Local Regions Research Articles

Assessment of the age and conditions of metamorphism of high-pressure blastolites of the Gonzhinsky block of the Argun superterrane of the eastern part of the Central Asian folded belt

As a result of petrographic and thermobaric studies, 4 mineral associations were identified in the blastolite: relict, main, association corresponding to biotitisation and association of retrograde changes. The relict association probably represented eclogites The main mineral association corresponds to apoeclogite zoisite amphibolites. Determination of the P-T parameters of the formation of this association showed an interval of P = 13.0–15.0 kbar and T = 580-670 °C. At the same time, if we take the most ferruginous outer rim of amphibole-1 for calculations, then the P-T parameters shift to a higher temperature region of P = 13.0–17.0 kbar and T = 660-780 °C. The association corresponding to the imposed biotitisation is well structurally expressed. The lines of monomineral equilibria of the biotite association constructed from various combinations of garnet, biotite and plagioclase compositions showed good convergence in the local region corresponding to the interval P = 12.5-13.2 kbar and T = 810-830 °C. The last association of retrograde changes includes low-alumina amphibole-2.The association corresponding to the imposed biotitisation.ше is well structurally expressed. The last association of retrograde changes includes low-alumina amphibole-2. Based on the obtained isotopic data, a mineral Sm-Nd isochron was constructed for the rock, garnet and two amphiboles. The age of the isochron is 171 ± 3 million years, the latter is interpreted as the time of formation of the main mineral association and corresponds to its crystallization at the peak of metamorphism.

Anderson Localization of Walking Droplets

Understanding the ability of particles to maneuver through disordered environments is a central problem in innumerable settings, from active matter and biology to electronics. Macroscopic particles ultimately exhibit diffusive motion when their energy exceeds the characteristic potential barrier of the random landscape. In stark contrast, wave-particle duality causes electrons in disordered media to come to rest even when the potential is weak—a remarkable phenomenon known as Anderson localization. Here, we present a hydrodynamic active system with wave-particle features, a millimetric droplet self-guided by its own wave field over a submerged random topography, whose dynamics exhibits localized statistics analogous to those of electronic systems. Consideration of an ensemble of particle trajectories reveals a suppression of diffusion when the guiding wave field extends over the disordered topography. We rationalize mechanistically the emergent statistics by virtue of the wave-mediated resonant coupling between the droplet and topography, which produces an attractive wave potential about the localization region. This hydrodynamic analog, which demonstrates how a classical particle may localize like a wave, suggests new directions for future research in various areas, including active matter, wave localization, many-body localization, and topological matter. Published by the American Physical Society 2024

Experiment and prediction of the strain-range dependent ultra-low-cycle fatigue based on micromechanical cyclic void growth model

Under severe seismic action, the local stress concentration region in steel structures is prone to the ultra-low-cycle fatigue (ULCF) under high triaxiality and irregular cyclic deformation with intensively varying strain amplitudes. It emphasizes the necessity of the jointed effects of the stress triaxiality and strain range incorporated in the ULCF life prediction. Given the limited relevant studies in terms of the underlying micro-mechanisms, this paper focuses on experimental and modeling studies of the combined effects of stress triaxiality and strain range on the ULCF failure, based on Gurson-Tvergaard-Needleman (GTN) microvoid evolution theories. Monotonic tensile tests on three types of notched round bars suggest that fracture strain decreases with increasing triaxiality. Cyclic tests on two types of notched bars under various strain ranges confirm the combined effects of stress triaxiality and strain range. Given a specific triaxiality, the ULCF damage accumulation rate increases linearly as the tensile plastic strain range ramps up. For the same tensile plastic strain range, higher triaxiality results in a greater damage accumulation rate. In the modeling studies, the consistency of the GTN and uncoupled damage models has been proven in terms of ULCF failure of structural steel. Based on GTN theories, a new micromechanical cyclic void growth model (GCVGM) is proposed, considering the detailed processes of void nucleation, growth, and coalescence under monotonic and cyclic loadings. Moreover, the joint effects of stress triaxiality and strain range can be explicitly described within a unified framework, without additional empirical assumptions. Based on experimental and simulation results, the proposed GCVGM shows significant advantages over conventional models in accurately predicting ULCF failure under various loading protocols, with low average errors of 2.73 % and −0.91 % for two types of notched bar specimens, respectively.

