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• Analyzed the stochastic resonance and stochastic P-bifurcation of an axially moving shape-memory alloy laminate. • A change in the volume fraction of the SMA shifted the formant of the SNR (signal-to-noise ratio) curve up and down. • Variation in axial velocity, temperature, and stochastic intensity induced stochastic P-bifurcation. This paper investigates the transverse vibration of an axially moving shape-memory alloy (SMA) fiber hybrid laminations under the combined action of transverse harmonic excitation and stochastic disturbance. Considering the shape memory alloy (SMA) fiber volume fraction random field, the kinetic energy and strain potential energy of SMA laminates are solved, and the axial motion equation of SMA laminates is derived according to Hamilton principle, a non-dimensional differential equation of the transverse vibration of the axially moving SMA laminated plates is obtained by adopting the Galerkin integral method. Considering the volume-fraction stochastic field, the stochastic natural vibration of a SMA laminate is analyzed. Considering the stochastic resonance of the SMA laminate under the action of Gaussian white noise and harmonic excitation, the effects of geometric parameters, physical parameters of materials, and temperature on the stochastic resonance behavior of the SMA laminate is analyzed. Finally, the effect of the stochastic P-bifurcation phenomenon of the parameters on the steady-state response of the SMA laminate is analyzed. [ABSTRACT FROM AUTHOR]

Recently, two ultralong-period radio transients, GLEAM-X J162759.5-523504.3 (J1627) and GPM J1839-10 (J1839), were discovered with spin periods longer than 1000 s. The origin of these two ultralong-period radio transients is intriguing in understanding the spin evolution of neutron stars (NSs). In this work, we examine whether the interaction between strong magnetized NSs and fallback disks can spin NSs down to the observed ultralong period. Our simulations found that the magnetar + fallback disk model can account for the observed period, period derivative, and X-ray luminosity of J1627 in the quasi-spin-equilibrium stage. To evolve to the current state of J1627, the initial mass-accretion rate of the fallback disk and the magnetic field of the NS are in the range of (1.1–30) × 1024 g s−1 and (2–5) × 1014 G, respectively. In the active lifetime of the fallback disk, it is impossible for J1839 to achieve the observed upper limit of the period derivative. Therefore, we propose that J1839 may be in the second ejector phase after the fallback disk becomes inactive. Those NSs with a magnetic field of (2–6) × 1014 G and a fallback disk with an initial mass-accretion rate of ∼1024–1026 g s−1 are possible progenitors of J1839. [ABSTRACT FROM AUTHOR]

The Photometric objects Around Cosmic webs (PAC) approach developed in Xu et al. has the advantage of making full use of spectroscopic and deeper photometric surveys. With the merits of PAC, the excess surface density n ¯ 2 w p of neighboring galaxies can be measured down to stellar mass 1010.80 M ⊙ around quasars at redshift 0.8 < z s < 1.0, with the data from the Sloan Digital Sky Survey IV extended Baryon Oscillation Spectroscopic Survey and the Dark Energy Spectroscopic Instrument Legacy Imaging Surveys. We find that n ¯ 2 w p generally increases quite steeply with the decrease of the separation. Using the subhalo abundance-matching method, we can accurately model the n ¯ 2 w p both on small and large scales. We show that the steep increase of n ¯ 2 w p toward the quasars requires that a large fraction f sate = 0.29 − 0.06 + 0.05 of quasars should be satellites in massive halos, and we find that this fraction measurement is insensitive to the assumptions of our modeling. This high satellite fraction indicates that the subhalos have nearly the same probability of hosting quasars as the halos for the same (infall) halo mass and that the large-scale environment has negligible effect on the quasar activity. We show that even with this high satellite fraction, each massive halo on average does not host more than one satellite quasar, due to the sparsity of quasars. [ABSTRACT FROM AUTHOR]

[Display omitted] • A novel composite photocatalyst NiS/CdS@DUT-67 is prepared. • The separation and transport of photogenerated carriers are assisted by NiS and DUT-67. • NiS/CdS@DUT-67 achieves high hydrogen production rate as 9618 μmol·g NiS/CdS −1·h−1. Metal-organic framework materials (MOFs) and their derivatives have been widely used in the field of photocatalytic water decomposition for hydrogen production. In this study, NiS/CdS was initially acquired and subsequently combined with DUT-67 via ultrasound to create a unique ternary photocatalyst NiS/CdS@DUT-67. The rate of hydrogen production for NiS/CdS@DUT-67 is 9618 μmol·g NiS/CdS −1·h−1 for NiS/CdS@DUT-67, which is 32 times and 2.5 times higher than that for CdS and NiS/CdS, respectively. Of particular interest is the fact that even after 50 h of photocatalysis, the hydrogen production rate did not show a significant decrease, demonstrating its excellent stability compared to CdS and NiS/CdS. In this ternary system, NiS and DUT-67 function as dual co-catalysts for CdS, collaborating to enhance charge separation during the photocatalysis. This study presents a clear demonstration of the advantages of utilizing metal–organic framework derivatives (MOF-derivatives) cophotocatalysts and their synergistic effect, resulting in improved photocatalytic activity and stability of semiconductors. This innovative approach provides a new perspective on constructing photocatalytic materials with exceptional performance. [ABSTRACT FROM AUTHOR]

Wearable devices have been widely used for the home monitoring of physical activities and healthcare conditions, among which ambulatory electrocardiogram (ECG) stands out for the diagnostic cardiovascular information it contains. Continuous and unobtrusive sensing often requires the integration of wearable sensors to existing devices such as watches, armband, headphones, etc.; nonetheless, it is difficult to detect high-quality ECG due to the nature of low signal amplitude at these areas. In this paper, a high-performance system with multi-channel signal superposition for weak ECG real-time detection is proposed. Firstly, theoretical analysis and simulation is performed to demonstrate the effectiveness of this system design. The detection system, including electrode array, acquisition board, and the application (APP), is then developed and the electrical characteristics are measured. A common mode rejection ratio (CMRR) of up to 100 dB and input inferred voltage noise below 1 μV are realized. Finally, the technique is implemented in form of ear-worn and armband devices, achieving an SNR over 20 dB. Results are also compared with the simultaneous recording of standard lead I ECG. The correlation between the heart rates derived from experimental and standard signals is higher than 0.99, showing the feasibility of the proposed technique. [ABSTRACT FROM AUTHOR]

The heterogeneity and intricate cellular architecture of complex cellular ecosystems play a crucial role in the progression and therapeutic response of cancer. Understanding the regulatory relationships of malignant cells at the invasive front of the tumor microenvironment (TME) is important to explore the heterogeneity of the TME and its role in disease progression. In this study, we inferred malignant cells at the invasion front by analyzing single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) data of ER-positive (ER+) breast cancer patients. In addition, we developed a software pipeline for constructing intercellular gene regulatory networks (IGRNs), which help to reduce errors generated by single-cell communication analysis and increase the confidence of selected cell communication signals. Based on the constructed IGRN between malignant cells at the invasive front of the TME and the immune cells of ER+ breast cancer patients, we found that a high expression of the transcription factors FOXA1 and EZH2 played a key role in driving tumor progression. Meanwhile, elevated levels of their downstream target genes (ESR1 and CDKN1A) were associated with poor prognosis of breast cancer patients. This study demonstrates a bioinformatics workflow of combining scRNA-seq and ST data; in addition, the study provides the software pipelines for constructing IGRNs automatically (cIGRN). This strategy will help decipher cancer progression by revealing bidirectional signaling between invasive frontline malignant tumor cells and immune cells, and the selected signaling molecules in the regulatory network may serve as biomarkers for mechanism studies or therapeutic targets. [ABSTRACT FROM AUTHOR]

