bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reduction of write current with improved thermal stability in GeSe2 doped Sb2Te3 films for phase change memory applications
Authors: Bhatt Nidhi , Parveen Shahin , Whab Abdul , munga Pumlian 
Published: June 2024

Abstract
Chalcogenide alloy-based semiconductors have gained significant attention in recent decades due to its applications in phase change memory (PCM). Sb2Te3 has proven to be an alternative to Static and Dynamic Random Access Memory and can be a suitable candidate for commercial memory devices due to their fast switching speed. However, Sb2Te3 suffers from low amorphous phase stability and high RESET current, which needs further improvement for high power efficiency. In this work, we have prepared (Sb2Te3)1−x
(GeSe2)
x
(x = 0.06, 0.12, 0.18, 0.24, 0.3) films to investigate their PCM properties. The films showed a rise in transition temperature to transform from high resistive amorphous (RESET) to low resistive crystalline (SET) states with doping that leads to significant enhancement in amorphous phase stability. For 30% doping of GeSe2 in Sb2Te3, the data retention temperature increases from 20.2 °C to 84.6 °C, and the resistance contrast also increases from 102 to 105. The rise in electrical resistance with doping in the amorphous as well as crystalline states leads to a drop in threshold current (I
th) from 3.5 to 0.8 mA. This also reduces the RESET and SET currents. By analyzing the samples using finite element method, it was found out that the high resistance materials produce more heat, resulting in a lower write current in an energy efficient PCM device.
Top-quark FCNC decays, LFVs, lepton g − 2, and W mass anomaly with inert charged Higgses
Authors: Chen Chuan-Hung , Chiang Cheng-Wei , Su Chun-Wei 
Published: June 2024

Abstract
The observed flavor-changing neutral-current (FCNC) processes in the standard model (SM) arise from the loop diagrams involving the weak charged currents mediated by the W-gauge boson. Nevertheless, the top-quark FCNCs and lepton flavor-violating processes resulting from the same mechanism are highly suppressed. We investigate possible new physics effects that can enhance the suppressed FCNC processes, such as a top quark decaying into a light quark with a Higgs or gauge boson in the final state, i.e. t → q(h, V) with V = γ, Z, g,

h
→
ℓ
ℓ
′

, and

ℓ
→
ℓ
′
γ

. To achieve the assumption that the induced FCNCs are all from quantum loops, we consider the scotogenic mechanism, where a Z
2 symmetry is introduced and only new particles carry an odd Z
2 parity. With the extension of the SM to include an inert Higgs doublet, an inert charged Higgs singlet, a vector-like singlet quark, and two neutral leptons, it is found that, with relevant constraints taken into account, the t → c(h, Z), h → μ
τ, and τ → ℓ
γ decays can be enhanced up to the expected sensitivities in experiments. The branching ratios of h → μ
+
μ
−/τ
+
τ
− from only new physics effects can reach up to

O
(

10

−
3

)

. Intriguingly, the resulting muon g − 2 can fit the combined data within 2 standard deviations, whereas the electron g − 2 can have either sign with a magnitude of

O

(

10

−
13

−

10

−
12

)

. In addition, we examine the oblique parameters in the model and find that the resulting W-mass anomaly observed by CDF II can be accommodated.
A Monte Carlo simulation study of a Janus discotic liquid crystal droplet
Authors: Llanas-García Andrea H , Salgado-Blanco Daniel 
Published: June 2024

Abstract
The study of discotic liquid crystals (DLCs) under spherical confinement has gained considerable significance due to its relevance in the design and optimization of advanced materials with tailored properties. The unique characteristics of DLC fluids, coupled with confinement within a spherical Janus surface, offer a compelling avenue for exploring novel behaviors and emergent phenomena. In this study, Monte Carlo simulations within the NpT ensemble are employed to investigate the behavior of a DLC fluid confined by a spherical Janus surface. The Janus surface is characterized by distinct hemispheres, with one promoting homeotropic (face-on) anchoring and the other planar (edge-on) anchoring. Our analysis reveals the emergence of two topological defects: one exclusively on the edge-anchoring hemisphere and the other at the boundary of both anchorings. Each topological defect possessing a topological charge of k = +1/2. We observe that as the temperature transitions the central region of the droplet into a nematic phase, a disclination line forms, linking the two surface defects. By investigating droplets of three different sizes, we confirm that the isotropic-nematic transition is first-order for the larger droplet studied. However, this transition becomes continuous under strong confinement conditions. In contrast, the nematic-columnar transition remains first order even for smaller systems.
TFASOT for bearing damage feature extraction and enhancement under complex working conditions
Authors: Wang Kun , Huang Yukun , Luo Huageng 
Published: June 2024

