysioNet/Computing in Cardiology Challenge (2021)’ dataset demonstrates RINCA's efficacy. On the hidden test data set, RINCA achieves the challenge metric score of 0.55, 0.51, 0.53, 0.51, and 0.53 (ranked 2nd, 5th, 4th, 5th and 4th) for the twelve-lead, six-lead, four-lead, three-lead, and two-lead combination cases, respectively. Significance. The proposed RINCA model is more robust against varied sampling frequency, recording time, and data with heterogeneous demographics than the existing art. The explainability analysis shows RINCA's potential in clinical interpretations.
Defect engineering using microwave processing in SiC and GaAs
Authors: Olikh Oleg , Lytvyn Petro 
Published: May 2022

Abstract
The influence of microwave radiation (2.45 GHz, 1.5 W cm−2, up to 80 s) on defects was studied in single crystals of n-6 H-SiC, n-GaAs, and epi-GaAs. The capture cross section of the charge carrier was found to change, and defect complexes were reconstructed because of the growing number of interstitial atoms in the near-surface layer. The correlation between the changes in the defect subsystem and deformation of the near-surface layer was analyzed. The possible mechanisms of the revealed effects are also discussed.
Performance and analysis of an ultraviolet C-band light emitting diode with an emission wavelength of 268 nm
Authors: Zhang Jianping , Zhou Ling , Gao Ying , Lunev Alexander , Zhang Bin , Götz Werner 
Published: May 2022

Abstract
We report a high-power ultraviolet C-band light-emitting diode (UVC LED) with peak wavelength at 268 nm delivering 199 mW optical power at 350 mA direct current. The peak wall-plug and external quantum efficiencies are greater than 10% and 13%, respectively. We developed an approach to determine light-extraction efficiency (LEE) and internal quantum efficiency (IQE) based on the carrier recombination rate equation and used it to analyze the junction-temperature-dependent optical power behavior. For this LED, we obtained a LEE of ~16% and a peak IQE of ~83%. The efficiency droop percentage was quantified to be ~20% at 350 mA, owing to Auger and other higher order carrier losses.
Fast full N-body simulations of generic modified gravity: conformal coupling models
Authors: Ruan Cheng-Zong , Hernández-Aguayo César , Li Baojiu , Arnold Christian , Baugh Carlton M. , Klypin Anatoly , Prada Francisco 
Published: May 2022

Abstract
We present mg-glam, a code developed for the very fast
production of full N-body cosmological simulations in modified
gravity (MG) models. We describe the implementation, numerical tests
and first results of a large suite of cosmological simulations for
three classes of MG models with conformal coupling terms: the f(R)
gravity, symmetron and coupled quintessence models. Derived from
the parallel particle-mesh code glam, mg-glam
incorporates an efficient multigrid relaxation technique to solve
the characteristic nonlinear partial differential equations of these
models. For f(R) gravity, we have included new variants to
diversify the model behaviour, and we have tailored the relaxation
algorithms to these to maintain high computational efficiency. In a
companion paper, we describe versions of this code developed for
derivative coupling MG models, including the Vainshtein- and
K-mouflage-type models. mg-glam can model the prototypes
for most MG models of interest, and is broad and versatile. The
code is highly optimised, with a tremendous speedup of a factor of
more than a hundred compared with earlier N-body codes, while
still giving accurate predictions of the matter power spectrum and
dark matter halo abundance. mg-glam is ideal for the
generation of large numbers of MG simulations that can be used in
the construction of mock galaxy catalogues and the production of
accurate emulators for ongoing and future galaxy surveys.
Possibilities of synthesizing new proton-rich nuclei with 40 ≤ Z ≤ 60 using multinucleon transfer reactions *
Authors: Cheng Zhi , Bao XiaoJun 
Published: May 2022

Abstract
Multinucleon transfer reactions near the Coulomb barrier are investigated based on the improved dinuclear system (DNS) model, and the deexcitation process of primary fragments are described using the statistical model GEMINI++. The production cross sections of

Ca+

Sn and

Ni+

Te based on the DNS model+GEMINI++ are calculated and compared with experimental data. The calculated results reproduce experimental data. The cross sections of fusion-evaporation, fragmentation, and multinucleon transfer reactions in the

region are also provided in this paper. The results show that in the

region, fusion-evaporation and fragmentation reactions have good results in the relatively proton-rich region, but in the extreme proton-deficient region, the MNT reaction is still promising for synthesizing proton-rich nuclei.
Implementation of a Kalman filter-based eddy current estimator for the P-EFIT magnetic equilibrium reconstruction code
Authors: Huang Yao , Mele Adriano , Luo Zhengping , Mattei Massimiliano , Pironti Alfredo , Xiao Bingjia , Yuan Qiping 
Published: May 2022