[Display omitted] The presence of an excessive amount of lead iodide on the surface of perovskite solar cells (PSCs) is a significant contributing factor that adversely affects the stability of these devices when exposed to continuous light. To address this issue, we developed an effective strategy involving polishing PbI 2 on a perovskite surface using CsF. In this study, we investigated the effects of CsF post-treatment on perovskite films and their photovoltaic properties. The results of the time-resolved photoluminescence and ultraviolet photoelectron spectroscopy tests reveal the significant positive impact of our passivation method based on CsF, which reduces the valence band offset between the perovskite and hole transport layers while simultaneously enhancing the carrier interface transport. PSCs treated with CsF exhibited a photoelectric conversion efficiency (PCE) of 24.25% and an increased fill factor (FF) of 81.72%, which surpassed those of the original PSCs (PCE = 22.12% and FF = 77.40%). Furthermore, after aging for over 2500 h at room temperature and in 30 ± 10% humidity, the PCE of the unpacked PSCs reduced to only 42% of the initial value. Furthermore, the devices treated with CsF maintained their impressive performance, with the PCE maintaining optimal levels at 91% of the initial efficiency. [ABSTRACT FROM AUTHOR]

In this study, Li 0.42 Zn 0.27 Ti 0.11 Mn 0.1 Fe 2.1 O 4 ferrites were co-fired with Bi 2 O 3 –B 2 O 3 (BB) additive at low sintering temperatures (∼920 °C), and the effects of BB additive on various properties of Li–Zn ferrites were systematically investigated. First of all, the existence of BB additive would not pollute the spinel phases of Li–Zn ferrites, in contrast, it could make the ferrites well-ripened at low temperatures. The micro-morphology results revealed that the introduction of BB additive could significantly promote the grain growth, where the average diameter of grain size increased from 0.81 μm (0.0 wt % BB) to 8.12 μm (0.5 wt % BB), leading to a higher densification degree and density. Owing to the liquid phase formed in the sintering process, magnetic properties of the Li–Zn ferrites were improved with the assistance of BB additive. The saturation flux density (B s) and saturation magnetization could reach a maximum value of 319.3 mT and 74.2 emu/g, respectively. The coercivity (H c) and ferromagnetic resonance (FMR) linewidths (ΔH) could reach a minimum value of 176.3 A/m and 243.2 Oe, respectively. Finally, it is noted that the optimal values of these parameters are obtained under the condition of 0.5 wt % BB additive doped, and most magnetic properties would be deteriorated when exceeding the above content. Thus, BB additive is considered as a promising sintering aid for synthesizing Li–Zn ferrites at low temperatures, which will play a vital role in the development of low-temperature co-fired ceramics (LTCC) technology. [ABSTRACT FROM AUTHOR]

In graphene electronics applications, in order to obtain the size and pattern required for the device, it is often necessary to photolithography the graphene after growth, resulting in contamination of graphene by the photoresist which have doping effect. Therefore, in order to avoid this effect, this article focused on directly grown patterned graphene. Based on atmospheric pressure chemical vapour deposition (APCVD) technology, patterned graphene was successfully grown on SiO2/Si by metal proximity catalytic effect. The patterned graphene was characterized by Raman spectroscopy and optical microscope. The effects of parameters such as gas flow, growth temperature, and growth time on the growth of patterned graphene were explored, and the best results were obtained. Metal copper and cobalt thin films were used for assisted catalysis, respectively, and the mechanism of metal proximity catalysis was explored. The experimental results showed that proximity catalysis is a catalytic growth mechanism based on surface diffusion. The growth method avoids using photolithography to make patterns, and can grow patterned graphene on insulating substrates or semiconductors in one step, which is of great significance for making patterned graphene and applying them to semiconductor devices. [ABSTRACT FROM AUTHOR]

Fully convolutional neural network has shown advantages in the salient object detection by using the RGB or RGB-D images. However, there is an object-part dilemma since most fully convolutional neural network inevitably leads to an incomplete segmentation of the salient object. Although the capsule network is capable of recognizing a complete object, it is highly computational demand and time consuming. In this paper, we propose a novel convolutional capsule network based on feature extraction and integration for dealing with the object-part relationship, with less computation demand. First and foremost, RGB features are extracted and integrated by using the VGG backbone and feature extraction module. Then, these features, integrating with depth images by using feature depth module, are upsampled progressively to produce a feature map. In the next step, the feature map is fed into the feature-integrated convolutional capsule network to explore the object-part relationship. The proposed capsule network extracts object-part information by using convolutional capsules with locally-connected routing and predicts the final salient map based on the deconvolutional capsules. Experimental results on four RGB-D benchmark datasets show that our proposed method outperforms 23 state-of-the-art algorithms. [ABSTRACT FROM AUTHOR]

Instance segmentation in remote sensing (RS) imagery aims to predict the locations of instances and represent them with pixel-level masks. Thanks to the more accurate pixel-level information for each instance, instance segmentation has enormous potential applications in resource planning, urban surveillance, and military reconnaissance. However, current RS imagery instance segmentation methods mostly follow the fully supervised paradigm, relying on expensive pixel-level labels. Moreover, remote sensing imagery suffers from cluttered backgrounds and significant variations in target scales, making segmentation challenging. To accommodate these limitations, we propose a semantic attention enhancement and structured model-guided multi-scale weakly supervised instance segmentation network (SASM-Net). Building upon the modeling of spatial relationships for weakly supervised instance segmentation, we further design the multi-scale feature extraction module (MSFE module), semantic attention enhancement module (SAE module), and structured model guidance module (SMG module) for SASM-Net to enable a balance between label production costs and visual processing. The MSFE module adopts a hierarchical approach similar to the residual structure to establish equivalent feature scales and to adapt to the significant scale variations of instances in RS imagery. The SAE module is a dual-stream structure with semantic information prediction and attention enhancement streams. It can enhance the network's activation of instances in the images and reduce cluttered backgrounds' interference. The SMG module can assist the SAE module in the training process to construct supervision with edge information, which can implicitly lead the model to a representation with structured inductive bias, reducing the impact of the low sensitivity of the model to edge information caused by the lack of fine-grained pixel-level labeling. Experimental results indicate that the proposed SASM-Net is adaptable to optical and synthetic aperture radar (SAR) RS imagery instance segmentation tasks. It accurately predicts instance masks without relying on pixel-level labels, surpassing the segmentation accuracy of all weakly supervised methods. It also shows competitiveness when compared to hybrid and fully supervised paradigms. This research provides a low-cost, high-quality solution for the instance segmentation task in optical and SAR RS imagery. [ABSTRACT FROM AUTHOR]

Rubidium laser optically pumped magnetometers (OPMs) are widely used magnetic sensors based on the Zeeman effect, laser pumping, and magnetic resonance principles. They measure the magnetic field by measuring the magnetic resonance signal passing through a rubidium atomic gas cell. The quality of the magnetic resonance signal is a necessary condition for a magnetometer to achieve high sensitivity. In this research, to obtain the best magnetic resonance signal of rubidium laser OPMs in the Earth's magnetic field intensity, the experiment system of rubidium laser OPMs is built with a rubidium atomic gas cell as the core component. The linewidth and amplitude ratio (LAR) of magnetic resonance signals is utilized as the optimization objective function. The magnetic resonance signals of the magnetometer experiment system are experimentally measured for different laser frequencies, radio frequency (RF) intensities, laser powers, and atomic gas cell temperatures in a background magnetic field of 50,765 nT. The experimental results indicate that optimizing these parameters can reduce the LAR by one order of magnitude. This shows that the optimal parameter combination can effectively improve the sensitivity of the magnetometer. The sensitivity defined using the noise spectral density measured under optimal experimental parameters is 1.5 pT/Hz1/2@1 Hz. This work will provide key technical support for rubidium laser OPMs' product development. [ABSTRACT FROM AUTHOR]