Abstract
In some complex working conditions, such as variable speeds and variable loadings, events like bearing skidding and/or contact angle changing may happen during the operations. In such cases, order tracking based on the shaft speed, i.e. the first order tracking (FOT), can no longer completely eliminate the smearing effect on spectrum, and thus affects the bearing damage detection precision and accuracy. The existing second order tracking is unable to resolve these issues either in some cases. To resolve these problems, a new approach called time frequency analysis based second order tracking is developed in this paper. Based on the FOT, short-time Fourier transform and synchro-reassigning transform are used to obtain the actual fault characteristic order (FCO) information. Then the FCO is extracted by ridge searching approach to set new synchronous resampling clock. Finally, synchronous resampling and order tracking are combined to correct and enhance the bearing damage feature, resulting in more accurate damage feature extraction. The effectiveness of proposed method is verified by numerical simulations and practical examples as well. The results show that the proposed method can effectively correct the dispersion and deviation of the FCO induced by speed variations as well as operation condition variations, and thus significantly improve the damage feature extraction.
An integrated navigation algorithm assisted by CNN-Informer during short-time GNSS outages
Authors: Hu Yuan , Fan Zhe , Liu Wei , Wu Linjin 
Published: June 2024

Abstract
Inertial Navigation System (INS) and Global Navigation Satellite System (GNSSs) are commonly used in integrated navigation systems. The GNSS navigation system, however, is not autonomous, and its signals are susceptible to environmental influences leading to poor navigation results. In order to improve the positioning accuracy of the INS/GNSS integrated navigation system during GNSS outages, a hybrid algorithm of Convolutional Neural Network (CNN)-Informer model-assisted INS is proposed. The CNN-Informer model combines the advantages of each of the CNN and the Informer network. It utilizes CNN to rapidly extract spatial features from input data, employs the Informer network to establish relationships between inputs and outputs, and acquires pseudo-GNSS signals to compensate for position errors in the INS. Lastly, we evaluate the proposed algorithm through six sets of experiments conducted on public datasets and real road scenarios. The comparative results demonstrate that the proposed method offers a more accurate and reliable solution during GNSS outages. Specifically, CNN-Informer can improve navigation accuracy by 81.46% over MLP and by 58.91% over LSTM during 20-s GNSS outages.
A rotor bearing system fault diagnosis method based on FSASCA-VMD and GraphSAGE-SA
Authors: Wang Yaping , Zhang Qisong , Zhang Sheng , Li Shengbiao , Fan Yuqi 
Published: June 2024

Abstract
In complex environments, signals from rotor bearing systems can easily be drowned out by strong noise, leading to low fault diagnosis accuracy. In order to reduce noise and improve diagnostic accuracy, this paper proposes a rotor bearing system fault diagnosis method based on future search algorithm based on sine cosine algorithm-variational mode decomposition (FSASCA-VMD) and Graph SAmple and aggreGatE-self attention (GraphSAGE-SA). First, the FSASCA optimization algorithm is used to determine two parameters in VMD. The best combination found is then input into VMD to decompose the original signal. Then, filter the intrinsic mode function (IMF) components with high correlation to the original signal using cumulative percentage kurtosis. Reconstruct the filtered IMF components to complete signal denoising. Finally, this paper utilizes graph theory and time series correlation to uncover the hidden relationships within the data. Utilizing the Euclidean distance as the edge weight between nodes, a graph model is established based on the topological structure of the PathGraph, and a GraphSAGE-SA fault diagnosis framework is constructed. Utilizing a self-attention mechanism to aggregate nodes enhances the weight allocation of important information. The experimental results indicate that the method proposed in this paper can effectively remove most of the noise in the signal while preserving a significant amount of useful information. In rotor bearing system fault diagnosis, the diagnostic accuracies of this method for simulated and laboratory signals are 98.33% and 98.56%, respectively, surpassing those of other methods.
A review on synthesis, properties, and biomedical applications of graphene quantum dots (GQDs)
Authors: Bae Gaeun , Cho Hyeonwoo , Hong Byung Hee 
Published: June 2024

