bluuebunny/crossref_metadata_2025 huggingface dataset:
Arbitrary wavefront uncertainty evaluation for the Shack–Hartmann wavefront sensor using physical optics propagation
Authors: Zhou Jichong , He Qiaozhi , Qu Yuan , Zhao Dineng , Wu Ziyin , Yang Jiamiao
Published: August 2023

The Shack–Hartmann wavefront sensor (SHWS) is a common option to characterize optical fields, due to its noninterference, high accuracy, and high-speed advantages. However, the current methods for evaluating measurement accuracy can only work for predefined standard wavefronts and cannot provide the error estimate for an arbitrary wavefront. Here, we propose an SHWS uncertainty evaluation approach for specific wavefronts based on the physical optics propagation. Our approach constructs a comprehensive SHWS model that incorporates twelve error sources. We analyzed the influence of different error sources on the measurement accuracy under the diffraction effect and reported that our model could achieve an accuracy of λ/559 under the ideal condition. In the experiment, we measured three different wavefronts and confined their uncertainty down to λ/65, λ/260, and λ/40, respectively. Our work may offer an effective solution for evaluating measurement errors in the high-accuracy wavefront measurement and provide a reliable, unbiased evaluation criterion.
High emissive contrast of adaptive, thin-film, tungsten-doped VO2 composites
Authors: Hunt G. M. , Miragliotta J. A. , Ginn J. , Warren A. P. , Shrekenhamer D. B.
Published: August 2023

There is a significant interest in developing advanced materials technologies that will reduce the consumption of fossil fuel resources. One efficient way of reducing energy consumption for heating and cooling applications is the development of a passive and adaptive thermal management system that radiates heat at high temperatures while providing insulation under cooler conditions. Vanadium dioxide (VO2) is a candidate material for this type of adaptive behavior since it transitions from a low temperature reflective state to a high temperature emissive state at 68 °C when deposited upon a dielectric-coated ground plane. Additionally, by doping VO2 with high valence tungsten (W6+), the transition temperature can be reduced to values that are close to room temperature (22 °C). In this Letter, W6+-doped VO2 multilayer composites are designed to utilize thin film interference in order to maximize the infrared (IR) emission contrast between the hot and cold states of VO2 while also reducing the transition temperature. Through careful engineering of the thickness and doping of the VO2 layer within the multilayer film, a 50% emissive contrast was maintained across the 8–13 μm spectral region, while the transition temperature was reduced from 68 °C in the undoped film to 29 °C in the 1.7 at. % W6+.
The COVID-19 baby bump in the United States
Authors: Bailey Martha J. , Currie Janet , Schwandt Hannes
Published: August 2023

We use natality microdata covering the universe of US. births for 2015 to 2021 and California births from 2015 through February 2023 to examine childbearing responses to the COVID-19 pandemic. We find that 60% of the 2020 decline in US fertility rates was driven by sharp reductions in births to foreign-born mothers although births to this group comprised only 22% of all US births in 2019. This decline started in January 2020. In contrast, the COVID-19 recession resulted in an overall “baby bump” among US-born mothers, which marked the first reversal in declining fertility rates since the Great Recession. Births to US-born mothers fell by 31,000 in 2020 relative to a prepandemic trend but increased by 71,000 in 2021. The data for California suggest that US births remained elevated through February 2023. The baby bump was most pronounced for first births and women under age 25, suggesting that the pandemic led some women to start families earlier. Above age 25, the baby bump was most pronounced for women aged 30 to 34 and women with a college education. The 2021 to 2022 baby bump is especially remarkable given the large declines in fertility rates that would have been projected by standard statistical models.
Alignment variations in the diachrony of Basque
Authors: Mounole Céline
Published: August 2023

Besides highly grammaticalized analytic verb forms that constitute the system’s main tense, aspect, and mood
forms, Basque has a handful of less grammaticalized periphrases for secondary aspectual and modal meanings. In both older and more
recent texts, some of these periphrases have been reanalyzed as monoclausal and readjusted in accordance with the auxiliated
verb’s argument structure. This readjustment or actualization process involves changes in two respects: case-marking and
indexation through auxiliary change. The reanalysis and actualization of theses periphrases seem to be driven by analogy with
highly extended and frequent analytic verb forms. With regard to their actualization, it seems to depend on three factors: word
order, valency of the auxiliated verb, and plural patient agreement.
The irreversibility of relativistic time-dilation
Authors: Basso Marcos L W , Maziero Jonas , Céleri Lucas C
Published: August 2023

The fluctuation relations, which characterize irreversible processes in nature, are among the most important results in non-equilibrium physics. In short, these relations say that it is exponentially unlikely for us to observe a time-reversed process and, thus, establish the thermodynamic arrow of time pointing from low to high entropy. On the other hand, fundamental physical theories are invariant under time-reversal symmetry. Although in Newtonian and quantum physics the emergence of irreversible processes, as well as fluctuation relations, is relatively well understood, many problems arise when relativity enters the game. In this work, by considering a specific class of spacetimes, we explore the question of how the time-dilation effect enters into the fluctuation relations. We conclude that a positive entropy production emerges as a consequence of both the special relativistic and the gravitational (enclosed in the equivalence principle) time-dilation effects.
Constraints on charged symmergent black hole from shadow and lensing
Authors: Puliçe Beyhan , Pantig Reggie C , Övgün Ali , Demir Durmuş
Published: August 2023