We measure the galaxy-ellipticity (GI) correlations for the Sloan Digital Sky Survey Data Release 12 LOWZ and CMASS samples with the shape measurements from the DESI Legacy Imaging Surveys. We model the GI correlations in an N -body simulation with our recent accurate stellar–halo mass relation from the Photometric object Around Cosmic webs (PAC) method. The large data set and our accurate modeling turns out an accurate measurement of the alignment angle between central galaxies and their host halos. We find that the alignment of central elliptical galaxies with their host halos increases monotonically with galaxy stellar mass or host halo mass, which can be well described by a power law for the massive galaxies. We also find that central elliptical galaxies are more aligned with their host halos in LOWZ than in CMASS, which might indicate an evolution of galaxy–halo alignment, though future studies are needed to verify this is not induced by the sample selections. In contrast, central disk galaxies are aligned with their host halos about 10 times more weakly in the GI correlation. These results have important implications for intrinsic alignment (IA) correction in weak lensing studies, IA cosmology, and theory of massive galaxy formation. [ABSTRACT FROM AUTHOR]

This paper proposes using spatially distributed TMD-type counterweights for the multiple-mode vibration control of irregular bridges subjected to wind loads. In particular, the governing equations of the bridge with TMD-type counterweights that are spatially distributed at any transverse and/or longitudinal positions of the bridge girder are established. Four objective functions are formulated and compared, and an optimum design method is developed to obtain the optimal design parameters of the TMD-type counterweights for each objective. Subsequently, an irregular cable-stayed bridge equipped with counterweight blocks is chosen as the prototype to demonstrate the control effectiveness of TMD-type counterweights. The results show that the proposed method is feasible for the multiple-mode vibration control of irregular bridges, and TMD-type counterweights show good control efficiency and robustness performance, providing an attractive alternative to traditional counterweights in the vibration control, especially multiple-mode vibration control, of irregular bridges. [ABSTRACT FROM AUTHOR]

Background: Intra-tumoral heterogeneity (ITH) is a distinguished hallmark of cancer, and cancer stem cells (CSCs) contribute to this malignant characteristic. Therefore, it is of great significance to investigate and even target the regulatory factors driving intra-tumoral stemness. c-Myc is a vital oncogene frequently overexpressed or amplified in various cancer types, including breast cancer. Our previous study indicated its potential association with breast cancer stem cell (BCSC) biomarkers. Methods: In this research, we performed immunohistochemical (IHC) staining on sixty breast cancer surgical specimens for c-Myc, CD44, CD24, CD133 and ALDH1A1. Then, we analyzed transcriptomic atlas of 1533 patients with breast cancer from public database. Results: IHC staining indicated the positive correlation between c-Myc and BCSC phenotype. Then, we used bioinformatic analysis to interrogate transcriptomics data of 1533 breast cancer specimens and identified an intriguing link among c-Myc, cancer stemness and copper-induced cell death (also known as "cuproptosis"). We screened out cuproptosis-related characteristics that predicts poor clinical outcomes and found that the pro-tumoral cuproptosis-based features were putatively enriched in MYC-targets and showed a significantly positive correlation with cancer stemness. Conclusion: In addition to previous reports on its oncogenic roles, c-Myc showed significant correlation to stemness phenotype and copper-induced cell toxicity in breast cancer tissues. Moreover, transcriptomics data demonstrated that pro-tumoral cuproptosis biomarkers had putative positive association with cancer stemness. This research combined clinical samples with large-scale bioinformatic analysis, covered description and deduction, bridged classic oncogenic mechanisms to innovative opportunities, and inspired the development of copper-based nanomaterials in targeting highly heterogeneous tumors. [ABSTRACT FROM AUTHOR]

With the growing incidence of cardiovascular disease (CVD) in recent decades, the demand for out-of-hospital real-time ECG monitoring is increasing day by day, which promotes the research and development of portable ECG monitoring equipment. At present, two main categories of ECG monitoring devices are "limb lead ECG recording devices" and "chest lead ECG recording devices", which both require at least two electrodes. The former needs to complete the detection by means of a two-hand lap joint. This will seriously affect the normal activities of users. The electrodes used by the latter also need to be kept at a certain distance, usually more than 10 cm, to ensure the accuracy of the detection results. Decreasing the electrode spacing of the existing ECG detection equipment or reducing the area required for detection will be more conducive to improving the integration of the out-of-hospital portable ECG technologies. Therefore, a single-position ECG system based on charge induction is proposed to realize ECG detection on the surface of the human body with only one electrode with a diameter of less than 2 cm. Firstly, the ECG waveform detected in a single location is simulated by analyzing the electrophysiological activities of the human heart on the human body surface with COMSOL Multiphysics 5.4 software. Then, the hardware circuit design of the system and the host computer are developed and the test is performed. Finally, experiments for static and dynamic ECG monitoring are carried out and the heart rate correlation coefficients are 0.9698 and 0.9802, respectively, which proves the reliability and data accuracy of the system. [ABSTRACT FROM AUTHOR]

Based on the panel data of 123 city commercial banks in China from 2007 to 2017, we use the dynamic panel system GMM estimation method to empirically test the impact of private capital holdings on the stability of city commercial banks. The results show that private capital holding improves the operating performance of city commercial banks, reduces the volatility of return on total assets, and is conducive to the stability of city commercial banks. Furthermore, the lack of financial awareness of local governments has led to the negative impact of private capital, that is, the stability of the banks has declined. [ABSTRACT FROM AUTHOR]

Nitrogen (N) is one of the most important mineral elements for plant growth and development and a key factor for improving crop yield. Rapeseed, Brassica napus, is the largest oil crop in China, producing more than 50% of the domestic vegetable oil. However, high N fertilizer input with low utilization efficiency not only increases the production cost but also causes serious environmental pollution. Therefore, the breeding of rapeseed with high N efficiency is of great strategic significance to ensure the security of grain and oil and the sustainable development of the rapeseed industry. In order to provide reference for genetic improvement of rapeseed N-efficient utilization, in this article, we mainly reviewed the recent research progress of rapeseed N efficiency, including rapeseed N efficiency evaluation, N-efficient germplasm screening, and N-efficient physiological and molecular genetic mechanisms. [ABSTRACT FROM AUTHOR]

Fully convolutional neural network has shown advantages in the salient object detection by using the RGB or RGB-D images. However, there is an object-part dilemma since most fully convolutional neural network inevitably leads to an incomplete segmentation of the salient object. Although the capsule network is capable of recognizing a complete object, it is highly computational demand and time consuming. In this paper, we propose a novel convolutional capsule network based on feature extraction and integration for dealing with the object-part relationship, with less computation demand. First and foremost, RGB features are extracted and integrated by using the VGG backbone and feature extraction module. Then, these features, integrating with depth images by using feature depth module, are upsampled progressively to produce a feature map. In the next step, the feature map is fed into the feature-integrated convolutional capsule network to explore the object-part relationship. The proposed capsule network extracts object-part information by using convolutional capsules with locally-connected routing and predicts the final salient map based on the deconvolutional capsules. Experimental results on four RGB-D benchmark datasets show that our proposed method outperforms 23 state-of-the-art algorithms. [ABSTRACT FROM AUTHOR]

