bluuebunny/crossref_metadata_2025_split huggingface dataset:
Role of dopants and defects on the photocatalytic performance of g-C3N4 under visible light and sub-band gap excitation
Authors: Jaiswal Manju Kumari , Choudhury Biswajit 
Published: October 2022

Abstract
Here, we report the photocatalytic (PC) activity of graphitic carbon nitride (g-C3N4) doped with potassium (K), magnesium (Mg), and boron (B) under visible (>390 nm), green (532 nm), and red (660 nm) light. Doped g-C3N4 has an improved band structure, high carrier density, and tunable band-edge absorption as compared to pure g-C3N4. An atomic force microscope shows a decrease in layer thickness that follows the order: g-C3N4 > K/g-C3N4 > Mg/g-C3N4 > B/g-C3N4. The evolution of nitrogen vacancies in doped g-C3N4 was identified via x-ray photoelectron spectroscopy (XPS) and CHNS/O analyses. The red-shift in the absorption spectrum of K/g-C3N4 and the emission spectrum of B/g-C3N4 is caused by the band gap renormalization (BGR) effect. Quantum confinement and a possible Burstein–Moss (BM) effect both contribute to the spectral blue shift in the absorption spectra of Mg/g-C3N4 and B/g-C3N4. The BM effect, quantum confinement, and dopant-induced lattice strain might all alter the band structure and move the conduction band edge away from the valence band zone centre, causing an above band gap emission in K/g-C3N4 and Mg/g-C3N4. All samples degraded methylene blue (MB) under visible light with outstanding results, but they responded poorly to methyl orange (MO) and rhodamine B (RhB). With 83.59% MB degradation at a rate constant of 1.1 × 10−2 min−1, Mg/g-C3N4 recorded the best PC, which was three times quicker than g-C3N4 (3.7 × 10−3 min−1). When compared to g-C3N4, the doped samples’ current density (both anodic and cathodic) and carrier density were almost two times greater. The mechanism demonstrated how active edge sites, defects, and dopants contributed to the remarkable PC activity in the doped samples.
Bounds on anomalous quartic WWZγ couplings in e
–
p collisions at the FCC-he
Authors: Gurkanli E 
Published: October 2022

Abstract
Non-Abelian structure of the standard model (SM) predicts the self-interactions of gauge bosons triple gauge couplings (TGC) and quartic gauge couplings (QGC). On the other hand, it is also important to determine the deviations from SM via anomalous triple gauge couplings and anomalous quartic gauge couplings (aQGC) to test the nature of the SM and to see the effects of new physics arising from the beyond the standard model. In this study, we focus on the e
−
p → jZ
γ
ν

e
→ j(l
+
l
−)γ
ν

e
process to examine the WWZ
γ aQGC at the Future Circular Collider-hadron electron with center-of-mass energy

s

=
5.29

TeV using a model-independent way in the effective theory approach. A Cut-based method is applied to analyse the signal and relevant SM background. Using the total cross-sections, we constrained the anomalous f

T,i=0,1,2,5,6,7/Λ4 couplings arising from dimension-8 operators at 95% confidence level for the dilepton decay of the Z-boson. The results are composed of integrated luminosities of


=
1
,
2

and 3 ab
−1 under the systematic uncertainties of 0%, 5% and 10%. In the calculations, we use the form factor to eliminate the effects of the violation of unitarity. With this, we obtained the limits for the energy scale of the form factor Λ = 1 TeV. In addition to all this, we use the advantages of ep collisions for analysing the process with much cleaner environment and lower background effects compared with the pp collisions. The obtained sensitivities on f

T, i=0, 1, 2, 5, 6, 7/Λ4 are comparable with the experimental results and related phenomenological studies in the literature.
Numerical study of non-adiabatic quantum thermodynamics of the driven resonant level model: non-equilibrium entropy production and higher order corrections
Authors: Tong Kaiyi , Dou Wenjie 
Published: October 2022