Optical pattern formation of laser fields in the Rydberg atomic gases

We study the phenomena of long-wave and short-wave modulation instabilities (LMI and SMI) in Rydberg atomic gases within the framework of the nonlocal nonlinear Schrödinger equations in the local and nonlocal regions (characterized by the ratio of beam radius to radius of Rydberg blockade sphere), respectively. We further reveal the rich soliton dynamics arising from interactions of nonlinear waves triggered by LMI. We also show the variety of spatial self-organization pattern formations and their active manipulation due to SMI. Through a synthesis of theoretical analysis and numerical simulations, the self-organized optical structures reported here provide a way for realizing what we believe to be novel optical patterns and solitons based on Rydberg atomic gases.

Dominant Role of Eurasian Evaporation on the Moisture Sources of the Interannual Variations in Central Asian Summer Precipitation

Abstract The precipitation changes in arid and semiarid central Asia have great impacts on the local fragile ecosystem. The summer precipitation in central Asia shows obvious interannual variations, but the corresponding crucial moisture transporting processes remain unclear. Therefore, this study employs the Lagrangian flexible particle (FLEXPART) diffusion model to achieve this goal. Results show that the moisture of climatological summer precipitation in central Asia is mainly from the local regions, the surrounding western and northern Eurasian regions. The contribution of local evaporation from western central Asia is about 2 times that from eastern central Asia. At the interannual time scale, the moisture variations are mainly influenced by the local regions and western Eurasia, while the local evaporation is mainly from western central Asia. Totally, the Eurasian evaporation plays a dominant role in the interannual variations of central Asian summer precipitation by contributing more than 90% of the total moisture. The moisture transports associated with central Asian summer precipitation interannual variations are impacted by the anomalous cyclones over the western and northeastern parts of central Asia during the wet years, which enhance the moisture convergence and hence increase the summer precipitation in central Asia. The anomalous cyclone over the western part of central Asia is correlated with the changes in the intensity of Eurasian summer subtropical westerly jet (ESSWJ), while the anomalous cyclone over the northeastern part of central Asia is correlated with both ESSWJ and the British–Baikal Corridor pattern teleconnection in association with the polar front jet.

Nitrogen and Oxygen Dual‐Doped Carbon as High‐Rate Long‐Cycle‐Life Anode Materials for Lithium‐Ion Batteries

Defect‐type carbon, doped with nitrogen and oxygen, is synthesized using the high‐temperature solid‐phase method. X‐ray photoelectron spectroscopy analysis reveals the presence of nitrogen, including pyridine nitrogen, pyrrole nitrogen, and graphitized nitrogen, incorporated into the carbon structure. Additionally, oxygen is introduced into carbon, with both CO and CO functionalities are observed. Transmission electron microscopy and scanning electron microscopy indicate that all samples exhibit a morphology of carbon microblocks with localized turbocharged lattice regions. Electrochemical tests demonstrate that the nitrogen‐ and oxygen‐doped carbon microblocks exhibit excellent cycling performance and high rate capacity. Specifically, at current densities of 1 and 2 A g−1, the rate capacity remains at 385.6 and 214.4 mA h g−1, respectively. Furthermore, the discharge capacity at 5 A g−1 remains at 58.3 mA h g−1 on the 3500th cycle. The defects introduced by nitrogen and oxygen doping not only enhance reactivity and electronic conductivity but also improve lithium‐ion diffusion dynamics.

Microscopic in situ observation of electromechanical instability in a dielectric elastomer actuator utilizing transparent carbon nanotube electrodes.

Electromechanical instability (EMI) restricts the performance of dielectric elastomer actuators (DEAs), leading to premature electrical breakdown at a certain voltage. However, macro-level observations using traditional carbon grease electrodes have failed to capture the detailed features of EMI. In this study, we investigated EMI at the microscopic scale by fabricating transparent and conductive single-walled carbon nanotube (SWCNT) electrodes. Our findings reveal that EMI predominantly occurs in highly localized regions with dimensions on the order of tens of micrometers. This snap-through instability is likely induced by pre-existing defects within the elastomer, such as air voids or conductive particles, which reduce the critical voltage required for EMI in the flawed areas. From the perspective of phase transition principles, these defects act as heterogeneous nucleation sites for new phase embryos, thereby lowering the energy barrier for the electromechanical phase transition (i.e., EMI) compared to homogeneous nucleation in an ideally impurity-free elastomer. This study clarifies the longstanding discrepancy between theoretically predicted deformation bursts and the experimentally observed macroscopic continuous expansion of DEAs under low pre-stretch conditions. Additionally, it underscores the critical importance of material purity in mitigating electromechanical instability.