In present paper, a novel flowable tritium breeder is prepared by mixing the Li2TiO3 micro-powders and liquid GaInSn alloy, where GaInSn alloy is used to simulate the fluid behaviors of lithium-based liquid tritium breeder, forming a type of composite characterized by liquid-solid dual phase. In detail, the effects of the volume fraction of ceramic micro-powders on viscosity and conductivity of the composite in magnetic field are the focus. The XRD results prove that the obtained Li2TiO3 micro-powders contained Li2TiO3 phase without impurities. The results shows that once the magnetic field intensity exceeds the critical value, the viscosity of liquid GaInSn metal becomes significantly greater than that of liquid-solid dual-phase composites. Furthermore, the addition of Li2TiO3 micro-powders could effectively reduce the magneto hydro dynamic (MHD) fluid effect, and the dual-phase composites exhibit comparatively lower flow resistance under the strong magnetic field. Moreover, the conductivity of the tritium breeder composites decreases rapidly with the addition of Li2TiO3 micro-powders. The MHD pressure-drop-increasing rate decreases with the increase of viscosity, which indicates that the addition of Li2TiO3 micro-powders effectively reduces the MHD effect. The conductivity of the composites increased slightly and then remained stable after static placing for several tens of minutes. The present investigation provides a novel insight into the fabrication strategy of tritium breeder materials with low MHD effect. [ABSTRACT FROM AUTHOR]

Aims/Introduction: To investigate the impact of visceral adipose tissue (VAT) on atherosclerosis in type 2 diabetes patients with normal bodyweight (OB[−]) in the Chinese population, and to further assess the sex–age differences between them. Materials and Methods: A total of 8,839 type 2 diabetes patients from two of the National Metabolic Management Centers in China were included in this study. Participants were classified into four groups by visceral fat area (VFA; cm2) and body mass index (BMI; kg/m2): VFA < 100 and BMI < 23.9 (VA[−]OB[−]), VFA < 100 and BMI ≥ 23.9 (VA[−]OB[+]), VFA ≥ 100 and BMI < 23.9 (VA[+]OB[−]), VFA ≥ 100 and BMI ≥ 23.9 (VA[+]OB[+]). Atherosclerosis was defined by brachial‐ankle pulse wave velocity (baPWV; cm/s), and we analyzed the association between VFA, BMI and the tertiles of baPWV values. Results: The VA(+)OB(−) prevalence was 3.7% among these participants. Patients with VA(+)OB(−) had the highest baPWV value (P < 0.001) and the highest proportion of the tertile 3 of baPWV (P < 0.001) among four groups, and were significantly associated with baPWV (standardized β = 0.026, P = 0.008). VFA was significantly related to tertile 2 to tertile 3 of baPWV in (OB[−]) type 2 diabetes patients, when compared with tertile 1 of baPWV, respectively. In sex–age stratified analysis, the association of VFA and the tertiles of baPWV showed sex differences. For the 55 years age stratification analysis, there was no age difference in the relationship between VFA and baPWV in (OB[−]) patients. Conclusion: Increased VAT was an independent risk factor for atherosclerosis in female type 2 diabetes patients with normal weight. [ABSTRACT FROM AUTHOR]

Flame detection is of great significance in a fire prevention system. YOLOv4 has poor real-time performance on flame detection caused by the complex structure and high parameter size. To address this problem, a novel flame detection framework, YOLO for flame (YOLO-F), is proposed in this paper. The backbone of YOLOv4 is simplified from the original 53 convolutional layers to 34 convolutional layers to reduce the number of parameters by simplifying the structure of the CSPBlock. Based on the FPN, an effective and light-weight feature pyramid architecture, namely FPNs-SE, is then proposed and the neck part of YOLOv4 is replaced by FPNs-SE to enhance the feature extraction ability of different scales. In addition, the CIoU loss in the YOLOv4 ignores the similarity measure of the area between the predicted bounding box and the ground-truth bounding box. An effective loss named ACIoU is proposed in this paper in order to handle the above issue and further improve the detection accuracy. The proposed methods are tested on FLAME dataset and network crawled dataset, respectively. The mAP, recall, and precision of YOLO-F are higher by 2.01%, 4.0%, 2.0% on average than those of YOLOv4. With input size of 4 1 6 × 4 1 6 and on a single GTX 1660, the operating speed of our method can reach 24.53 fps, which is improved by 38.04% compared with YOLOv4. The experimental results show that our method is more robust to the small flame and flame-like objects and can achieve the best balance of detection speed and accuracy. The code is made available at https://github.com/Windxy/YOLO-F. [ABSTRACT FROM AUTHOR]

We propose a unified game-theoretical framework to perform classification and conditional image generation given limited supervision. It is formulated as a three-player minimax game consisting of a generator, a classifier and a discriminator, and therefore is referred to as Triple Generative Adversarial Network (Triple-GAN). The generator and the classifier characterize the conditional distributions between images and labels to perform conditional generation and classification, respectively. The discriminator solely focuses on identifying fake image-label pairs. Theoretically, the three-player formulation guarantees consistency. Namely, under a nonparametric assumption, the unique equilibrium of the game is that the distributions characterized by the generator and the classifier converge to the data distribution. As a byproduct of the three-player formulation, Triple-GAN is flexible to incorporate different semi-supervised classifiers and GAN architectures. We evaluate Triple-GAN in two challenging settings, namely, semi-supervised learning and the extremely low data regime. In both settings, Triple-GAN can achieve excellent classification results and generate meaningful samples in a specific class simultaneously. In particular, using a commonly adopted 13-layer CNN classifier, Triple-GAN outperforms extensive semi-supervised learning methods substantially on several benchmarks no matter data augmentation is applied or not. [ABSTRACT FROM AUTHOR]

We propose a unified game-theoretical framework to perform classification and conditional image generation given limited supervision. It is formulated as a three-player minimax game consisting of a generator, a classifier and a discriminator, and therefore is referred to as Triple Generative Adversarial Network (Triple-GAN). The generator and the classifier characterize the conditional distributions between images and labels to perform conditional generation and classification, respectively. The discriminator solely focuses on identifying fake image-label pairs. Theoretically, the three-player formulation guarantees consistency. Namely, under a nonparametric assumption, the unique equilibrium of the game is that the distributions characterized by the generator and the classifier converge to the data distribution. As a byproduct of the three-player formulation, Triple-GAN is flexible to incorporate different semi-supervised classifiers and GAN architectures. We evaluate Triple-GAN in two challenging settings, namely, semi-supervised learning and the extremely low data regime. In both settings, Triple-GAN can achieve excellent classification results and generate meaningful samples in a specific class simultaneously. In particular, using a commonly adopted 13-layer CNN classifier, Triple-GAN outperforms extensive semi-supervised learning methods substantially on several benchmarks no matter data augmentation is applied or not. [ABSTRACT FROM AUTHOR]