In this paper, we report on exact charged black hole solutions in symmergent gravity with Maxwell field. Symmergent gravity induces the gravitational constant G, quadratic curvature coefficient

c

O

, and the vacuum energy

V

O

from the flat spacetime matter loops. In the limit in which all fields are degenerate in mass, the vacuum energy

V

O

can be expressed in terms of G and

c

O

. We parametrize deviation from this limit by a parameter

α
ˆ

such that the black hole spacetime is de Sitter (dS) for

α
ˆ

<
1

and anti-de Sitter (AdS) for

α
ˆ

>
1

. In our analysis, we study horizon formation, shadow cast and gravitational lensing as functions of the black hole charge, and find that there is an upper bound on the charge. At relatively low values of charge, applicable to astronomical black holes, we determine constraints on

c

O

and

α
ˆ

using the Event Horizon Telescope (EHT) data from Sgr. A* and M87*. We apply these constraints to reveal how the shadow radius behaves as the observer distance

r

O

varies. It is revealed that black hole charge directly influences the shadow silhouette, but the symmergent parameters have a tenuous effect. We also explored the weak field regime by using the Gauss–Bonnet theorem to study the weak deflection angle caused by the M87* black hole. We have found that impact parameters comparable to the actual distance D = 16.8 Mpc show the potential detectability of such an angle through advanced astronomical telescopes. Overall, our results provide new insights into the behavior of charged black holes in the context of symmergent gravity and offer a new way to test these theories against observational data.
Effect of solar free oscillations on TianQin’s range acceleration noise
Authors: Liu Kun , Luo Chengjian , Zhang Xuefeng
Published: August 2023

TianQin is a proposed space-based gravitational-wave detector mission to be deployed and operated in high Earth orbits. As a sequel to Zhang et al (2021 Phys. Rev. D 103 062001), we investigate a type of ‘orbital noise’ in TianQin’s range acceleration that is caused by gravitational perturbation associated with solar free oscillations. Frequencies of such oscillations are typically within TianQin’s measurement band of 0.1 mHz–1 Hz, and the disturbance level needs careful assessment. By using high-precision orbit propagation and adding the Sun’s time-variable oblateness J
2 to detailed gravity-field models, we examine the effect in the frequency domain and show that the solar free oscillation noise is expected to be two orders of magnitude lower than the noise requirement on single links and hence has little impact on the mission.
Petrov classification of analogue spacetimes
Authors: Baak Sang-Shin , Datta Satadal , Fischer Uwe R
Published: August 2023

In an effort to invariantly characterize the conformal curvature structure of analogue spacetimes built from a nonrelativistic fluid background, we determine the Petrov type of a variety of laboratory geometries. Starting from the simplest examples, we increase the complexity of the background, and thereby determine how the laboratory fluid symmetry affects the corresponding Petrov type in the analogue spacetime realm of the sound waves. We find that for more complex flows isolated hypersurfaces develop, which are of a Petrov type differing from that of the surrounding fluid. Finally, we demonstrate that within the incompressible background approximation, as well as for all compressible quasi-one-dimensional flows, the only possible Petrov types are the algebraically general type I and the algebraically special types O and D.
Irreversibility of sudden processes: compression versus expansion in perfect gases
Authors: Vallejo Andrés , Osorio Matías
Published: August 2023

We focus on the study of the processes undergone by a perfect gas when the external pressure is suddenly modified. The analysis shows that, from the second law perspective, there is a non-evident asymmetry between the processes of compression and expansion between the same pressures, which is manifested through different levels of entropy production. If the system remains in contact with a thermal reservoir during the processes this asymmetry is remarkable, since while entropy grows linearly with the relative change of pressure during the compression, the relation between those variables is logarithmic during the expansion.
Impurity-driven simultaneous size and crystallinity control of metal nanoparticles
Authors: Shiomi Shohei
Published: August 2023

Both the size and crystallinity should be optimized for practical applications utilizing metallic nanoparticles because they strongly influence the nanoparticles property. Herein a liquid phase chemical reduction method controls the defects (crystallinity) in metallic Cu nanoparticles simply and easily. Although the addition of an impurity substance, which cannot be thermodynamically alloyed with Cu, reduces the crystallinity of synthesized Cu nanoparticles, it also affects the deposition behavior, and consequently, the nanoparticle size changes unexpectedly. Therefore, a precise control of the synthesis condition is required to synthesize the nanoparticles having optimal size and crystallinity. To clarify the nanoparticle formation mechanism in an impurity-containing solution, the catalytic activity of the reductant and the redox potential change due to the metastable product are electrochemically evaluated to reveal the correlation between nanoparticle formation behavior and synthesis condition. Finally, the synthesis of two types of Cu nanoparticles, which have similar sizes but different crystallinities is demonstrated. This simple nanomaterial design approach to control the crystallinity and the interpretation of the deposition process in an impurity-containing condition should be widely applicable to metallic nanoparticle syntheses.
MCSF-Net: a multi-scale channel spatial fusion network for real-time polyp segmentation
Authors: Liu Weikang , Li Zhigang , Xia Jiaao , Li Chunyang
Published: August 2023