Abstract
We present our numerical study on quantum thermodynamics of the resonant level model subjected to non-equilibrium condition as well as external driving. Following our previous work on non-equilibrium quantum thermodynamics (Dou et al 2020 Phys. Rev. B 101 184304), we expand the density operator into a series of power in the driving speed, where we can determine the non-adiabatic thermodynamic quantities. Particularly, we calculate the non-equilibrium entropy production rate as well as higher order non-adiabatic corrections to the energy and/or population, which is not determined previously in Dou et al (2020 Phys. Rev. B 101 184304). In the limit of weak system-bath coupling, our results reduce to the one from the quantum master equation.
Whole surface defect detection method for bearing rings based on machine vision
Authors: Ping Zhou , Chuangchuang Zhang , Gongbo Zhou , Zhenzhi He , Xiaodong Yan , Shihao Wang , Meng Sun , Bing Hu 
Published: October 2022

Abstract
As an important part of a bearing, a bearing ring (BR) is prone to producing various defects on each surface in the production process, which seriously affects the reliability of the bearing. To solve the problem in which multiple defects are randomly distributed on multiple surfaces and manual detection is difficult, an automatic method for detecting defects on the whole surface of BRs based on machine vision is proposed. Firstly, the characteristics of the BR’s surface defects are analyzed, and an efficient scheme for acquiring the whole surface image of the BR is designed. Then, the method for detecting the defects on the whole surface of BRs is developed, and the corresponding image preprocessing, region of interest extraction and defect recognition algorithms are designed. Finally, a visual inspection system to identify the defects on the whole surface of BRs based on a multi-station turnover process is developed. On the premise of determining the key parameters of the detection algorithm, the performance of the detection method is analyzed through the experimental method. The results show that the comprehensive accuracy of the proposed detection method is 95%, which meets the detection requirements. On this basis, the detection strategy is optimized, and the best parameter combination is obtained through the experiments, which further reduces the false detection rate of good products and the missed detection rate of defective products, both of which are less than 3.5%.
Effect of magnetic resonance imaging pre-processing on the performance of model-based prostate tumor probability mapping
Authors: Alley Stephanie , Jackson Edward , Olivié Damien , Van der Heide Uulke A , Ménard Cynthia , Kadoury Samuel 
Published: October 2022

Abstract

Objective. Multi-parametric magnetic resonance imaging (mpMRI) has become an important tool for the detection of prostate cancer in the past two decades. Despite the high sensitivity of MRI for tissue characterization, it often suffers from a lack of specificity. Several well-established pre-processing tools are publicly available for improving image quality and removing both intra- and inter-patient variability in order to increase the diagnostic accuracy of MRI. To date, most of these pre-processing tools have largely been assessed individually. In this study we present a systematic evaluation of a multi-step mpMRI pre-processing pipeline to automate tumor localization within the prostate using a previously trained model. Approach. The study was conducted on 31 treatment-naïve prostate cancer patients with a PI-RADS-v2 compliant mpMRI examination. Multiple methods were compared for each pre-processing step: (1) bias field correction, (2) normalization, and (3) deformable multi-modal registration. Optimal parameter values were estimated for each step on the basis of relevant individual metrics. Tumor localization was then carried out via a model-based approach that takes both mpMRI and prior clinical knowledge features as input. A sequential optimization approach was adopted for determining the optimal parameters and techniques in each step of the pipeline. Main results. The application of bias field correction alone increased the accuracy of tumor localization (area under the curve (AUC) = 0.77; p-value = 0.004) over unprocessed data (AUC = 0.74). Adding normalization to the pre-processing pipeline further improved diagnostic accuracy of the model to an AUC of 0.85 (p-value = 0.000 12). Multi-modal registration of apparent diffusion coefficient images to T2-weighted images improved the alignment of tumor locations in all but one patient, resulting in a slight decrease in accuracy (AUC = 0.84; p-value = 0.30). Significance. Overall, our findings suggest that the combined effect of multiple pre-processing steps with optimal values has the ability to improve the quantitative classification of prostate cancer using mpMRI. Clinical trials: NCT03378856 and NCT03367702.
Dynamics of a charged Thomas oscillator in an external magnetic field
Authors: Vijayan Vinesh , Pratik Das Pranaya 
Published: October 2022