With the increment of cable length, long stay cables are prone to experience high-mode vortex-induced vibrations (VIVs) at normal wind velocities, and the VIV-prone mode range also becomes wider. Existing dampers cannot supply sufficient damping for such a wide range of high-modes. Inerter-based dampers (IBDs), which take advantage of the two-terminal inertial device dubbed inerter, have been proved to have a better control performance than conventional dampers. However, existing studies on IBDs only focused on the first several cable modes, which cannot cover the wide range of VIV-prone modes of long stay cables. The high-mode and multi-mode VIV control by using IBDs is investigated in this study. The governing equations of the cable-IBD systems under VIV are first established. The control efficiency of the IBDs and the influence of optimum design strategies are compared. The use of two IBDs to further enhance the control efficiency is also discussed. The results show that a three-element IBD in this study is quite effective for high-mode and multi-mode VIV control of long stay cables. Moreover, the multi-mode control efficiency can be further improved through using two IBDs. The results in this study can guide the design of IBDs for VIV control of long stay cables. [ABSTRACT FROM AUTHOR]

Based on the microseismic monitoring data of underground cavern of Shuangjiangkou Hydropower Station, the internal relationship between rockburst and microseismic events is analyzed and the occurrence mechanism of slip-type rockburst in underground cavern of Shuangjiangkou Hydropower Station is analyzed through the change of microseismic monitoring b value to warn the risk level of rockburst. The results show that microseismic events are closely related to excavation activities, and the change of b value reflects the rockburst risk level. The smaller the b value of microseismic events is, the more large magnitude events is and the greater the possibility of rockburst is. The slip-type rockburst was mainly affected by structural plane; it is due to the accumulation of elastic strain energy at the structural plane and the sudden release under the action of unloading or disturbance, driving the block on the structure surface fast slide, mainly manifested as the sliding of large blocks of surrounding rock, and forming a "V" shape pit blasting or cuneate blasting crater, as well as destruction with crackle. Compared with the strained rockburst, the damage is more serious. The research results can provide reference for rockburst prediction and prevention in similar deep rock engineering. [ABSTRACT FROM AUTHOR]

The original rock taken from underground powerhouses of Shuangjiangkou Hydropower Station in south-west China was employed to prepare granite samples containing fractures with different dip angles, widths, and lengths. On this basis, the failure process of rock samples with different shapes of fractures under triaxial loading was investigated; furthermore, the mechanical properties, failure mode, and energy transfer of fractured granite under triaxial loading were revealed. The results showed that a significant post-peak stress drop occurs, and the stress then slowly decreases in the form of repeated drops and increases under triaxial compression. The larger the fracture width, the greater the stress drop; with increasing fracture length, the peak stress decreases and the stress varies from slow, fluctuating reduction to abrupt reduction in the post-peak stage. The failure angle of fractured granite grows with the increase of the confining pressure; as the fracture length increases, X-shaped shear failure mode is gradually prominent and the pre-fabricated fractures more significantly dominate the failure mode; at the dip angle within 0 to 60°, the samples are mainly subjected to X-shaped shear failure. The energy storage limit of fractured granite linearly increases with the increase of the confining pressure while linearly decreases with the increase of the fracture length, and it first decreases, and then increases with increasing fracture dip angle. [ABSTRACT FROM AUTHOR]

• A TMDI-controlled primary structure is evaluated under base excitations. • Closed-form tuning formulas of non-grounded TMDI are derived. • Performance of proposed formulas are compared with those in the literature. • Control and dissipation performances are verified under actual ground motions. This research contributes new analytical formulae for H ∞ optimal tuning of non-grounded tuned mass-damper-inerter (TMDI) for minimizing free-end displacement of base-excited cantilevered structures. The derivation relies on the fixed-point theory, making use of single-mode modelling of the cantilevered structure while accommodating arbitrary TMDI placement along the structural height. Optimal TMDI tuning parameters are derived for given dominant mode shape of structure and TMDI inertial properties (i.e., secondary mass and inertance) under two different types of harmonic excitations with frequency-independent displacement and acceleration amplitudes. The applicability of the derived TMDI tuning formulae for response mitigation of lightly damped cantilevered structures under stationary broadband support excitation is established through comparisons with numerically optimal TMDI properties for a wide range of TMDI inertial properties. Moreover, the analytical TMDI tuning formulae derived in this study achieve enhanced structural performance for base-excited structures compared to those from the literature, derived under various modelling assumptions and optimality criteria. Lastly, the potential of the proposed TMDI tuning for structural response mitigation is numerically evaluated by examining displacement, acceleration, and energy dissipation response history data of an experimentally identified reinforced concrete bridge pier model subjected to 100 earthquake ground motion (GM) records. Overall, reported results demonstrate that the derived analytical formulae can significantly extend the practical application of TMDI as a bona fide dynamic vibration absorber for base-excited structures by circumventing the need for computationally demanding numerical TMDI tuning optimization. [Display omitted] [ABSTRACT FROM AUTHOR]

We provide a method for estimating the projected density distribution n ÂŻ 2 w p (r p) of photometric objects around spectroscopic objects in a spectroscopic survey. This quantity describes the distribution of photometric sources with certain physical properties (e.g., luminosity, mass, and color) around cosmic webs (PAC) traced by the spectroscopic objects. The method can make full use of current and future deep and wide photometric surveys to explore the formation of galaxies up to medium redshift (z s < 2) 33 Throughout the paper, we use z s for redshift, z for the z -band magnitude, z p for the photometric redshift. with the aid of cosmological spectroscopic surveys that sample only a fairly limited species of objects (e.g., emission line galaxies). As an example, we apply the PAC method to the CMASS spectroscopic and HSC-SSP PDR2 photometric samples to explore the distribution of galaxies for a wide range of stellar masses from 109.0 to 1012.0 M ⊙ around massive stars at z s ≈ 0.6. Using the abundance-matching method, we model n ÂŻ 2 w p (r p) in N -body simulation using Markov chain Monte Carlo sampling, and we accurately measure the stellarâ€"halo mass relation and stellar mass function for the whole mass range. We can also measure the conditional stellar mass function of satellites for central galaxies of different mass. The PAC method has many potential applications for studying the evolution of galaxies. [ABSTRACT FROM AUTHOR]

Breast cancer is one of the most-common female malignancies with a high risk of relapse and distant metastasis. The distant metastasis of breast cancer exhibits organotropism, including brain, lung, liver and bone. Breast cancer stem cells (BCSCs) are a small population of breast cancer cells with tumor-initiating ability, which participate in regulating distant metastasis in breast cancer. We investigated the heterogeneity of BCSCs according to biomarker status, epithelial or mesenchymal status and other factors. Based on the classical "seed and soil" theory, we explored the effect of BCSCs on the metastatic organotropism in breast cancer at both "seed" and "soil" levels, with BCSCs as the "seed" and BCSCs-related microenvironment as the "soil". We also summarized current clinical trials, which assessed the safety and efficacy of BCSCs-related therapies. Understanding the role of BCSCs heterogeneity for regulating metastatic organotropism in breast cancer would provide a new insight for the diagnosis and treatment of advanced metastatic breast cancer. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (COVID-19) has caused millions of deaths, and serious consequences to public health, economies and societies. Rapid responses in vaccine development have taken place since the isolation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the release of the viral genome sequence. By 21 May 2021, 101 vaccines were under clinical trials, and published data were available for 18 of them. Clinical study results from some vaccines indicated good immunogenicity and acceptable reactogenicity. Here, we focus on these 18 vaccines that had published clinical data to dissect the induced humoral and cellular immune responses as well as their safety profiles and protection efficacy. [ABSTRACT FROM AUTHOR]