Abstract
This article discusses the integration of a Kalman filter in the P-EFIT equilibrium reconstruction code, with the aim of estimating the currents induced in the passive structures of a tokamak. The filter is based on a vacuum electromagnetic model of the reactor, and takes advantage of an estimate of the effect of the plasma on the magnetics, provided by the equilibrium reconstruction algorithm. On the other hand, the observer is integrated into the equilibrium reconstruction, which exploits the eddy currents estimates provided by the Kalman filter to refine the obtained solution. To analyze the interplay of the reconstruction code and the proposed observer, the ITER tokamak is considered as a case-study, and the algorithm is tested on a variety of plasma conditions, selected in such a way to maximize the relevance of an accurate knowledge of the passive currents. The code performance is evaluated in terms of convergence metrics, eddy currents estimation accuracy and reconstruction of plasma-related quantities such as plasma–wall gaps, plasma current and plasma profile parameters.
Multi-scale analysis of global electromagnetic instabilities in ITER pre-fusion-power operation plasmas
Authors: Hayward-Schneider T. , Lauber Ph. , Bottino A. , Mishchenko A. 
Published: May 2022

Abstract
Global electromagnetic gyrokinetic simulations are performed with the particle-in-cell code ORB5 for an ITER pre-fusion-power-operation plasma scenario, with half-field (2.65 T) and half-current (7.5 MA). We report on a ‘multi-scale‘ analysis of the discharge, considering eigenmodes and instabilities across three scale-lengths (n < 35, 45 < n < 70, n > 100). Although the scenario will nominally have neutral beam heating with particles injected with 1 MeV, Alfvén eigenmodes are investigated in the absence of such source, and reversed shear, toroidal and elliptical Alfvén eigenmodes are found with weak damping for moderately low toroidal mode numbers (10 ⩽ n ⩽ 35). At higher toroidal mode numbers (40 ⩽ n ⩽ 70), unstable Alfvénic modes have been observed close to rational surfaces and are labelled as beta-induced Alfvén eigenmodes (BAEs)/Alfvénic ion temperature gradient modes, since their frequency is associated with the BAE gap and they are driven by the bulk plasma on the Alfvénic continuum. These modes are unstable in the absence of energetic particles (EPs), and adding a species of EPs (with an isotropic 1 MeV slowing down distribution) has negligible impact on their growth rate. At higher toroidal mode numbers (n ⪅ 200), low frequency microscale instabilities are observed.
Rheology of a granular system with capillary interactions
Authors: Montoya-Reyes Susana , Sánchez Rodrigo 
Published: May 2022

Abstract
The rheology of granular systems is poorly understood, particularly in terms of single-particle behaviour. The present work examines a computational system with capillary interparticle interactions, mimicking granular particles at an interface. Depending on the detailed physics of the system, Newtonian or viscoelastic behaviour is observed; the latter case corresponds approximately to the Voigt model of a fluid. This behaviour hints at analogies with thermal systems.
A smoking behavior detection method based on the YOLOv5 network
Authors: Jiang Xiangkui , Hu Haochang , Liu Xun , Ding Rui , Xu Yuanbo , Shi Jianxu , Du Yaoyao , Da Chunlin 
Published: May 2022

Abstract
Smoking in public places not only brings about some safety hazards, but also does harm to people’s lives, property and living environment. A smoking behavior detection model based on deep learning is trained for the concern of environment and safety. First, a vertical rotation data enhancement method is adopted in the preprocessing stage to extend the dataset and increase the objects of detection. Then, the channel attention module is introduced in backbone network to calibrate the feature response. Finally, added a small target detection layer to the YOLOv5 algorithm. This paper analyzes the network structure of the YOLOv5s, and the model is trained and tested by utilizing the YOLOv5s network. Experimental results show that the mAP value of the algorithm is improved by 5.3% over the original algorithm.
CAN message unpack and pack based on simulink automatic code generation technology
Authors: Yuan Ruiteng , Xiao Chun , Liu Mengjie , Chen Jing , Yu Maochang 
Published: May 2022

Abstract
Aiming at the problem of a large amount of CAN communication message data of automobile controllers and low efficiency of traditional software development, this paper proposes a method of CAN message unpack and pack based on Simulink automatic code generation technology. S-Function is used to design CAN message sending and receiving model that can import DBC files, and use RTW (real-time workshop) to realize Simulink model to automatically generate C code. This method effectively solves the unpack and pack of CAN messages, simplifies the code development process, and improves the efficiency of software development, especially when there are DBC files, which simplifies the work of sending and receiving and testing.
Dimensionality reduction method of rotor fault data set based on KPCA-KNPE
Authors: Lu Yu , Wu Han , Zhou Bo 
Published: May 2022

