Using a covariant and angular-momentum-conserved chiral transport model, which takes into account the spin-orbit interactions of chiral fermions in their scatterings via the side jumps, we study the ...quark spin polarization in quark matter. For a system of rotating and unpolarized massless quarks in an expanding box, we find that side jumps can dynamically polarize the quark spin and result in a final quark spin polarization consistent with that of thermally equilibrated massless quarks in a self-consistent vorticity field. For the quark matter produced in noncentral relativistic heavy ion collisions, we find that in the medium rest frame both the quark local spin polarizations in the direction perpendicular to the reaction plane and along the longitudinal beam direction show an azimuthal angle dependence in the transverse plane similar to those observed in experiments for the Lambda hyperon.
We study the spin polarization generated by the hydrodynamic gradients. In addition to the widely studied thermal vorticity effects, we identify an undiscovered contribution from the fluid shear. ...This shear-induced polarization (SIP) can be viewed as the fluid analog of strain-induced polarization observed in elastic and nematic materials. We obtain the explicit expression for SIP using the quantum kinetic equation and linear response theory. Based on a realistic hydrodynamic model, we compute the differential spin polarization along both the beam direction z and the out-plane direction y in noncentral heavy-ion collisions at √sNN = 200 GeV , including both SIP and thermal vorticity effects. We find that SIP contribution always shows the same azimuthal angle dependence as experimental data and competes with thermal vorticity effects. In the scenario that Λ inherits and memorizes the spin polarization of a strange quark, SIP wins the competition, and the resulting azimuthal angle dependent spin polarization Py and Pz agree qualitatively with the experimental data.
A
bstract
We systematically analyze the effects of the derivatives of the hydrodynamic fields on axial Wigner function that describes the spin polarization vector in phase space. We have included all ...possible first-order derivative contributions that are allowed by symmetry and compute the associated transport functions at one-loop using the linear response theory. In addition to reproducing known effects due to the temperature gradient and vorticity, we have identified a number of potentially significant contributions that are overlooked previously. In particular, we find that the shear strength, the symmetric and traceless part of the flow gradient, will induce a quadrupole for spin polarization in the phase space. Our results, together with hydrodynamic gradients obtained from hydrodynamic simulations, can be employed as a basis for the interpretation of the Λ (anti-Λ) spin polarization measurement in heavy-ion collisions.
Spin Hall effect (SHE) is the generation of spin current due to an electric field, and has been observed in a variety of materials. In this work, we use linear response theory to verify that the ...analogous spin Hall current can be induced by chemical potential and temperature gradient, both of which are present in hot and dense nuclear matter created in heavy-ion collisions. We propose to measure "directed spin flow", the first Fourier coefficients of local spin polarization of Λ (Λ) hyperon, at central collisions to probe spin Hall current in heavy-ion collision experiments. We benchmark the magnitude of the induced "directed spin flow" at two representatively collisions energies, namely √sNN = 200 GeV and √sNN = 19.6 GeV , by employing a phenomenologically motivated freeze-out prescription. At both beam energies, the resulting "directed spin flow" ranges from 10−4 to 10−3, and is very sensitive to the rapidity.
Abstract
Controllable and on‐demand delivery of supramolecular systems have received considerable attention in modern agricultural management, especially for managing intractable plant diseases. ...Here, an intelligent photoresponsive pesticide delivery system is reported based on
β
‐cyclodextrin (
β
‐CD) and azobenzene, which overcomes the resistance of phytopathogens caused by the irrational use of conventional pesticides. Antibacterial bioassays illustrated that designed azobenzene derivative
3a
possesses the most efficient bioactivity with EC
50
values of 0.52–25.31 µg mL
−1
toward three typical phytopathogens. Moreover, the assembly of the supramolecular binary complex
3a
@
β
‐CD is successfully elucidated and displays exceptional inhibitory activity on biofilm formation. Of note, this supramolecular binary complex significantly improves the water solubility, foliar surface wettability, and shows marked light‐responsive properties. In vivo anti‐
Xoo
assays reveal that
3a
@
β
‐CD has excellent control efficiency (protective activity: 51.22%, curative activity: 48.37%) against rice bacterial blight pathogens, and their control efficiency can be elevated to values of 55.84% (protective activity) and 52.05% (curative activity) by UV–vis exposure. In addition, the
3a
@
β
‐CD are non‐toxic toward various non‐target organisms. This study therefore offers new insights into the potential of host‐guest complexes as a feasible pesticide discovery strategy characterized by a safe, biocompatible, light‐responsive release, and antibiofilm properties for overcoming intractable plant bacterial diseases.