Elucidating the hemodynamic impact of residual stenosis post-carotid artery stenting: A numerical study.

Residual stenosis (RS) and hemodynamics demonstrate a significant correlation with postoperative in-stent restenosis/thrombosis following carotid artery stenting (CAS). This study endeavors to elucidate the potential associations between RS and adverse postoperative hemodynamic factors. This study utilized 46 patient-specific carotid artery models post-stenting, which were categorized into two groups based on the presence of RS: the normal group (N, n=23) and the RS group (RS, n=23). A comparative analysis was conducted to evaluate the discrepancies in geometry and adverse hemodynamic parameters, alongside investigating the potential correlation between hemodynamic and geometric parameters. The results reveal that a higher reflux flow volume is discernible in the RS group during low-velocity phases of the cardiac cycle, concomitant with an augmented extent of areas exposed to oscillatory shear stress and extended particle residence time. Moreover, the adverse hemodynamic parameters exhibit a positive correlation with the degree of stent expansion, stent length in the common carotid artery (CCA), and the distal slope of the RS. The distal slope and tortuosity of RS significantly influence the development of adverse hemodynamic conditions post-stenting, exacerbating the hemodynamic environment near the stenosis. Interestingly, while an extended stent length in the internal carotid artery (ICA) region improves hemodynamics by reducing flow disturbance, a longer stent in the CCA significantly worsens these conditions. Hence, it is prudent to analyze the characteristics of the local lesion regions to optimize the strategy for stent implantation.

Non-invasive temporal interference brain stimulation reduces preference on morphine-induced conditioned place preference in rats

Long-term use of opioid drugs such as morphine can induce addiction in the central nervous system through dysregulation of the reward system of the brain. Deep brain stimulation (DBS) is a non-pharmacological technique capable of attenuating behavioral responses associated with opioid drug consumption and possesses the capability to selectively activate and target localized brain regions with a high spatial resolution. However, long-term implantation of electrodes in brain tissue may limit the effectiveness of DBS due to changes in impedance, position, and shape of the tip of the stimulation electrode and the risk of infection of nerve tissue around the implanted electrode. The main objective of the current study is to evaluate the effect of temporal interference (TI) brain stimulation on addictive behaviors of morphine-induced conditioned place preference (CPP) in rats. TI stimulation is a non-invasive technique used transcranially to modulate neural activity within targeted brain regions. It involves applying two high-frequency currents with slightly different frequencies, resulting in interference and targeted stimulation of different brain areas with the desired spatial resolution. The results indicated that TI stimulation with the amplitude of I1=I2=0.5\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ ext{I}}_{1}{ = }{\ ext{I}}_{2}{ = 0.5}$$\\end{document} mA, carrier frequency of 2 kHz, frequency difference of 25 Hz, ON–OFF stimulation frequency of 0.25 Hz, and total duration of 10 min in three consecutive days resulted in a significant reduction of morphine preference in the morphine-stimulation group in comparison with the morphine group (p < 0.001). These findings highlight the potential of TI stimulation as a modulatory intervention in mitigating the addictive properties of morphine and provide valuable insights into the therapeutic implications of this stimulation paradigm for treatment of opioid drugs in human subjects.

Consecutive attractive local regions – bidirectional long short-term memory for trip destination prediction

We propose a sequence-to-sequence model to capture a partial trajectory that contains a few attractive local regions and forecast its destination. Therefore, the main goal of this work is to predict the destination, given the trip’s trajectory, effectively by learning from its attractive local sub-trajectory only. Conceptually, the proposed model incorporates Bidirectional Long Short-Term Memory (BiLSTM) for finding frequent trip trajectories and a Consecutive Attractive Local Regions (CALR) mechanism for only taking their few attractive local regions, called CALR-BiLSTM. Existing related works focused on observing whole regions of each trip trajectory at once to decide its attractive ones from a Global Attention Mechanism (GAM). However, GAM may hold similar attractive sub-trajectories for different destinations, which leads to worse predictions. To overcome the issue, the proposed model observes the entire trip trajectory part by part within a small window, such as focusing on a few regions that are attractive. In this work, we demonstrated the proposed model on large public datasets. As a result, we can enjoy the proposed model as the winner against the state-of-the-art models. Moreover, we present ablation studies on various recurrent neural networks and attention mechanisms to ensure the proposed model is in the right settings.