Colorectal cancer is a globally prevalent cancer type that necessitates prompt screening. Colonoscopy is the established diagnostic technique for identifying colorectal polyps. However, missed polyp rates remain a concern. Early detection of polyps, while still precancerous, is vital for minimizing cancer-related mortality and economic impact. In the clinical setting, precise segmentation of polyps from colonoscopy images can provide valuable diagnostic and surgical information. Recent advances in computer-aided diagnostic systems, specifically those based on deep learning techniques, have shown promise in improving the detection rates of missed polyps, and thereby assisting gastroenterologists in improving polyp identification. In the present investigation, we introduce MCSF-Net, a real-time automatic segmentation framework that utilizes a multi-scale channel space fusion network. The proposed architecture leverages a multi-scale fusion module in conjunction with spatial and channel attention mechanisms to effectively amalgamate high-dimensional multi-scale features. Additionally, a feature complementation module is employed to extract boundary cues from low-dimensional features, facilitating enhanced representation of low-level features while keeping computational complexity to a minimum. Furthermore, we incorporate shape blocks to facilitate better model supervision for precise identification of boundary features of polyps. Our extensive evaluation of the proposed MCSF-Net on five publicly available benchmark datasets reveals that it outperforms several existing state-of-the-art approaches with respect to different evaluation metrics. The proposed approach runs at an impressive ∼45 FPS, demonstrating notable advantages in terms of scalability and real-time segmentation.
All-top-contact 0.59 eV InGaAs thermophotovoltaic cells and modules
Authors: Tang Liangliang , Yin Long , Shao Jianxiong , Tang Yili , Liu Yonghui
Published: August 2023

InGaAs cells are ideal converters for low temperature thermophotovoltaic power generation systems. Commonly, the positive and negative electrodes of InGaAs cells are deposited on the top and bottom of the cells, respectively. In the engineering of level modules, solder strips are used to connect the top and bottom of adjacent cells, the distance between the cells is considerable in order to prevent short circuits from the side wall of the cells, and the area ratio of cells to modules is relatively low. In this paper, we design and fabricate a novel all-top-contact InGaAs cell, with the positive electrode deposited on top of the p-InGaAs epitaxial layer, and the negative electrode deposited on top of the n-InPAs-grade epitaxial layer by precise etching of the p–n junction layers. The novel all-top-contact cells show good efficiencies compared to traditional cells with top-and-bottom electrodes under the same testing conditions. Novel flat and compact cell modules were fabricated using all-top-contact InGaAs cells, the distance between the adjacent cells was controlled within tens of microns, and the area ratio of cells to modules was improved efficiently.
Dynamics of polaron formation in 1D Bose gases in the strong-coupling regime
Authors: Will Martin , Fleischhauer Michael
Published: August 2023

We discuss the dynamics of the formation of a Bose polaron when an impurity is injected into a weakly interacting one-dimensional Bose condensate. While for small impurity-boson couplings this process can be described within the Froehlich model as generation, emission and binding of Bogoliubov phonons, this is no longer adequate if the coupling becomes strong. To treat this regime we consider a mean-field approach beyond the Froehlich model which accounts for the backaction to the condensate, complemented with Truncated Wigner simulations to include quantum fluctuation. For the stationary polaron we find a periodic energy-momentum relation and non-monotonous relation between impurity velocity and polaron momentum including regions of negative impurity velocity. Studying the polaron formation after turning on the impurity-boson coupling quasi-adiabatically and in a sudden quench, we find a very rich scenario of dynamical regimes. Due to the build-up of an effective mass, the impurity is slowed down even if its initial velocity is below the Landau critical value. For larger initial velocities we find deceleration and even backscattering caused by emission of density waves or grey solitons and subsequent formation of stationary polaron states in different momentum sectors. In order to analyze the effect of quantum fluctuations we consider a trapped condensate to avoid 1D infrared divergencies. Using Truncated Wigner simulations in this case we show under what conditions the influence of quantum fluctuations is small.
A large magnetocaloric effect and thermoelectric properties of anti-perovskite SnMn3N material: a DFT study and monte carlo simulation
Authors: Alaoui Y Charif , Jabar A , Tahiri N , El Bounagui O , Ez-Zahraouy H
Published: August 2023

In this paper, we have investigated the electronic, magnetic, magnetocaloric, and thermoelectric properties of the anti-perovskite material SnMn3N using density functional theory (DFT) calculations and Monte Carlo simulations. We observed a second-order phase transition at a temperature of T = 480 K. Firstly, we studied the structural and electronic properties of the material. The crystal structure of this material is cubic with a spatial group of Pm3m. Secondly, we examined the magnetocaloric properties of this metallic compound by calculating the magnetic entropy change