As an emerging biomedical image processing technology, medical image segmentation has made great contributions to sustainable medical care. Now it has become an important research direction in the ...field of computer vision. With the rapid development of deep learning, medical image processing based on deep convolutional neural networks has become a research hotspot. This paper focuses on the research of medical image segmentation based on deep learning. First, the basic ideas and characteristics of medical image segmentation based on deep learning are introduced. By explaining its research status and summarizing the three main methods of medical image segmentation and their own limitations, the future development direction is expanded. Based on the discussion of different pathological tissues and organs, the specificity between them and their classic segmentation algorithms are summarized. Despite the great achievements of medical image segmentation in recent years, medical image segmentation based on deep learning has still encountered difficulties in research. For example, the segmentation accuracy is not high, the number of medical images in the data set is small and the resolution is low. The inaccurate segmentation results are unable to meet the actual clinical requirements. Aiming at the above problems, a comprehensive review of current medical image segmentation methods based on deep learning is provided to help researchers solve existing problems.
Ammonia is one of the most abundant and simple nitrogen sources with decent stability and reactivity. Direct insertion of ammonia into a carbon skeleton is an ideal approach to building valuable ...N-heterocycles for extensive applications with unprecedented atom and step economy. Here, we show an electrochemical dehydrogenative method in which ammonia is inserted directly into alkenes to build aromatic N-heterocycles in a single step without the use of any external oxidant. This new approach achieves 98-99.2% atom economy with hydrogen as the only byproduct. Quinoline and pyridine with diverse substitutions are readily available. In this work, electrochemistry was used to drive a 4-electron oxidation reaction that is hard to access by other protocols, providing a parallel pathway to nitrene chemistry. In a tandem transformation that included three distinct electrochemical processes, the insertion of ammonia further showcased the tremendous potential to manipulate heterocycles derived from Hantzsch ester to diazine via pyridine and pyrrole.
In multi-sensor detection system, the application of multi-sensor accurate detection system parameters is limited due to the existence of measurement noise. Using multi-source data fusion technology ...can be more accurate, timely detection and data processing system. Data fusion is a basic function in humans and other biological systems. In this paper, in order to make the system adaptive multi-source data fusion, using the BP neural network algorithm is a good way to deal with incomplete test data and test the noise problem. In this paper, the characteristics of three levels of data fusion and the derivation process of BP neural network algorithm are introduced in detail. In order to verify the role of BP neural network algorithm in the process of detection system filtering, a MATLAB simulation experiment is carried out. The experimental results show that the BP neural network algorithm can effectively reduce the measurement error of multi-sensor detection system and improve the detection accuracy.
Starting from the basic process of piano music recognition, this paper focuses on the feature extraction process of piano art performance. In the feature extraction of piano art performance, the ...fundamental frequency characteristics of piano music signals were analyzed by using short-time Fourier transform theory, focusing on the feature extraction of musical pitch, time value, and tonality, and the spectrum analysis of piano music signals and the reconstruction of piano timbre were completed. The piano performance work, “Autumn Moon on the Peaceful Lake,” is used as an example to analyze the musical characteristics and personality. The overall structure of “Autumn Moon on the Peaceful Lake” is a typical three-part structure: the key is the
D palace seven-tone mode, the key is single, and the marking range of performance strength is ppp-pp-p-mf-mf-f-ff. In the three versions played by Yin Chengzong, Lang Lang, and Chen Jie, the average tempo of the performance was 31.5 beats, 26.5 beats, and 26.8 beats, respectively. The performance process of different pianists is a “slow-fast-slow” layout, and other passages are added to the individual free processing to further enhance the charm of the work.
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