Abstract
In this letter, we provide a detailed numerical examination of the dynamics of a charged Thomas oscillator in an external magnetic field. We do so by adopting and then modifying the cyclically symmetric Thomas oscillator to study the dynamics of a charged particle in an external magnetic field. These dynamical behaviours for weak and strong field strength parameters fall under two categories; conservative and dissipative. The system shows a complex quasi-periodic attractor whose topology depends on initial conditions for high field strengths in the conservative regime. There is a transition from adiabatic motion to chaos on decreasing the field strength parameter. In the dissipative regime, the system is chaotic for weak field strength and weak damping but shows a limit cycle for high field strengths. Such behaviour is due to an additional negative feedback loop that comes into action at high field strengths and forces the system dynamics to be stable in periodic oscillations. For weak damping and weak field strength, the system dynamics mimic Brownian motion via chaotic walks. We claim that the modified Thomas oscillator is a prototypical model to understand the dynamics of an active particle.
A stable and causal model of magnetohydrodynamics
Authors: Armas Jay , Camilloni Filippo 
Published: October 2022

Abstract
We formulate the theory of first-order dissipative magnetohydrodynamics in an arbitrary hydrodynamic frame under the assumption of parity-invariance and discrete charge symmetry. We study the mode spectrum of Alfvén and magnetosonic waves as well as the spectrum of gapped excitations and derive constraints on the transport coefficients such that generic equilibrium states with constant magnetic fields are stable and causal under linearised perturbations. We solve these constraints for a specific equation of state and show that there exists a large family of hydrodynamic frames that renders the linear fluctuations stable and causal. This theory does not require introducing new dynamical degrees of freedom and therefore is a promising and simpler alternative to Müller-Israel-Stewart-type theories. Together with a detailed analysis of transport, entropy production and Kubo formulae, the theory presented here is well suited for studying dissipative effects in various contexts ranging from heavy-ion collisions to astrophysics.
Mass-derivative relations and unitarity constraints for CP asymmetries at finite temperature
Authors: Blažek Tomáš , Maták Peter , Zaujec Viktor 
Published: October 2022

AbstractWithin the seesaw type-I leptogenesis, we formulateCPTand unitarity constraints for the equilibrium reaction rateCPasymmetries and consider thermal mass and quantum statistics. We demonstrate that including higher-order perturbative corrections in the classical Boltzmann equation remarkably induces quantum effects into the kinetic theory.
Sliding of motor tails on cargo surface due to drift and diffusion affects their team arrangement and collective transport
Authors: Yadav Saumya , Kunwar Ambarish 
Published: October 2022

Abstract
Kinesin is a microtubule-associated motor protein which works in teams to carry the cellular cargo transport. Lipid rafts on membranous cargos reorganize, causing the motors present in these areas to physically cluster. Unregulated clustering of motors leads to diseases such as Leishmaniasis, Newmann-Pick disease, etc. Various in-vitro and computational studies have reported improved cargo velocity and travel distance of a fluid cargo as compared to a rigid cargo. However, only cargo velocity increases with increase in membrane fluidity of a fluid cargo. Thermal and motor forces acting tangentially on a cargo generate random torque and motor torque respectively, leading to cargo rotation and motor tail sliding on cargo surface. However, it is unknown which of these forces/torques play a crucial role in improving the transport properties. Here, we use computational models that incorporate random torque, motor torque, and combination of both random and motor torques to understand how they influence the clustering of Kinesin motors on cargo surface due to drift and diffusion of their tails. These studies were performed at varying tail diffusivity to understand their effect on clustering of tails in dispersed and clustered arrangement. We find that in dispersed arrangement, random torque does not cause clustering, whereas motor torque is crucial for clustering of tails on cargo surface, and tails sliding due to both random and motor torques have fastest cargo transport and maximum cooperativity. In clustered arrangement, tails slide to form a broad and steady cluster whose size increases with tail diffusivity resulting in decreased cargo runlength, velocity and cooperativity. These findings suggest that increased tail diffusivity negatively impacts the cluster and cargo transport of tails in the clustered arrangement, whereas it aids physical clustering of tails and cargo transport in dispersed arrangement.
High-sensitivity metamaterial sensor based on electromagnetically induced transparency (EIT) effect
Authors: Zhu Lei , Rong Miaoxin , Li Haodong , Dong Liang 
Published: October 2022