Intracellular Ca2+ After Eccentric Muscle Contractions: Key Role for Ryanodine Receptors.

Eccentric contractions (ECC) induce excessive intracellular calcium ion (Ca2+) accumulation and muscle structural damage in localized regions of the muscle fibers. In this investigation, we present the novel hypothesis that the ryanodine receptor (RyR) plays a central role in evoking a Ca2+ dynamics profile that is markedly distinguishable from other muscle adaptive responses.

Ex-Vivo Human-Sized Organ Machine Perfusion: A Systematic Review on the Added Value of Medical Imaging for Organ Condition Assessment.

Machine perfused ex-vivo organs offer an excellent experimental platform, e.g., for studying organ physiology and for conducting pre-clinical trials for drug delivery. One main challenge in machine perfusion is the accurate assessment of organ condition. Assessment is often performed using viability markers, i.e., lactate concentrations and blood gas analysis. Nonetheless, existing markers for condition assessment can be inconclusive, and novel assessment methods remain of interest. Over the last decades, several imaging modalities have given unique insights into the assessment of organ condition. A systematic review was conducted according to accepted guidelines to evaluate these medical imaging methods, focussed on literature that use machine perfused human-sized organs, that determine organ condition with medical imaging. A total of 18 out of 1,465 studies were included that reported organ condition results in perfused hearts, kidneys, and livers, using both conventional viability markers and medical imaging. Laser speckle imaging, ultrasound, computed tomography, and magnetic resonance imaging were used to identify local ischemic regions and quantify intra-organ perfusion. A detailed investigation of metabolic activity was achieved using 31P magnetic resonance imaging and near-infrared spectroscopy. The current review shows that medical imaging is a powerful tool to assess organ condition.

Changing seroprevalence of schistosomiasis japonica in China from 1982 to 2020: A systematic review and spatial analysis.

Schistosomiasis is a global public health issue. In China, while the seroprevalence of Schistosomiasis japonica has currently reduced to a relatively low level, risk of infection still exists in certain areas. However, there has been a lack of comprehensive research on the long-term trends of national seroprevalence, changes across age groups, and characteristics in spatial distribution, which is crucial for effectively targeting interventions and achieving the goal of eliminating schistosomiasis by 2030. Our study aimed to address this gap by analyzing the long-term trends of Schistosomiasis japonica seroprevalence in China from 1982 to 2020 based on the data from diverse sources spanning a period of 39 years. Seroprevalence data were collected from literature databases and national schistosomiasis surveillance system. Meta-analysis was conducted to estimate the seroprevalence. Joinpoint model was used to identify changing trend and inflection point. Inverse distance weighted interpolation was used to determine the spatial distribution of seroprevalence. The seroprevalence decreased from 34.8% in 1982 to 2.4% in 2020 in China. Before 2006, the seroprevalence was higher in the middle age group, and a pattern of increasing with age was observed afterwards. The areas with high seroprevalence existed in Dongting Lake, Poyang Lake, Jianghan Plain, the Anhui branch of the Yangtze River and some localized mountainous regions in Sichuan and Yunnan provinces. There was a significant decline in the seroprevalence of Schistosomiasis japonica from 1982 to 2020 in China. Nevertheless, schistosomiasis has not been eradicated; thus, implementing precise and personalized monitoring measures is crucial for the elimination of schistosomiasis, especially in endemic areas and with a particular focus on the elderly.

PET radiomics-based lymphovascular invasion prediction in lung cancer using multiple segmentation and multi-machine learning algorithms.