Fast radio bursts (FRBs) are mysterious radio transients with millisecond durations. Recently, ∼16 days of periodic activity and ∼159 days of possible periodicity were detected to arise from FRB 180916.J0158+65 and FRB 121102, respectively, and the spin period of a slow-rotation magnetar was further considered to be one of the possible explanations of the periodic activities of repeating FRBs. For isolated neutron stars, the spin evolution suggests that it has difficulty reaching several hours. In this work, we mainly focus on the possible maximum spin period of isolated NSs/magnetars dominated by an interaction between a star's magnetic field and the disk. We find that the disk wind plays an important role in spin evolution, whose influence varies the power-law index in the evolution equation of mass flow rate. For a magnetar without disk wind, the longest spin period is tens of hours. When the disk wind with a classical parameter is involved, the maximum spin period can reach hundreds of hours. But for an extremely large index of mass flow rate due to disk wind or other angular momentum extraction processes, a spin period of ∼(16–160) days is still possible. [ABSTRACT FROM AUTHOR]

We present a two-dimensional particle–particle–particle-mesh (P3M) algorithm with an optimized Green's function and adaptive softening length for gravitational lensing studies in N-body simulations. The analytical form of the optimized Green's function is given. The softening schemes (S) are studied for both the particle-mesh (PM) and the particle–particle (PP) calculations in order for accurate force calculation and suppression of the particle discreteness effect. Our method is two orders of magnitude more accurate than the simple PM algorithm with the poor man's Green's function (∝ 1/k2) at a scale of a few mesh cells or smaller. The force anisotropy is also much smaller than the conventional PM calculation. We can achieve a force accuracy better than 0.1% at all scales with our algorithm, which makes it an ideal (accurate and fast) algorithm for microlensing studies. When we apply the algorithm to computing weak and strong lensing quantities in N-body simulations, the errors are dominated by the Poisson noise caused by particle discreteness. The Poisson noise can be suppressed by smoothing out the particle distribution, which can be achieved by simply choosing an adaptive softening length in the PP calculation. We have presented a criterion to set the adaptive softening length. Our algorithm is also applicable to cosmological simulations. We provide a python implementation P3Mlens for this algorithm. [ABSTRACT FROM AUTHOR]

• A mesh stiffness model of spur gear pairs with tooth profile errors is established based on slice theory with slice coupling. • The slice coupling is equivalent to a spring and the corresponding stiffness model is presented. • A deformation transfer coefficient is derived between the springs in contact state and non-contact state. • The solving procedure of the mesh stiffness model is studied, in which an iterative computation method is designed. The misalignment and lead crown relief make the tooth partial contact along the tooth width direction, which greatly affects the mesh characteristics. In this paper, a mesh stiffness model of spur gear pairs with misalignment and lead crown relief is proposed based on the slice theory, in which the slice coupling effect is presented. The slice coupling is simulated as a spring and the corresponding model is developed. Then, the solving procedure of the mesh stiffness model is studied. The deformation transfer model is derived between the springs in contact state and non-contact state. An iterative computation method is designed to calculate the mesh deformation of tooth pairs. Finally, the mesh stiffness model is validated by the finite element method for a spur gear pair with ideal tooth profile, misalignment and lead crown relief. Effects of the misalignment and lead crown relief on mesh stiffness of gear pairs are also studied. The results reveal that the proposed model is accurate, effective and efficient for spur gear pairs with ideal tooth profile, misalignment and lead crown relief. It is suggested that the slice coupling should be considered in mesh stiffness calculation of gear pairs with misalignment and lead crown relief. [ABSTRACT FROM AUTHOR]

Metal-organic frameworks (MOFs) are novel crystalline porous materials assembled from metal ions and organic ligands. The adaptability of their design and the fine-tuning of the pore structures make them stand out in porous materials. Furthermore, by integrating MOF guest functional materials with other hosts, the novel composites have synergistic benefits in numerous fields such as batteries, supercapacitors, catalysis, gas storage and separation, sensors, and drug delivery. This article starts by examining the structural relationship between the host and guest materials, providing a comprehensive overview of the research advancements in various types of MOF-functionalized composites reported to date. The review focuses specifically on four types of spatial structures, including MOFs being (1) embedded in nanopores, (2) immobilized on surface, (3) coated as shells and (4) assembled into hybrids. In addition, specific design ideas for these four MOF-based composites are presented. Some of them involve in situ synthesis method, solvothermal method, etc. The specific properties and applications of these materials are also mentioned. Finally, a brief summary of the advantages of these four types of MOF composites is given. Hopefully, this article will help researchers in the design of MOF composite structures. This paper reviews the significant progress of MOF-functionalized composites in the fields of adsorption, biology, and catalysis from the perspective of host-guest composite structure relationships. The key qualitative properties and preparation schemes of four types of composite structures are elucidated, and the potential structure-property-application relationships are highlighted. [Display omitted] • Starting from the spatial structure of the host and guest materials. • Reviewing four spatial structures of MOF-functional composites. • Summarizing specific design routes and advantages for each structure. • Synergistic effects of MOF-functional composites. • Analyzing the relationship between structure-performance-application. [ABSTRACT FROM AUTHOR]

A compressible ZIF-67/polyacrylamide/chitosan composite aerogel (named as ZIF-67/PAM/CSA) is prepared by two-step method with in-situ polymerization and growth, which exhibits excellent compressible property and efficient adsorption performance of tetracycline. The loading capacity of ZIF-67 in ZIF-67/PAM/CSA can reach 42.7%, making the increased specific surface area up to 491.95 m2 g−1 for composite aerogel. For tetracycline adsorption, ZIF-67/PAM/CSA presents high capacity of 260.09 mg g−1 as well as stable enough recycling availability. The composite aerogel synthesized here with high specific surface area and compressibility, offers a promising method to branch out compressible adsorbents with benefits for the adsorption regeneration process in pollutant treatment applications. We prepared a novel compressible ZIF-67/PAM/CSA using a two-step method of in-situ polymerization and in-situ growth. Its specific surface area can reach 491.95 m2 g−1, and its adsorption capacity for TC can reach 260.09 mg g−1, realizing great potential ambition in water treatment applications. [Display omitted] • A new type of compressible ZIF-67/PAM/CSA was prepared by two-step method with in situ polymerization and in situ growth. • The content of ZIF-67 in ZIF-67/PAM/CSA can reach 42.7%. • The specific surface area of ZIF-67/PAM/CSA can reach 491.95 m2 g−1. • The adsorption capacity of ZIF-67/PAM/CSA for TC reaches 260.09 mg g−1. [ABSTRACT FROM AUTHOR]