(

∆
S

max

) and the relative cooling power (RCP) under different magnetic fields: 1 T, 3 T, and 5 T. The values obtained for these parameters were 19.382 J kg−1 K−1 and 203.466 J kg−1 at an external magnetic field of 5 T, respectively. Lastly, we also analyzed the thermoelectric properties of the compound using the BoltzTraP and Gibbs2 methods. We determined that the Seebeck coefficient at room temperature is 17.7766 μV K−1) and 23.099 μV K−1) in the transition phase at 480 K. We are currently conducting measurements of the thermal conductivity and power factor of this material at both room temperature and the transition temperature of 480 K. In summary, this study provides a deeper understanding of the magnetocaloric, thermoelectric, and thermal properties of the SnMn3N material, which can potentially be utilized in the development of more efficient cooling systems.
Independent wavefront manipulation of broadband spin-decoupled metasurfaces based on equivalent circuit model
Authors: Chen Xinbo , An Cheng , Zhou Jianyang , Li Weiwen
Published: August 2023

Various functional meta-devices have exhibited powerful manipulation of orbital angular momentum spectrums, but they are still faced with the issue of inherent spin-correlated characteristic and lack of effective method to design metasurface. In this work, a broadband spin-decoupled metasurface is presented to realize independent regulation of dual circularly polarized waves. Based on the transmission line theory, an equivalent circuit model of meta-atom is proposed to establish the relationship between reflection coefficients and structural parameters. By utilizing the model, a group of meta-atoms has been designed with a step phase difference of 45°, which can form a 3-bit coding metasurface. The proposed meta-atoms have a broad frequency band covering 11.56 − 18.17 GHz (44.5%). Moreover, the bifunctional reflection-type metasurfaces are constructed for producing the vortex waves along the +z axis, the off-axis pencil beams, and their synthetic beams. Based on the Fourier transform analysis, the mode purity and the electric field distribution of the generated beams are discussed in detail. The experimental measurements have good agreement with the simulation results, thus revealing the effectiveness of the proposed methodology to design metasurface.
First-principles study of the phase stability and elastic properties of TiVNbMoM (M = Al, Sc, Ni and Cu) high entropy alloys
Authors: Al-Zoubi N
Published: August 2023

The ab initio exact muffin-tin orbitals (EMTO) method in combination with the coherent potential approximation (CPA) were used to study the influence of alloying elements M = Al, Sc, Ni and Cu on the phase stability, lattice constants, elastic constants, polycrystalline elastic moduli and electronic structure of equiatomic and non-equiatomic TiVNbMoM refractory high entropy alloys. The agreement between our results and the available experimental and theoretical data is quite good. It was found that the equiatomic systems are stable in the body-centered cubic (bcc) structure. Alloying elements decrease the stability of the bcc against the face-centered cubic (fcc) and the hexagonal close-packed (hcp) structures. Scandium enlarges the lattice constants of equiatomic and non-equiatomic systems significantly. According to the calculated bulk modulus to shear modulus, Poisson’s ratio and Vickers hardness, all studied equiatomic and non-equiaomic systems are found to be ductile. However, alloying elements Al, Ni and Cu reduce the ductility and improve the hardness of equiatomic and non-equiatomic TiVNbMoM systems, while the ductility (hardness) of non-equiatomic systems enhances (reduces) by substitution with Sc element. The present theoretical results provide insight for the design and improvement of high entropy alloys and complete information on the alloying effects.
Effect of short-term plasticity on working memory
Authors: Yang 杨 Fan 帆 , Liu 刘 Feng 锋
Published: August 2023

The way in which persistent firing activity and synaptic plasticity are orchestrated to underlie working memory in recurrent neural networks is not fully understood. Here, we build a continuous attractor network of pyramidal cells and interneurons to simulate an oculomotor delayed response task. Both short-term facilitation (STF) and short-term depression (STD) manifest at synapses between pyramidal cells. The efficacy of individual synapses depends on the time constants of STF and STD as well as the presynaptic firing rate. Self-sustained firing activity (i.e., a bump attractor) during the delay period encodes the cue position. The bump attractor becomes more robust against random drifts and distractions with enhancing STF or reducing STD. Keeping STF and STD at appropriate levels is crucial for optimizing network performance. Our results suggest that, besides slow recurrent excitation and strong global inhibition, short-term plasticity plays a prominent role in facilitating mnemonic behavior.
Efficient transfer of metallophosphor excitons via confined polaritons in organic nanocrystals
Authors: Lu 芦 Wenbin 文斌 , Chen 陈 Yongcong 永聪 , Yang 杨 Xuyun 旭云 , Ao 敖 Ping 平
Published: August 2023

We investigate the transfer of phosphorescent energy between co-assembled metallophosphors in crystalline nanostructures [Angew. Chem. Int. Ed.
57 7820 (2018) and J. Am. Chem. Soc.
140 4269 (2018)]. Neither Dexter’s nor Förster’s mechanism of resonance energy transfer (RET) could account fully for the observed rates, which exceed 85% with significant temperature dependence. But there exists an alternative pathway on RET mediated by intermediate states of resonantly confined exciton–polaritons. Such a mechanism was used to analyze artificial photosynthesis in organic fluorescents [Phys. Rev. Lett.
122 257402 (2019)]. For metallophosphors, the confined modes act as extended states lying between the molecular S1 and T1 states, offering a bridge for the long-lived T1 excitons to migrate from donors to acceptors. Population dynamics with parameters taken entirely based on experiments fits the observed lifetimes of phosphorescence across a broad range of doping and temperature.
Tunable dispersion relations manipulated by strain in skyrmion-based magnonic crystals
Authors: Jin 金 Zhao-Nian 兆年 , He 何 Xuan-Lin 宣霖 , Yu 于 Chao 超 , Fang 方 Henan 贺男 , Chen 陈 Lin 琳 , Tao 陶 Zhi-Kuo 志阔
Published: August 2023