Abstract
A new type of 0-dimensional carbon-based materials called graphene quantum dots (GQDs) is gaining significant attention as a non-toxic and eco-friendly nanomaterial. GQDs are nanomaterials composed of sp2 hybridized carbon domains and functional groups, with their lateral size less than 10 nm. The unique and exceptional physical, chemical, and optical properties arising from the combination of graphene structure and quantum confinement effect due to their nano-size make GQDs more intriguing than other nanomaterials. Particularly, the low toxicity and high solubility derived from the carbon core and abundant edge functional groups offer significant advantages for the application of GQDs in the biomedical field. In this review, we summarize various synthetic methods for preparing GQDs and important factors influencing the physical, chemical, optical, and biological properties of GQDs. Furthermore, the recent application of GQDs in the biomedical field, including biosensor, bioimaging, drug delivery, and therapeutics are discussed. Through this, we provide a brief insight on the tremendous potential of GQDs in biomedical applications and the challenges that need to be overcome in the future.
Tracing quantum correlations back to collective interferences
Authors: Ji Ming , Hance Jonte R , Hofmann Holger F 
Published: June 2024

Abstract
In this paper, we investigate the possibility of explaining nonclassical correlations between two quantum systems in terms of quantum interferences between collective states of the two systems. We achieve this by mapping the relations between different measurement contexts in the product Hilbert space of a pair of two-level systems onto an analogous sequence of interferences between paths in a single-particle interferometer. The relations between different measurement outcomes are then traced to the distribution of probability currents in the interferometer, where paradoxical relations between the outcomes are identified with currents connecting two states that are orthogonal and should therefore exclude each other. We show that the relation between probability currents and correlations can be represented by continuous conditional (quasi)probability currents through the interferometer, given by weak values; the violation of the noncontextual assumption is expressed by negative conditional currents in some of the paths. Since negative conditional currents correspond to the assignment of negative conditional probabilities to measurements results in different measurement contexts, the necessity of such negative probability currents represents a failure of noncontextual local realism. Our results help to explain the meaning of nonlocal correlations in quantum mechanics, and support Feynman’s claim that interference is the origin of all quantum phenomena.
Direct & efficient detection of x-ray radiation using thermally evaporated 2D hybrid lead halide perovskite (BA2PbBr4)(BA=n-Butylammonium=C4H9NH3) film
Authors: Mitra Saikat , Majhi Parushottam , Maity Avisek , Hazra Snehamoyee , Chowdhury Avijit , Ghosh Barnali 
Published: June 2024

Abstract
This report demonstrates fast response and direct detection of x-ray radiation by thermally evaporated 2D hybrid halide perovskite (BA2PbBr4)(n-BA=Butylammonium=C4H9NH3) based film. A highly efficient pin-hole free/compact film (thickness∼1 μm), via a controlled evaporation process, has been grown to fabricate solid-state x-ray radiation detector film (typical dimension ∼1 × 1 cm2) of 2D hybrid halide perovskite BA2PbBr4 ( BAPB) material. Direct detection of x-rays is possible using this detector by simple electrical readout method, where a change in resistance occurs while exposed to x-ray radiation at ambient temperature. The detector current increases when an x-ray impinges on it and exhibits the highest sensitivity ∼1000 μC/Gy/cm2. The detector film shows fast response, exhibiting quick response-recovery time ∼

ms

towards x-ray. The detector film exhibits reasonably high dark resistivity ∼

10

10

Ω
−
cm

and good mobility-lifetime (

μ
τ
)

product

3.308
×

10

−
6

c

m

2

/
s
.