Abstract
We propose a metamaterial sensor based on electromagnetically induced transparency (EIT) effect, which is composed of two elliptical structures with splits. Based on the coupling of bright and dark modes, a low-loss transparent window is realized at 1.88 THz. Surface current distribution and equivalent circuit model are used to analyze the physical mechanism of the EIT effect. In addition, the sensitivity of the sensor is investigated for different thickness and refractive index for analyte. The simulation results show that when the analyte thickness is 15 μm and the refractive index is between 1 and 1.5, the sensitivity of the sensor is as high as 450.7 GHz/RIU, and the figure of merit (FOM) value is 7.7. And when the refractive index of analyte is 1.5 and its thickness is between 0 and 5 μm, the sensor can also be used for thickness sensing with a sensitivity of 40.8 GHz μm−1. In addition, the proposed metamaterial sensor can be used to simulate the detection of sodium chloride solution, and the sensitivity is 66.2 GHz/

mol

d

m

3

. These above features indicate that the proposed structure paves the way for designing high-sensitivity EIT sensors in the terahertz region, which plays important roles in promoting terahertz sensing and detection technology.
Electromagnetic multi-beam steering of matrix pattern-encoded metasurfaces
Authors: Chen Yi , Li Ruisi , Huang Wenkang , Wu Yinglai , Lu Jianxun , Ke Lan , Li Chenxia , Jing Xufeng 
Published: October 2022

Abstract
An electromagnetically encoded metasurface is a synthetic surface based on subwavelength unit particles, which can freely control the amplitude, phase and polarization direction of electromagnetic waves. Using digital states to characterize electromagnetic parameters directly links digital technology at the information level with metasurface technology at the physical level. This paper proposes a matrix encoding mode to realize the flexible control of the number of scattering beams and the scattering angle of the encoding metasurface. In order to reduce the ohmic loss of the metal structure metasurface, we propose to use the all-dielectric material cylindrical structure to construct the coding unit. In view of the encoding of metasurface sequences in one-dimensional direction, the scattering angle of THz beam can only be controlled in a single direction, but not the scattering azimuth in three-dimensional (3D) space. We use different matrix encoding modes to achieve multi-beam and multi-angle control of terahertz beams in 3D space. Based on the cross-coding mode, the multi-beam separation of the beam scattering main lobe is obtained, and the azimuth angle of each separated main lobe beam is flexibly controlled.
The cavity method to protein design problem
Authors: Takahashi Tomoei , Chikenji George , Tokita Kei 
Published: October 2022

Abstract
In this study, we propose an analytic statistical mechanics approach to solve a fundamental problem in biological physics called protein design. Protein design is an inverse problem of protein structure prediction, and its solution is the amino acid sequence that best stabilizes a given conformation. Despite recent rapid progress in protein design using deep learning, the challenge of exploring protein design principles remains. Contrary to previous computational physics studies, we used the cavity method, an extension of the mean-field approximation that becomes rigorous when the interaction network is a tree. We found that for small two-dimensional lattice hydrophobic-polar protein models, the design by the cavity method yields results almost equivalent to those from the Markov chain Monte Carlo method with lower computational cost.
Thermal-mechanical coupling simulation analysis of submarine armored cable soil environment
Authors: Huang Youcong , Fu Zhiwei , Zheng Zhongnan , Lv Tian , Zhang Ying , Li Yaowei , Xv Jun , Mao Yulin 
Published: October 2022