We theoretically investigate the propagation characteristics of spin waves in skyrmion-based magnonic crystals. It is found that the dispersion relation can be manipulated by strains through magneto-elastic coupling. Especially, the allowed bands and forbidden bands in dispersion relations shift to higher frequency with strain changing from compressive to tensile, while shifting to lower frequency with strain changing from tensile to compressive. We also confirm that the spin wave with specific frequency can pass the magnonic crystal or be blocked by tuning the strains. The result provides an advanced platform for studying the tunable skyrmion-based spin wave devices.
Diamond growth in a high temperature and high pressure Fe–Ni–C–Si system: Effect of synthesis pressure
Authors: Liu 刘 Yang 杨 , Wang 王 Zhiwen 志文 , Li 李 Bowei 博维 , Zhao 赵 Hongyu 洪宇 , Wang 王 Shengxue 胜学 , Chen 陈 Liangchao 良超 , Ma 马 Hongan 红安 , Jia 贾 Xiaopeng 晓鹏
Published: August 2023

Pressure is one of the necessary conditions for diamond growth. Exploring the influence of pressure on growth changes in silicon-doped diamonds is of great value for the production of high-quality diamonds. This work reports the morphology, impurity content and crystal quality characteristics of silicon-doped diamond crystals synthesized under different pressures. Fourier transform infrared spectroscopy shows that with the increase of pressure, the nitrogen content in the C- center inside the diamond crystal decreases. X-ray photoelectron spectroscopy test results show the presence of silicon in the diamond crystals synthesized by adding silicon powder. Raman spectroscopy data shows that the increase in pressure in the Fe–Ni–C–Si system shifts the Raman peak of diamonds from 1331.18 cm−1 to 1331.25 cm−1, resulting in a decrease in internal stress in the crystal. The half-peak width decreased from 5.41 cm−1 to 5.26 cm−1, and the crystallinity of the silicon-doped diamond crystals improved, resulting in improved quality. This work provides valuable data that can provide a reference for the synthesis of high-quality silicon-doped diamonds.
Combination of density-clustering and supervised classification for event identification in single-molecule force spectroscopy data
Authors: Yuan 袁 Yongyi 泳怡 , Liang 梁 Jialun 嘉伦 , Tan 谭 Chuang 创 , Yang 杨 Xueying 雪滢 , Yang 杨 Dongni 东尼 , Ma 马 Jie 杰
Published: August 2023

Single-molecule force spectroscopy (SMFS) measurements of the dynamics of biomolecules typically require identifying massive events and states from large data sets, such as extracting rupture forces from force-extension curves (FECs) in pulling experiments and identifying states from extension-time trajectories (ETTs) in force-clamp experiments. The former is often accomplished manually and hence is time-consuming and laborious while the latter is always impeded by the presence of baseline drift. In this study, we attempt to accurately and automatically identify the events and states from SMFS experiments with a machine learning approach, which combines clustering and classification for event identification of SMFS (ACCESS). As demonstrated by analysis of a series of data sets, ACCESS can extract the rupture forces from FECs containing multiple unfolding steps and classify the rupture forces into the corresponding conformational transitions. Moreover, ACCESS successfully identifies the unfolded and folded states even though the ETTs display severe nonmonotonic baseline drift. Besides, ACCESS is straightforward in use as it requires only three easy-to-interpret parameters. As such, we anticipate that ACCESS will be a useful, easy-to-implement and high-performance tool for event and state identification across a range of single-molecule experiments.
Computational and experimental investigations of a microfluidic mixer for efficient iodine extraction using carbon tetrachloride enhanced with gas bubbles
Authors: Muhammad Kashif Siddique , Lin 孙 Sun 林 , Songjing 李 Li 松晶
Published: August 2023

Numerous studies have been conducted on microfluidic mixers in various microanalysis systems, which elucidated the manipulation and control of small fluid volumes within microfluidic chips. These studies have demonstrated the ability to control fluids and samples precisely at the microscale. Microfluidic mixers provide high sensitivity for biochemical analysis due to their small volumes and high surface-to-volume ratios. A promising approach in drug delivery is the rapid microfluidic mixer-based extraction of elemental iodine at the micro level, demonstrating the versatility and the potential to enhance diagnostic imaging and accuracy in targeted drug delivery. Micro-mixing inside microfluidic chips plays a key role in biochemical analysis. The experimental study describes a microfluidic mixer for extraction of elemental iodine using carbon tetrachloride with a gas bubble mixing process. Gas bubbles are generated inside the microcavity to create turbulence and micro-vortices resulting in uniform mixing of samples. The bubble mixing of biochemical samples is analyzed at various pressure levels to validate the simulated results in computational fluid dynamics (CFD). The experimental setup includes a high-resolution camera and an air pump to observe the mixing process and volume at different pressure levels with time. The bubble formation is controlled by adjusting the inert gas flow inside the microfluidic chip. Microfluidic chip-based gas bubble mixing effects have been elaborated at various supplied pressures.
Determination of the resonant parameters of excited vector strangenia with
data*
Authors: Zhu 朱 Wenjing 文静 , Wang 王 Xiaolong 小龙
Published: August 2023