Abstract
In order to solve the problem that it is difficult to extract fault information in all directions in the process of dimensionality reduction of high-dimensional and nonlinear fault data sets, this research designs a rotor fault data set that combines Kernel principal component analysis, KPCA and Kernel Neighborhood Preserving Embedding, and KNPE Dimensionality reduction method. This method first uses the KPCA algorithm to effectively reduce the redundant attributes of the data, and retains the global nonlinear information of the original data; then uses the KNPE algorithm to mine the local manifold structure information of the data and extract the low-dimensional essential features. The above method can avoid the distortion of the local subspace structure through the simultaneous orthogonalization process, and can visually display the low-dimensional results. Use low-dimensional feature subsets to input K-nearest neighbor, KNN recognition rate and cluster analysis, etc. The distance GB
and the intra-class distance GW
are used as indicators to measure the effect of dimensionality reduction. Experiments show that this method can fully extract global and local discriminant information, make the fault classification clearer, and the recognition accuracy rate has been significantly improved. The research can solve the visualization and classification of high-dimensional and nonlinear mechanical fault data sets, and provide theoretical reference.
Robust stabilization technique for a quadrotor slung-load system using sliding mode control
Authors: Sun Huiyu , Gu Xinyan , Luo Shaoxin , Liang Yuan , Bai Jing 
Published: May 2022

Abstract
This paper addresses the problem of the robust stabilization control for a quadrotor slung-load system using sliding mode control. The hybrid model of the slung-load system is presented as two separate systems, one fully actuated, and another under actuated. To achieve the robust stabilization control with the unexpected external disturbance, a sliding mode controller is proposed to enforce the slung-load system tracking of the desired trajectory with a slight swing of the suspended load. The Lyapunov function is defined as the system energy function that is always dissipated over time until nullity, when the system reaches the point of equilibrium. The stability of the controller is analyzed by the Lyapunov function and the stability criteria are given. Finally, the simulations are performed to evaluate the effectiveness of the proposed control scheme.
A data-driven innovative design method for smart product-service systems to achieve mass personalization in rehabilitation
Authors: Ren Mengyang , Xiang Zhongxia , Cong Jingchen , Nan Bin 
Published: May 2022

Abstract
Smart product-service system (Smart PSS), as an emerging digital paradigm, offers users solution bundles to enhance the digitalization capability of the system by utilizing user-generated data. Massive information can be collected to investigate the dynamic changes of user requirements and assists the developers in designing personalized products and services. Meanwhile, key technologies (i.e. big data analysis and cloud computing) have enabled upgrading the rehabilitation equipment from the traditional physical training device to the personalized smart rehabilitation product-service system. However, few studies focus on gathering and utilizing user-generated physiological data to guide the innovative design of rehabilitation solutions in the Smart PSS environment. To fill this gap, an innovative design method is proposed to guide the Smart PSS development in the personalized rehabilitation field. The presented approach can be divided into three phases: the research phase, the development phase, and the usage phase. A personalized lower limb rehabilitation smart product-service system was described to explain the proposed approach.
Control algorithm of path planning and path tracking for automated valet parking
Authors: Kong Qi , Zhang Liangliang , Xu Xin 
Published: May 2022

Abstract
Automated Valet Parking (AVP) can relieve drivers from having to park. It enables vehicles to drive, park and charge fully automatically. This paper focuses on the first working step of the motion planning module, the global path planner. Therefore, a global path planner will be developed and evaluated based on actual research methods. A route will be computed by using an A^* algorithm based on the occupancy grid map. Subsequently, a smoothing operation will follow to obtain a drivable path. By implementing a single polar polynomial function each vertex is smoothened. The resulting global path serves as an input for path tracking. For a reasonable simulation, a vehicle controller with a lock-ahead distance and a node-check will be designed in order to keep the vehicle on the desired path. A simulation of the designed components in CarSim will be carried out to analyze the path tracking and vehicle behavior in detail.
Influence of pyrolysis temperature on tea waste-based biochar property and function as a heavy metal sorbent in aqueous solution
Authors: Cui X. L. , Zhong J. , Li H.X. , Jin R.Z. , Liu Y. , Che X.K. , Yuan X. T. , Zhang Q.D. , Fu H. 
Published: May 2022

Abstract
The properties of biochars and their adsorption performance are highly dependent on the pyrolysis temperature. In this study, tea waste-based biochars at the different pyrolysis temperature (573K-973K) were investigated, and adsorption capacities of heavy metals from solution by biochars were studied. TG/DTA and SEM results showed that with the increased of pyrolysis temperature, the yield of biochar sharply declined and reached stable at 973K. Moreover, low ratios of H/C, O/C and (O+N)/C were obtained at high pyrolysis temperature, which could produce more pore structure and be conducive to the adsorption of heavy metal ions. The adsorption experiments confirmed that the Pb and Zn absorption efficiency at 973K could reach 99.98% and 30.49%, respectively, which was the optimum temperature.
The application of CFD technology in the research of inorganic ceramic film
Authors: Li Xin , Fan Zimin 
Published: May 2022

Abstract
Inorganic ceramic membrane has been widely used in the field of fluid filtration, purification and separation. The flow characteristics of fluid passing through ceramic membrane are very important for its filtration and purification efficiency. Computational fluid dynamics (CFD) technology can simulate the fluid field rules and predict its application effect, so as to optimize the membrane structure and performance. This paper reviews the application of inorganic ceramic membrane and the application of CFD technology in the optimization of the structure of the inorganic ceramic membrane module and filtration purification separation, and makes a prospect for its future development.