[Display omitted] • A lightweight 3D CNN for MPM is proposed, which adopts the inception structure of GoogleNet and combines the idea of end-to-end learning. • The 3D geophysical and geological models are used to facilitate the ore-controlling representation. • The predicted results between the WofE and our proposed 3D CNN method for MPM are compared. With the continuous exploitation of surface and shallow mineral resources, the global demand for concealed ore deposit exploration is increasing. However, concealed mineral prospectivity modeling (MPM) requires significant efforts, particularly in terms of methods and technologies for three-dimensional modeling. In this study, we propose a lightweight three-dimensional convolutional neural network (3D CNN) for MPM, which adopts the inception structure of GoogleNet and combines the idea of end-to-end learning. We replace the fully connected layer in the conventional CNN with deconvolution, which can greatly reduce the required parameters during the training process and accelerate the convergence. The proposed method overcomes the disadvantage that other shallow machine learning methods cannot extract spatial neighborhood information, while it can extract cross-correlations among geological factors and generates less parameters by a lightweight network when facing massive data. Additionally, compared with the patch-wise method commonly used in previous studies, we use the pixel-wise method for end-to-end learning, which not only overcomes the drawbacks of random sampling but also considers the influence of each voxel when calculating the loss function. The three-dimensional multi-source geoscientific characteristics obtained from the geophysical inversion and 3D geological models are not discretized in order to promote effective CNN training while facilitating the ore-controlling representation. Comparing the predicted results between the 3D weight of evidence (WofE) and our proposed 3D CNN method for MPM, our proposed method and WofE delineated 100% of the known mineralization in high-favorability areas with voxel numbers of 70% and 95%, respectively. A case study of a structure-controlled hydrothermal gold deposit in the Sanhetun area of Heilongjiang Province demonstrates that the proposed 3D CNN method performs better than WofE in terms of prediction effectiveness and efficiency and effectively reveals the correlation between mineralization and adjacent ore-controlling characteristics. Moreover, the proposed 3D CNN method can simulate non-linear metallogenic processes and mine hidden relationships to reveal complex ore-controlling characteristics. In conclusion, the proposed 3D CNN method can reduce the exploration effort in 3D MPM, thus greatly improving the efficiency of discovering concealed ore deposits. [ABSTRACT FROM AUTHOR]

In recent years, deep learning has been extensively applied to bearing fault diagnosis with remarkable achievements. However, in real industrial scenarios, the primary challenge in developing an effective intelligent diagnosis model is the scarcity of fault samples required for training due to shutting down operations during failure behavior. Simulation data-driven and data augmentation-based small sample diagnosis methods have their own limitations, including insufficient diagnostic performance and low data quality. In view of these, a novel mechanism-data fusion diagnosis scheme with bearing dynamic model and multi-agent diverse generative adversarial network (MAD-GAN) is proposed in this study. Specifically, the bearing dynamic model addresses the scarcity of failure samples by simulating vibration signals across various operating conditions. Besides, A simulation-real transformation model based on MAD-GAN is developed to achieve the conversion between simulated domain and real domain, which shares the diagnostic knowledge between two domains. Finally, the domain adversarial based comprehensive generalization network is improved by maximum mean discrepancy and metric learning to further generalize diagnosis knowledge from simulation domain to real domain. Two bearing experimental datasets are applicated and case studies are conducted under small sample, validating the effectiveness and superiority of the proposed method. Experimental results show the potential application of this method in real industrial scenarios. [ABSTRACT FROM AUTHOR]

Chemical vapor deposition (CVD) is one of the most important methods for the preparation of graphene. Graphene is usually prepared using horizontal tube CVD (HT-CVD) method. However, the preparation of this method is too long, generally more than 2 h. In this article, a method called vertical cold-wall CVD (VCW-CVD) method was introduced for graphene preparation. Due to the vertical angle between direction of gas flow and sample surface, the reaction process of this method for graphene preparation is only 1 min. Accordingly, in this article, the modified parameter of graphene preparation by this method was discussed. Besides, the VCW-CVD graphene had an equal quality with the HT-CVD graphene, which was proved by measurement of conductivity, transmittance and heat stability. [ABSTRACT FROM AUTHOR]

Drawing from prior literature on machine-generated news, this study examines machine-generated artworks in a cross-cultural context. It combines machine learning approaches with online experiments and investigates how different genres of artworks and different authorship cues influence participants' open-ended responses to machine-generated works. Results suggest that while genres and cultures affected participants' discussion topics and word use, the differences between participants' responses to machine-generated artworks and human-generated ones were not evident. This study tests the explanatory power of machine heuristic and demonstrates the feasibility of integrating multiple methods in future AI-based media research. [ABSTRACT FROM AUTHOR]

It is believed that massive galaxies have quenched their star formation because of active galactic nucleus feedback. However, recent studies have shown that some massive galaxies are still forming stars. We analyze the morphology of star formation regions for galaxies of stellar masses larger than 1011.3M⊙ at around redshift zr = 0.5 using u − z color images. We find that about 20% of the massive galaxies are star-forming (SF) galaxies, and most of them (∼85%) have asymmetric structures induced by recent mergers. Moreover, for these asymmetric galaxies, we find that the asymmetry of the SF regions becomes larger for bluer galaxies. Using the Illustris simulation, we can qualitatively reproduce the observed relation between asymmetry parameter and color. Furthermore, using the merger trees in the simulation, we find a correlation between the color of the main branch galaxies at zr = 0.5 and the sum of the star formation rates of the recently accreted galaxies, which implies that star formation of the accreted galaxies has contributed to the observed star formation of the massive (host) galaxies (ex situ star formation). Furthermore, we find two blue and symmetric galaxies, candidates for massive blue disks, in our observed sample, which indicates that about ∼10% of massive SF galaxies are forming stars in the normal mode of disk star formation (in situ star formation). With the simulation, we find that the disk galaxies at zr ≈ 0.5 should have experienced few major mergers during the last 4.3 Gyr. [ABSTRACT FROM AUTHOR]

• The first example of Ni-catalyzed Minisci acylation reaction was developed. • This protocol avoids using external chemical oxidants. • A ligand-to-metal electron transfer process was observed. A nickel-catalyzed electrochemical methodology for the Minisci acylation of aromatic electron-deficient heterocycles with α -keto acids has been developed. The reaction is performed in an undivided cell under constant current conditions, featuring broad scope of substrates and avoiding the conventional utilization of silver-based catalysts in conjunction with excess amount of oxidants. Cyclic voltammetric analysis disclosed that a ligand-to-metal electron transfer process may be involved in the generation of the key acyl radicals. [ABSTRACT FROM AUTHOR]

Ultrasonic tomography (UT) is a nondestructive technique that is widely applied in industrial process imaging. In this paper, a novel sector diffusion method for construction of a sensitivity matrix is proposed to improve the performance of a linear back-projection (LBP) algorithm. The so-called sector-diffusion-matrix-based LBP (SLBP) was applied to reconstruct gas/liquid two-phase flow. A series of models has been established to evaluate the effectiveness of the method. The images reconstructed by traditional LBP and SLBP are presented and compared. Two quantitative evaluation criteria including position error and image correlation coefficient ($I_{\mathrm {cr}}$) were defined and used to evaluate the quality of the reconstructed images. The imaging results indicate that the SLBP method is valid and feasible to improve the quality of reconstructed images, especially for a UT system with a small number of transducers. The evaluation criterion $I_{\mathrm {cr}}$ is improved by 26%, 20%, 9%, and 4% for four different flow patterns with an eight-transducer UT system in $128\times128$ pixels and improved by 26%, 20%, 10%, and 1% in $40\times40$ resolution. [ABSTRACT FROM AUTHOR]