The current study aimed to predict lymphovascular invasion (LVI) using multiple machine learning algorithms and multi-segmentation positron emission tomography (PET) radiomics in non-small cell lung cancer (NSCLC) patients, offering new avenues for personalized treatment strategies and improving patient outcomes. One hundred and twenty-six patients with NSCLC were enrolled in this study. Various automated and semi-automated PET image segmentation methods were applied, including Local Active Contour (LAC), Fuzzy-C-mean (FCM), K-means (KM), Watershed, Region Growing (RG), and Iterative thresholding (IT) with different percentages of the threshold. One hundred five radiomic features were extracted from each region of interest (ROI). Multiple feature selection methods, including Minimum Redundancy Maximum Relevance (MRMR), Recursive Feature Elimination (RFE), and Boruta, and multiple classifiers, including Multilayer Perceptron (MLP), Logistic Regression (LR), XGBoost (XGB), Naive Bayes (NB), and Random Forest (RF), were employed. Synthetic Minority Oversampling Technique (SMOTE) was also used to determine if it boosts the area under the ROC curve (AUC), accuracy (ACC), sensitivity (SEN), and specificity (SPE). Our results indicated that the combination of SMOTE, IT (with 45% threshold), RFE feature selection and LR classifier showed the best performance (AUC = 0.93, ACC = 0.84, SEN = 0.85, SPE = 0.84) followed by SMOTE, FCM segmentation, MRMR feature selection, and LR classifier (AUC = 0.92, ACC = 0.87, SEN = 1, SPE = 0.84). The highest ACC belonged to the IT segmentation (with 45 and 50% thresholds) alongside Boruta feature selection and the NB classifier without SMOTE (ACC = 0.9, AUC = 0.78 and 0.76, SEN = 0.7, and SPE = 0.94, respectively). Our results indicate that selection of appropriate segmentation method and machine learning algorithm may be helpful in successful prediction of LVI in patients with NSCLC with high accuracy using PET radiomics analysis.

Nanoscale subsurface imaging by non-steady-state electron beam-driven scanning thermoelectric capacitance microscopy

Nanoscale subsurface characterization technologies based on the scanning electron microscope platform offer incomparable advantages of nondestructiveness and penetration depths up to the micrometer scale. However, the electron beam can serve not just as a mechanical/electrical excitation source but also as an excellent nanoscale thermal excitation source, which can facilitate the development of nanoscale subsurface imaging methods based on the Seebeck effect in semiconducting materials. In this work, a subsurface nondestructive imaging technology, scanning thermoelectric capacitance microscopy (STeCM), was developed based on the interaction between a non-steady-state electron beam and semiconducting materials, exploiting the Seebeck effect. In STeCM, a square wave-modulated hot electron beam with huge kinetic energy excites a “thermal wave” in the subsurface local region of the semiconducting sample. The heated local region, acting as a thermoelectric capacitor, undergoes cyclic charging and discharging, leading to the generation of periodic current due to non-equilibrium carrier migration. The second-order harmonic component of this current is demodulated to visualize embedded local thermal/thermoelectric inhomogeneities. Amazingly, for STeCM sample, only a smooth or polished surface is required, eliminating the need for any microfabrication, which will effectively decrease the configuration difficulty in the experiment. STeCM offers an alternative subsurface nondestructive imaging technology for more efficient, simple, and robust characterization.

Improving generative adversarial network inversion via fine-tuning GAN encoders

Generative adversarial networks (GANs) can synthesize high-quality (HQ) images, and GAN inversion is a technique that discovers how to invert given images back to latent space. While existing methods perform on StyleGAN inversion, they have limited performance and are not generalized to different GANs. To address these issues, we proposed a self-supervised method to pre-train and fine-tune GAN encoders. First, we designed an adaptive block to fit different encoder architectures for inverting diverse GANs. Then we pre-train GAN encoders using synthesized images and emphasize local regions through cropping images. Finally, we fine-tune the pre-trained GAN encoder for inverting real images. Compared with state-of-the-art methods, our method achieved better results that reconstructed high-quality images on mainstream GANs. Our code and pre-trained models are available at: https://github.com/disanda/Deep-GAN-Encoders.