Abstract
Due to the complex and diverse seabed environment, the coupling effect of high depth and temperature will seriously affect the operation stability of submarine cables. Therefore, the thermal-mechanical coupling model and inherent characteristics of submarine armored cables in soil environment are simulated and analyzed. Firstly, the influence of different buried depth and surrounding seawater temperature on cable temperature in soil environment is studied. Then the natural frequency of the cable is obtained by modal analysis. Since the low frequency vibration mainly occurs in the operation process, the high frequency vibration is not easy to excite and decay quickly, only the first eight order vibration is considered. The results show that it is beneficial to avoid the vibration near the resonance frequency, to lay in the relatively shallow position and to reduce the buried depth appropriately.
Imaging of hydroxyl radical (·OH) distributions using luminol water during irradiation with low-energy X-rays
Authors: Yamamoto Seiichi , Yabe Takuya , Hirano Yoshiyuki , Kataoka Jun 
Published: October 2022

Abstract
Reactive hydroxyl radicals (·OH) play important roles
in the biological effects of radiation exposure or radiation
therapy, and the distribution of ·OH in water during
irradiation is of interest to researchers. However, real-time
·OH distribution measurement during irradiation has so far not
been achieved due to the difficulty of detecting ·OH. To make
these distribution measurements possible, we attempted the imaging
of light emitted from luminol water during irradiation with
low-energy X-rays. Imaging of the light emitted from luminol water
was conducted using a cooled charge-coupled device (CCD) camera
during X-ray irradiation to luminol water at lower energy than the
Cherenkov-light threshold. The light emission of luminol water was
25 times higher than that of water, and clear images of light
distributions were measured for the luminol water. By carrying out
the imaging of luminol water with the addition of a radical
scavenger to the luminol water, we could confirm that the emitted
light was from ·OH produced in water. With this addition of
the radical scavenger, the light intensity decreased as the weight
of the scavenger increased. With these results, we confirmed that
the detected light distribution in luminol water could be attributed
to the ·OH produced by the X-ray irradiation.
Historical evolution and new trends for soil-intruder interaction modeling
Authors: Pirrone Serena R M , Del Dottore Emanuela , Mazzolai Barbara 
Published: October 2022

Abstract
Soil is a crucial resource for life on Earth. Every activity, whether natural or man-made, that interacts with the sub or deep soil can affect the land at large scales (e.g. geological risks). Understanding such interactions can help identify more sustainable and less invasive soil penetration, exploration, and monitoring solutions. Over the years, multiple approaches have been used in modeling soil mechanics to reveal soil behavior. This paper reviews the different modeling techniques used to simulate the interaction between a penetrating tool and the soil, following their use over time. Opening with analytical methods, we discuss the limitations that have partially been overcome by the finite element method (FEM). FEM models are capable of simulating more complex conditions and geometries. However, they require the continuum mechanics assumption. Hence, FEM analysis cannot simulate the discrete processes occurring during soil deformation (i.e. the separation and mixing of soil layers, the appearance of cracks, or the flow of soil particles). The discrete element method (DEM) has thus been adopted as a more promising modeling technique. Alongside models, experimental approaches have also been used to describe soil-intruder interactions, complementing or validating simulation results. Recently, bioinspired approaches have been considered promising to improve sustainability and reduce the invasiveness of classical penetration strategies. This review highlights how DEM-based models can help in studying the interaction mechanisms between bioinspired root-like artificial penetrometers and the soil. Bioinspired designs and the merging of multiple analysis approaches can offer new perspectives. These may be pivotal in the design of highly optimized soil robotic explorers capable of adapting their morphology and penetration strategies based on their surrounding conditions.