The 2D hybrid halide perovskite (BA2PbBr4) based detector can sustain an effective high electric field ∼5000 V cm−1 corresponding to 40 V operational bias. It shows very good radiation resistant towards x-ray and retains its crystal structure, as confirmed from structural data under sustained x-ray exposure. The 2D halide perovskite detector (BAPB) shows long-term stability or shelf life (∼4 months) and response is highly repeatable with less than

5
%

fluctuation, which is an important key performance metric for any radiation detector. This detector has good application potential in several areas like, medical imaging, security checking, etc.
Study on trap sensitivity for single material gate and double material gate nano-ribbon FETs
Authors: Rai Shashank , Sharma Ritu , Saha Rajesh , Bhowmick Brinda , Goswami Rupam 
Published: June 2024

Abstract
In this work, the trap sensitivity of single material gate (SMG) and dual material gate (DMG) nano ribbon FETs (NRFETs) are reported using TCAD Sentaurus Device simulator. The trap sensitivity is extracted for Gaussian trap distribution of both acceptor and donor type traps. We have reported the trap sensitivity for the variation in trap concentration, energy peak position, work function of metal gate, and temperature for both the NRFETs. It is realized that trap sensitivity is greater and lesser than 100% for acceptor type trap in SMG and DMG NRFETs, respectively, whereas, such sensitivity is 147% and 123% for donor type trap concentration, respectively. Temperature also shows a significant variation in trap sensitivity for both the NRFETs. The increase in work function leads to the reduction in trap sensitivity for both NRFETs in existence of acceptor and donor trap charges. The maximum sensitivity in trap are 400% and 275% for SMG and DMG NRFETs, respectively, in presence of donor trap concentration. Moreover, the trap sensitivity is very insignificant at high gate bias for donor type trap concentration with wide variation in parameters.
Transformer based deep learning hybrid architecture for phase unwrapping
Authors: Bujagouni Karthik Goud , Pradhan Swarupananda 
Published: June 2024

Abstract
A deep learning Hybrid architecture for phase unwrapping has been proposed. The hybrid architecture is based on integration of Convolutional Neural Networks (CNN) with Vision Transformer. The performance of Hybrid architecture/network in phase unwrapping is compared against CNN based standard UNET network. Structural Similarity Index (SSIM) and Root Mean Square Error (RMSE) have been used as performance metrics to assess the performance of these deep learning networks for phase unwrapping. To train and test the networks, dataset with high mean Entropy has been generated using Gaussian filtering of random noise in Fourier plane. The Hybrid architecture is tested on test dataset and is found to have superior performance metrics against the UNET network. Their performance is also tested in noisy environment with various noise levels and Hybrid architecture demonstrated better anti-noise capability than UNET network. Hybrid architecture was successfully validated in real world scenario using experimental data from custom built Digital Holographic Microscope. With the advent of newer architectures and hardware, Deep learning networks can further improve the performance in solving inverse problems.
Dynamical analysis and circuit realization of a high complexity fourth-order double-wing chaotic system with transient chaos and its application in image encryption
Authors: Zhang Jie , Bi Jingshun , Guo Yan , Wang Pengyuan 
Published: June 2024

Abstract
This paper proposes a fourth-order double-wing chaotic system with high complexity. After conducting a dynamic analysis, it is found that the system exhibits transient chaos and a rare inverse period-doubling bifurcation phenomenon in the bifurcation diagram. The system also exhibits attractor coexistence, with periodic, quasi-periodic, indicating high sensitivity to initial values. These phenomena sufficiently demonstrate the rich dynamical characteristics of chaotic systems. By introducing an impulse function with a cosine function in the foundation of the proposed system, it is found that controllable wing number and staircase burst oscillations occur. Furthermore, the number of wings and oscillation periods vary with changes in parameters, which has significant implications in engineering applications. The circuit design and construction are carried out using the Multisim simulation software, and the digital circuit is realized by using a Field-Programmable Gate Array (FPGA). It is found that the simulation results and the actual implementation results are highly consistent with the phase portrait of the system, thus demonstrating the feasibility of the circuit. Finally, by combining the proposed system with a DNA encryption algorithm, a novel image encryption algorithm with multiple layers of encryption is designed, greatly enhancing the security of encrypted images. The security of this encryption algorithm is analyzed in terms of information entropy, key space, correlation, and resistance to attacks. It is found that the proposed encryption algorithm exhibits high confidentiality and resistance to attacks. The proposed system has significant reference value in secure communication when applied to image encryption.
Perturbed conjugate gradient method: controlling semi-convergence, enforcing non-negativity, and accelerating iterations in tomographic imaging
Authors: Nikazad Touraj 
Published: June 2024