Fuzzy logic for the management of vaccination during pandemics: A spread-rate-based approach

&lt;p&gt;Pandemics, such as coronavirus disease COVID-19 are known to cause massive damage to the world's economic growth and their impacts are serious and influence across every aspect of social structure. The most inevitable factor in responding to the disaster of pandemics is the right management in terms of allocating a limited vaccine supply. The focus of this research work is to utilize a fuzzy logic inference system in the allocation of vaccine doses to the regional authorities by a central authority. The objective is obtained by designing a system based on fuzzy logic that considers the spread rate as the input to infer the vaccination rate of the local population. This system makes it possible for sufficient doses of vaccines to be allotted to the prioritized regions where the severity of the spread rate is a concern and vaccines are not held up in regions where the severity of the spread rate is lesser. The designed system is verified using MATLAB software, which shows that this method can ensure an effective and efficient allocation of vaccination in the local regions and aid the fight against the disastrous spread of the disease.&lt;/p&gt;

Synergistic Development Pathways for National Parks and Local Regions: Shared Socioeconomic Pathway Scenario Forecasting and Optimization

National parks play a crucial role in protecting ecosystems and biodiversity while facing challenges in balancing nature conservation and economic development. However, because of the difficulty in the unified simulation of natural protection functions and regional socioeconomic development, there is a lack of integrated prediction research on the comprehensive development pathways of national parks and their surrounding areas. This study adopts the Shared Socioeconomic Pathway (SSP) framework that links climate change research with socioeconomic development paths, taking China’s first national park—Sanjiangyuan National Park—region as an example, to conduct research on the synergistic development path of regional socioeconomic development and national parks. The model design includes five typical paths to cover a wide range of socioeconomic development possibilities. These paths are based on different assumptions, including factors such as population growth, economic development, energy use, technological progress, and policy choices. By applying scenario planning methods, optimal development pathways are identified based on environmental, economic, and social priorities. The results show that GDP growth is fastest under the sustainable development and fossil fuel development pathways. By 2050, the population difference under different pathways will approach 100,000, and the GDP gap will be close to CNY 200 billion. This study provides valuable insights for the planning, decision-making, and management of Sanjiangyuan and similar national parks and their surrounding areas, contributing to the promotion of sustainable ecological and economic development of national parks and their regions.

Has the Digital Economy Boosted Carbon Reduction in Livestock Farming in China?

Carbon reduction in livestock is a necessary path for the green transformation of the livestock industry. Has the digital economy as an emerging productive force in recent years driven carbon reduction in the livestock sector? This paper employs dynamic panel regression models, mediation effect models, and spatial econometric models to investigate the impact mechanisms of the digital economy on carbon emission reduction in livestock husbandry. The results indicate the following: (1) The digital economy has a positive impact on carbon reduction in livestock farming by fostering technical innovation, enhancing the level of human capital, and transforming the mode of production. (2) From 2013 to 2021, the digital economy did not show a significant carbon reduction effect until 2018. It has had a substantial impact on carbon reduction in livestock husbandry in the northeastern and western regions, while its influence in the eastern and central regions has not been significant. The digital economy positively affects carbon emission reduction in non-dairy cows and pigs, negatively affects poultry, and shows no significant effect on dairy cows and sheep. (3) In terms of spatial effects, the digital economy is not only driving carbon emission reductions from livestock farming in the local region but is also significantly driving carbon emission reductions from livestock farming in the surrounding provinces. The findings of this article provide some insights into future policy formulation for low-carbon development in the livestock sector.

Study on secondary motions in supersonic boundary layers of a bent pipe

The present study employed direct numerical simulation to investigate the supersonic flow of Mach 3 in a bent pipe with a curvature of 0.0825, elucidating the dynamic mechanism of secondary motions within the turbulent boundary layer. The findings indicate that the compressible flow, affected by the wall curvature, is differentiated into several motion patterns as the bending angle increases: a portion of the outer fluid close to the wall, driven by the circumferential pressure gradient, moves inward through the lateral wall, causing an increase in the mass rate toward the lateral boundary layer and promoting the circumferential transport of energy and vorticity; other outer fluids at the start of the bent section, due to the centrifugal force, approach the wall to form a thinner boundary layer downstream; meanwhile, the fluid near the inner wall experiences the expansion, followed by the flow separation and reattachment at a bending angle of 14.6° and 22.0°, respectively, which induce a shear layer that develops from the inner end point toward the mainstream center, gradually reshaping the high-speed flow area within the pipe cross section into a U-shape, and enhancing the vorticity and temperature field of the inner region. Additionally, this study reveals a remarkable phenomenon that the separated flow in a localized inner region forms a rotating field, inducing vortices distinct from the mainstream Dean vortices in the low-speed flow region enclosed by the shear layer.