Recently years have witnessed the rapid progress of the halide perovskite materials that could be applied to photovoltaics and light-emitting diodes (LED). Due to the structural similarity with respect to the three-dimensional (3D) halide perovskite materials, the molecular state of the halide perovskites has received much attention. In this manuscript, we employ first-principles calculations to systematically investigate the possible routes to design cesium-based molecular halide perovskite material Cs 4 MX 6 via substituting the halide and metal atoms. The substitution method is found to be effective to modulate the electronic and optical properties of the molecular halide perovskites. In particular, the halide mixing is beneficial to improve the optical properties of the Cs 4 PbX 6 molecules. We propose that the molecular halide perovskite Cs 4 MX 6 could be used as organic dye substitutes in various applications. This study is important for the fundamental understanding of the molecular halide perovskite materials and facilitates the design of Cs 4 MX 6 as alternative molecular dyes to be selected for optoelectronic applications. Image 1 • Cs 4 MX 6 molecules are compositionally engineered for light harvesting purpose. • Halogen substitution leads to red-shift in UV–vis with the ranking: I > Br > Cl. • Mixing different halide atoms into Cs 4 PbX 6 is more effective on light harvesting. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the anxiolytic and antidepressant effects of α- and β-amyrins in a mouse model of mild traumatic brain injury (mTBI), and the underlying mechanism(s) of action. Methods: Male Swiss mice (n = 165), weighing 25 - 40 g (mean weight = 32.5 ± 7.5 g), were used in this study. Existing mTBI model was modified and optimized for mild injury to brain capable of producing neurobehavioral changes. Forced swim test (FST) and tail suspension test (TST) were used to measure the antidepressant effects of α- and β-amyrins, while elevated plus maze (EPM) and light-dark model (LDM) were used for anxiety assessment. The probable mechanism of action of amyrin was also investigated through kinetics of serotonin uptake and activities of monoamine oxidases A (MAO A) and B (MAO B) in mouse hippocampus and cortex. Results: Induction of mTBI produced anxiety- and depression-like behaviors in mice. The 5th hitting righting time was 259 ± 25.11 s while duration of apnea was 27.33 ± 3.84 s. Apnea was significantly reduced on 5th and 7th hits, when compared with 4th and 6th hits (p < 0.05). The immobility time of mice was significantly reduced in FST and TST. A combination of the two forms of amyrin was more effective in reducing duration of immobility, relative to when each was used alone (p < 0.05). Amyrin significantly and dose-dependently increased entries, and time spent in open arms and light zone (p < 0.05). Mice in mTBI group exhibited a high degree of hopelessness, when compared with control group (p < 0.05). However, amyrin at a dose of 50 mg/kg significantly reduced the degree of hopelessness in the mice (p < 0.05). The specific activity of MAO A in hippocampal tissue (265.00 ± 12.07 μmol/min/g protein) was significantly higher than that of cortex (61.85 ± 5.14 μmol/min/g protein). In both tissues, there were no significant differences in the activity of MAO B among the groups (p > 0.05). Amyrin significantly reversed the effects of mTBI on the levels of amino acids in mice hippocampus and cortex (p < 0.05). The results of synaptosomal uptake of serotonin show that fluoxetin exhibited competitive inhibition of serotonin uptake, while amyrin exhibited mixed type inhibition. Conclusion: The results obtained show that α- and β-amyrins exert potent anxiolytic and antidepressant effects via mechanisms involving MAO and GABA in the hippocampus. [ABSTRACT FROM AUTHOR]

Traditional GCNs have limitations due to fixed convolutional kernels with a narrow receptive field, which prevent them from adequately learning the local fine-grained features between the points and frequently employ a max pooling function to eliminate noise (redundant information), exacerbating a substantial loss of global information during the sampling process. To address these issues, we propose a novel multi-level feature pyramid graph convolutional neural network that combines multi-scale adaptive atrous graph convolution (MSAGConv) and learnable graph pooling (LGP) techniques. With an adaptive atrous kernel in a multi-scale architecture, MSAGConv can mine more deeply into the local fine-grained features of the points, enhance the flexibility of the point convolution kernel, extend its perception field, and capture more rich semantic information between points across scales. Next, LGP aims to eliminate noise by maximizing practical global information retention. Our approach outperforms state-of-the-art shape classification and part segmentation techniques on the ModelNet40, ScanObjectNN, and ShapeNetPart datasets in comprehensive qualitative and quantitative evaluations. [ABSTRACT FROM AUTHOR]

The penetration of electric vehicles (EVs) in vehicle-to-grid (V2G) interaction can effectively assist the grid in achieving frequency regulation and peak load balancing. However, the customer perceives that participating in V2G services would result in the additional cycling of the battery and the accelerated aging of the EVs' power battery, which has become a major obstacle to the widespread adoption of V2G services. Most existing methods require long-term cycling data and battery parameters to quantify battery aging, which is not suitable for the V2G scenario with large-scale and short-time intervals. Consequently, the real-time and accurate quantification of battery aging for optimization remains a challenge. This study proposes a charging scheduling method for EVs that can accurately and online quantify battery aging. Firstly, V2G scheduling is formulated as an optimization problem by defining an online sliding window to collect real-time vehicle information on the grid, enabling online optimization. Secondly, battery aging is more accurately quantified by proposing a novel amplitude-based rain-flow cycle counting (MRCC) method, which utilizes the charging information of the battery within a shorter time period. Lastly, an intelligent optimization algorithm is employed to optimize the charging and discharging power of EVs, aiming to minimize grid fluctuations and battery aging. The proposed method is validated using a V2G scenario with 50 EVs with randomly generated behaviors, and the results demonstrate that the proposed online scheduling method not only reduces the EFCC of the battery by 8.4%, but also achieves results close to global optimization. [ABSTRACT FROM AUTHOR]

• A global–local design method based on the average absorption/transmission condition (AATC) is proposed. • The equivalent circuit model (ECM) is employed to derive the AATC. • A new structure of the honeycomb-core sandwich rasorber is designed and analyzed. Multi-function composite structures with unique electromagnetic and mechanical performance have attracted increasing interest in the design of airborne radomes. In this study, a novel global–local design method embedded with average absorption/transmission conditions (AATC) is proposed on the basis of the equivalent circuit model (ECM) to investigate the wideband absorption/transmission characteristics of a honeycomb-core sandwich rasorber (HSR) with a dual-polarized resistive sheet and second-order bandpass frequency-selective surfaces (FSS). The structure of the HSR is optimized by adopting the global–local design method combined with the finite element model (FEM). The calculation and simulation results show that the optimized HSR can realize a wide absorption band (3.9–17.9 GHz) and a wide transmission band (9.1–10.9 GHz) simultaneously. Moreover, the absorption/transmission performance of the HSR is independent of the polarizations and incident angles. The effectiveness of the proposed method is validated by the excellent electromagnetic performance of the optimized HSR. [ABSTRACT FROM AUTHOR]

• A novel lever-arm TMDI is proposed for vibration control of long-span bridges. • The influences of design parameters are systematically investigated. • Empirical design formulas are proposed. • Control performance is validated in both frequency and time domains. In this study, the lever mechanism is incorporated with the tuned mass damper inerter (TMDI) to further promote the practical application of TMDI in long-span bridges. Four potential configurations of the lever-arm tuned mass damper inerter (LTMDI) are first established, and the corresponding governing equations are derived. Then, the optimum configuration of LTMDI is identified by minimizing the peak of non-dimensional displacement frequency response function (FRF). Subsequently, the influences design parameters, such as mass ratio, inertance ratio, lever mass ratio, and spanning distance of the inerter are investigated. Based on the results, empirical design formulas of design parameters are proposed and verified. Finally, a cable-stayed bridge is adopted as a numerical case to further illustrate the performance of LTMDI in terms of response reduction and robustness. The results show that the involving of the lever into TMDI is an effective mechanism for implementing the inerter's spanning in long-span bridges. With this mechanism, it is practically feasible to achieve a high effectiveness, low space requirement and more robustness control device for long-span bridges. The developed design formulas have a high accuracy, which can provide reliable support for the design of the LTMDI in engineering applications. [ABSTRACT FROM AUTHOR]