Abstract
We regulate the semi-convergence behaviour, impose non-negativity on the iterations, reduce total variation, and enhance the conjugate gradient (CG) method by introducing a perturbed version of the CG method. We provide a convergence analysis for this perturbed version. We also demonstrate its performance using examples taken from tomographic imaging and compare it with CG and its projected version, superiorized conjugate gradient (S-CG-CD), and non-negative flexible CGLS (NN-FCGLS).
Analytic computation of the entanglement of formation for bipartite isotropic states using their symmetry
Authors: Akbari-Kourbolagh Y , Shahhoseini E 
Published: June 2024

Abstract
It is well-known that computing the entanglement of formation of a general bipartite state is a difficult task. We use the local symmetry of bipartite isotropic states in arbitrary dimensions to compute their entanglement of formation analytically. Our computation is an explicit and detailed version of the computation performed by Terhal et al [B. M. Terhal and K. G. H. Vollbrecht, Phys. Rev. Lett. 85, 2625 (2000)]. However, it is not just a review but we also have our contribution and novelty. For instance, we provide a rigorous proof for the entanglement of formation of two qutrit isotropic states and notably we give a proof supporting the conjecture proposed by Terhal et al about the entanglement of formation of bipartite isotropic states for the last range of allowed parameter values.
Dynamical analysis of a new memristive map with offset boosting and extreme multistability
Authors: Han Zhitang , Cao Yinghong , Xu Xianying , Mou Jun 
Published: June 2024

Abstract
In this paper, a memristive circuit is designed based on a charge-controlled memristor, and the Hamilton energy function is obtained from the Helmholtz theorem. The system equation of memristive circuit is discretized by redefining the variables to obtain a three-dimensional memristive map and the corresponding energy function. Then, the effects of parameters and initial values on the memristive map are analyzed using conventional dynamical analysis. There are multiple types of quasi-periodic and chaotic states of the memristive map under different parameters, and the energy evolution of different states is shown. In addition, offset boosting and homogeneous extreme multistability are found in the map, which can be controlled to offset the attractor by changing specific parameters and initial values. The complexity of the chaotic sequence is also analyzed as the parameters and initial values are varied over the chosen range. Finally, the map is implemented on PSIM circuit simulation and digital signal processor (DSP) respectively. This research will provide a reference for secure communication.
Study on the influence of intermediate airshafts on the aerodynamic effect of urban rapid rail transit
Authors: Zhu Xinyi , Weng Miaocheng 
Published: June 2024

Abstract
This study explores how intermediate airshafts affect the aerodynamics of urban rapid transit trains in tunnels. It employs a three-dimensional turbulence model to simulate train-tunnel interactions, specifically examining airshafts’ impact on transient pressure variations along surfaces. The model’s accuracy and reliability are confirmed by comparing results with full-scale experimental data. The results show that airshafts effectively mitigate peak tunnel wall pressures, with the lowest peak overpressure observed at the airshaft location. With the airshaft-reflected expansion wave arriving ahead of the train, the pressure between the train front and tunnel wall decreases compared to scenarios without airshafts. Similar transient pressure changes at the tunnel entrance and rear half suggest the emergence of a “secondary compression wave” due to the train’s transit.
Design and application of a testing device for solar reflective materials
Authors: Guo Senyuan , Fang Yueyun 
Published: June 2024

Abstract
Using white polyvinyl chloride pipes, gray polyvinyl chloride pipes, natural rubber foam sheets, and nylon 6 as experimental materials, this article designed a sandwich structure solar reflective material testing device. By testing the thermal conductivity of various materials and the thermal conductivity of the composite materials in the device and conducting thermal insulation verification experiments on the solar reflective material testing device, it was found that the overall thermal conductivity of the device was small and the internal temperature of the device was less affected by the external environmental temperature. The results indicated that the solar reflective material testing device has good insulation performance.