We determine the resonant parameters of the vector states

and

by performing a combined fit to the

cross sections from the threshold to

measured by the BaBar, Belle, BESIII, and CMD-3 experiments. The mass

and width

are obtained for

, and the mass

and width

are obtained for

. The statistical significance of

is

. Depending on the interference between

,

, and a non-resonant

amplitude in the nominal fit, we obtain four solutions and

,

,

or

, and

,

,

or

. We also search for the production of

, and the significance is only

. We then determine the upper limit of

at the 90% confidence level.
CP asymmetry from the resonance effect of the B meson decay process with π and K final states*
Authors: Yuan 原 Xi-Liang 喜亮 , Lü 吕 Gang 刚 , Wang 王 Na 娜 , Zhang 张 Li-Ying 丽英 , Guo 郭 Xin-Heng 新恒
Published: August 2023

We present the novel

resonance, which generates a strong phase associated with vector meson resonances, leading to significant CP asymmetry in the interference region. The

,

, and

resonances arise from the mixing of the vector mesons ϕ, ρ, and ω. We calculate the CP asymmetry from the decay mode of

. Meanwhile, the localized CP asymmetries are presented and a detailed analysis is performed. The CP asymmetry from the decay mode of

is also presented in our framework, which is highly consisted with that of the LHC experiment. The introduced CP asymmetry can provide a favorable theoretical support for experimental exploration in the future.
Preparation and performance study of multichannel PLA artificial nerve conduits
Authors: Wang Shanlong , Wang Yuyu , Chen Biling , Zhao Mingda , Song Gongji , Wang Jiannan , Xu Jianmei
Published: August 2023

Compared with single-channel nerve conduits, multichannel artificial nerve conduits are more beneficial for repairing damaged peripheral nerves of long-distance nerve defects. Multichannel nerve conduits can be fabricated by the mold method and the electrospinning method but with disadvantages such as low strength and large differences in batches, while the braiding method can solve this problem. In this study, polylactic acid yarns were used as the braiding yarn, and the number of spindles during braiding was varied to achieve 4, 5, 6, 7 and 8 multichannel artificial nerve conduits. A mathematical model of the number of braiding yarn spindles required to meet certain size specification parameters of the multichannel conduit was established. The cross-sectional morphology and mechanical properties of the conduits were characterized by scanning electron microscopy observation and mechanical testing; the results showed that the multichannel structure was well constructed; the tensile strength of the multichannel conduit was more than 30 times that of the rabbit tibial nerve. The biocompatibility of the conduit was tested; the in vitro cell culture results proved that the braided multichannel nerve conduits were nontoxic to Schwann cells, and the cell adhesion and proliferation were optimal in the 4-channel conduit among the multichannel conduits, which was close to the single-channel conduit.
Quantifying impact-relevant heatwave durations
Authors: Polt Kelley De , Ward Philip J , de Ruiter Marleen , Bogdanovich Ekaterina , Reichstein Markus , Frank Dorothea , Orth René
Published: August 2023

Heatwaves are weather hazards that can influence societal and natural systems. Recently, heatwaves have increased in frequency, duration, and intensity, and this trend is projected to continue as a consequence of climate change. The study of heatwaves is hampered by the lack of a common definition, which limits comparability between studies. This applies in particular to the considered time scale for utilised metrics. Here, we study which durations of heatwaves are most impact-relevant for various types of impacts. For this purpose, we analyse societal metrics related to health (heat-related hospitalisations, mortality) and public attention (Google trends, news articles) in Germany. Country-averaged temperatures are calculated for the period of 2010–2019 and the warmest periods of all time scales between 1 and 90 days are selected. Then, we assess and compare the societal response during those periods to identify the heatwave durations with the most pronounced impacts. Note that these durations are based on average temperatures across the given time frame while individual days may be less warm. The results differ slightly between the considered societal metrics but indicate overall that heatwaves induce the strongest societal response at durations between 2 weeks and 2 months for Germany. Finally, we show that heatwave duration affects the societal response independent of, and additionally to, heatwave temperatures. This finding highlights the relevance of making informed choices on the considered time scale in heatwave analyses. The approach we introduce here can be extended to other societal indices, countries, and hazard types to reveal more meaningful definitions of climate extremes to guide future research on these events.
Artificial intelligence can dynamically adjust strategies for auxiliary diagnosing respiratory diseases and analyzing potential pathological relationships
Authors: Zhang Quan , Chen Binyue , Liu Guohua
Published: August 2023

Respiratory diseases are one of the leading causes of human death and exacerbate the global burden of non-communicable diseases. Finding a method to assist clinicians pre-diagnose these diseases is an urgent task. Existing artificial intelligence-based methods can improve the clinical diagnosis efficiency, but still face challenges. For example, the lack of interpretability, the problem of information redundancy or missing caused by only using static data, the difficulty of model to learn the interdependence between features, and the performance of model is limited by sparse datasets, etc. To alleviate these problems, we propose a novel RQPA-Net. It consists of Q&A diagnosis module (QAD) and pathological inference module (PI). The QAD is responsible for interacting with patients, adjusting inquiry strategies dynamically and collecting effective information for disease diagnosis. The designed multi-subspace network can alleviate the problem that classical method is difficult to understand the interdependence between features. The deep reinforcement learning designed also can alleviate the problem of classical methods lack of interpretability. The PI is responsible for reasoning potential pathological relationships between diseases or symptoms based on existing knowledge. Through integrating the advantages of deep learning and reinforcement learning techniques, PI can handle sparse datasets. Finally, for auxiliary diagnosis, the model achieves 0.9780 ± 0.0002 Recall, 0.9778 ± 0.0003 Acc, 0.9779 ± 0.0003 Precision and 0.9780 ± 0.0003 F1-score on the test set. In terms of assisting pathological analysis, compared with the end-to-end model, our model achieves higher comprehensive performance on different tasks and datasets with different degrees of sparsity. Even in sparse datasets, it can effectively infer potential associations between diseases or symptoms, and has higher potential clinical application. In this paper, we propose a novel network structure, which can not only assist doctors in diagnosing diseases, but also contribute to explore the potential disease mechanisms. It provides a new perspective for integrating AI technology and clinical practice.
Exploring the influence of nanocavity alignment on slow light generation via multiple EIT and Fano resonances in square lattice plasmonic silver nanostructures
Authors: Khan Haseeb Ahmad , Khan Adnan Daud , Shah Syed Waqar , Chaudhry Muhammad Rehan , Azeem Farhan , Ahmed Salman , Ahmad Khurshid
Published: August 2023

In this paper, we present a comprehensive investigation of multiple electromagnetic induced transparency (EIT) and Fano resonances in a square lattice plasmonic nanostructure, which is composed of four silver slabs arranged in a square configuration, with each slab featuring a cylindrical nanocavity at its center. Initially, symmetric structures were analyzed to explore the potential for achieving EIT effects. Subsequently, we introduce deliberate symmetry breaking by precisely aligning the nanocavity in a controlled manner, first within a single slab, then in combinations of two, three, and all four slabs simultaneously. This controlled alignment strategy enabled the relaxation of dipole coupling selection rules, leading to the mixing of dipole and higher-order modes. The interaction between these modes resulted in the generation of multiple EITs and Fano resonances in the optical spectrum. Furthermore, the effective group index was evaluated for the optimal results obtained in the single, double, triple, and four symmetry reduced structures. High group index values were observed in the vicinity of the EIT and Fano resonances, with a remarkable maximum group index value of 6900 achieved within the EIT window. These findings highlight the significant potential of these structures in the design of slow light devices and sensitive sensors.
Preparation of corrosion-resistant surface of magnesium alloy and its performance study
Authors: Li Shimeng , Sun Baofu
Published: August 2023

The susceptibility of magnesium alloys to corrosion has hindered the wide application of magnesium alloys. A natural green method was proposed in this study to prepare a corrosion-resistant film layer whose main substance is MgO on the magnesium alloy substrate by a two-step hydrothermal method combining water steaming and annealing treatment. The morphology, composition, structure and corrosion resistance of the coating were investigated by SEM, FTIR, XRD and electrochemical methods. The results showed that the prepared coating has excellent corrosion resistance, reducing corrosion current by about four orders of magnitude compared with the bare Mg alloy substrate, and the corrosion potential and corrosion rate are also increased in different degree.
Interaction of 1/2〈111〉 interstitial dislocation loop with hydrogen and helium in tungsten: molecular dynamics simulation
Authors: Xu Bai-Chuan , Li Xiao-Chun , Wang Jinlong , Li Ya-Wen , Pan Xin-Dong , Lyu Yi-Ming , Zhou Hai-Shan , Luo Guang-Nan
Published: August 2023

The interaction of hydrogen and helium atoms with 1/2 〈111〉 interstitial dislocation loop in tungsten is investigated by molecular dynamics simulation. The binding energies of hydrogen and helium atoms around dislocation loop are calculated by molecular statics method. The results show that the outer region of the loop is attractive to the two atoms and the inner region is repulsive. Notably, the maximum binding energies are located in the core region of the dislocation loop. We have also studied the influence factors of the interaction between the dislocation loop and two atoms: free volume, lattice distortion degree, the radius and shape of the dislocation loop. The results show that large free volume benefits the retention of hydrogen and helium atoms, especially for helium. The less lattice distortion caused by the impurity atom, the more favorable for the dislocation loop to trap it. In addition, the larger dislocation loop with higher defect concentration results in stronger capture ability for the hydrogen and helium atoms. The different dislocation loop shapes lead to different binding energy distribution patterns. And the hydrogen and helium atoms tend to occupy the groove region of the concave dislocation loop. Finally, we employ the nudged elastic band theory and dynamics method to investigate the diffusion pattern of the hydrogen atom in the dislocation loop and find that the hydrogen atom tends to migrate spirally around dislocation line. Based on the obtained results, a reasonable interpretation of the interaction behaviors between the dislocation loop with hydrogen and helium atoms are discussed, which can provide essential parameters for mesoscopic scale simulations.
Microstructure and properties study of Mg2-xYxNi0.9Co0.1 (x = 0, 0.1, 0.2, 0.3) hydrogen storage alloys
Authors: Li Defa , Huang Feng , Zhang Wei , Li Yanzhou , Zhou Binjun
Published: August 2023

To enhance the hydrogen storage performance of Mg-Ni system alloys, multi-elemental alloys incorporating Y element, namely Mg2-xYxNi0.9Co0.1 (x = 0, 0.1, 0.2, 0.3), were synthesized through ball milling and sintering. The microstructures of Mg2-xYxNi0.9Co0.1 (x = 0, 0.1, 0.2, 0.3) alloys were characterized using XRD and SEM/EDS techniques, and the hydrogen storage properties of Mg2Ni0.9Co0.1 and Mg1.7Y0.3Ni0.9Co0.1 alloys were evaluated via the Sieverts method. At a sintering temperature of 500 °C, the Y element existed in the form of Y/Y2O3 phases and displayed no reactivity with other alloy constituents. The addition of Y enhanced the activation performance of Mg-Ni system alloys, because it takes 2 times for Mg1.7Y0.3Ni0.9Co0.1 alloy to complete activation, while Mg2Ni0.9Co0.1 needs 3, albeit causing a slight reduction from 3.6 wt% to 3.2 wt% in the hydrogen storage capacity when Y replaced Mg. The enthalpy of hydrogen desorption of Mg1.7Y0.3Ni0.9Co0.1 alloy was 57.4 kJ mol−1 H2, which was significantly lower than that of Mg2Ni0.9Co0.1 (68.0 kJ mol−1 H2) and Mg2Ni alloy (64.4 kJ mol−1 H2), indicating improved thermodynamic properties. Moreover, the apparent activation energy of Mg2Ni0.9Co0.1 (71.48 kJ mol−1 H2) was lower than that of Mg1.7Y0.3Ni0.9Co0.1 (83.62 kJ mol−1 H2), implying that the addition of Y reduced the kinetic properties.
Error scaling laws for kernel classification under source and capacity conditions
Authors: Cui Hugo , Loureiro Bruno , Krzakala Florent , Zdeborová Lenka
Published: August 2023

In this manuscript we consider the problem of kernel classification. While worst-case bounds on the decay rate of the prediction error with the number of samples are known for some classifiers, they often fail to accurately describe the learning curves of real data sets. In this work, we consider the important class of data sets satisfying the standard source and capacity conditions, comprising a number of real data sets as we show numerically. Under the Gaussian design, we derive the decay rates for the misclassification (prediction) error as a function of the source and capacity coefficients. We do so for two standard kernel classification settings, namely margin-maximizing support vector machines and ridge classification, and contrast the two methods. We find that our rates tightly describe the learning curves for this class of data sets, and are also observed on real data. Our results can also be seen as an explicit prediction of the exponents of a scaling law for kernel classification that is accurate on some real datasets.
Reflection equivariant quantum neural networks for enhanced image classification
Authors: T West Maxwell , Sevior Martin , Usman Muhammad
Published: August 2023

Machine learning is among the most widely anticipated use cases for near-term quantum computers, however there remain significant theoretical and implementation challenges impeding its scale up. In particular, there is an emerging body of work which suggests that generic, data agnostic quantum machine learning (QML) architectures may suffer from severe trainability issues, with the gradient of typical variational parameters vanishing exponentially in the number of qubits. Additionally, the high expressibility of QML models can lead to overfitting on training data and poor generalisation performance. A promising strategy to combat both of these difficulties is to construct models which explicitly respect the symmetries inherent in their data, so-called geometric quantum machine learning (GQML). In this work, we utilise the techniques of GQML for the task of image classification, building new QML models which are equivariant with respect to reflections of the images. We find that these networks are capable of consistently and significantly outperforming generic ansatze on complicated real-world image datasets, bringing high-resolution image classification via quantum computers closer to reality. Our work highlights a potential pathway for the future development and implementation of powerful QML models which directly exploit the symmetries of data.
Automated gadget discovery in the quantum domain
Authors: Trenkwalder Lea M , López-Incera Andrea , Poulsen Nautrup Hendrik , Flamini Fulvio , Briegel Hans J
Published: August 2023

In recent years, reinforcement learning (RL) has become increasingly successful in its application to the quantum domain and the process of scientific discovery in general. However, while RL algorithms learn to solve increasingly complex problems, interpreting the solutions they provide becomes ever more challenging. In this work, we gain insights into an RL agent’s learned behavior through a post-hoc analysis based on sequence mining and clustering. Specifically, frequent and compact subroutines, used by the agent to solve a given task, are distilled as gadgets and then grouped by various metrics. This process of gadget discovery develops in three stages: First, we use an RL agent to generate data, then, we employ a mining algorithm to extract gadgets and finally, the obtained gadgets are grouped by a density-based clustering algorithm. We demonstrate our method by applying it to two quantum-inspired RL environments. First, we consider simulated quantum optics experiments for the design of high-dimensional multipartite entangled states where the algorithm finds gadgets that correspond to modern interferometer setups. Second, we consider a circuit-based quantum computing environment where the algorithm discovers various gadgets for quantum information processing, such as quantum teleportation. This approach for analyzing the policy of a learned agent is agent and environment agnostic and can yield interesting insights into any agent’s policy.