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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]

Probing biomolecular interactions at cellular interfaces is crucial for understanding and interfering with life processes. Although affinity binders with site specificity for membrane proteins are unparalleled molecular tools, a high demand remains for novel multi‐functional ligands. In this study, a synthetic peptide (APQQ) with tight and specific binding to the untargeted extracellular loop of CD81 evolved from a genetically encoded peptide pool. With tailored affinity, APQQ flexibly accesses, site‐specifically binds, and forms a complex with CD81, enabling in‐situ tracking of the dynamics and activity of this protein in living cells, which has rarely been explored because of the lack of ligands. Furthermore, APQQ triggers the relocalization of CD81 from diffuse to densely clustered at cell junctions and modulates the interplay of membrane proteins at cellular interfaces. Motivated by these, efficient suppression of cancer cell migration, and inhibition of breast cancer metastasis were achieved in vivo. [ABSTRACT FROM AUTHOR]

Probing biomolecular interactions at cellular interfaces is crucial for understanding and interfering with life processes. Although affinity binders with site specificity for membrane proteins are unparalleled molecular tools, a high demand remains for novel multi‐functional ligands. In this study, a synthetic peptide (APQQ) with tight and specific binding to the untargeted extracellular loop of CD81 evolved from a genetically encoded peptide pool. With tailored affinity, APQQ flexibly accesses, site‐specifically binds, and forms a complex with CD81, enabling in‐situ tracking of the dynamics and activity of this protein in living cells, which has rarely been explored because of the lack of ligands. Furthermore, APQQ triggers the relocalization of CD81 from diffuse to densely clustered at cell junctions and modulates the interplay of membrane proteins at cellular interfaces. Motivated by these, efficient suppression of cancer cell migration, and inhibition of breast cancer metastasis were achieved in vivo. [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]

Digital finance is reshaping trade credit. This study investigates the influence of digital finance on trade credit among A-share listed companies in China from 2011 to 2020. The paper matches this data with city-level digital finance index (DFI) data. Empirical results indicate that digital finance significantly benefits trade credit. This impact occurs through bank competition, regulatory penalties, and disclosure quality channels. Different levels of digital finance development and financing constraints of companies have a varying impact on trade credit. This paper provides a new perspective on trade credit in the firm's supply chain that enriches theoretical research on digital finance. The research results can help the country to implement digital finance development strategy better and offer relevant guidance and reference. [ABSTRACT FROM AUTHOR]

The dual five-axis machining machine is state-of-the-art equipment designed for producing thin-walled aerospace parts like skins and panels. It comprises two five-axis machine tools with mirrored synchronous motions: one bi-rotary machine for milling and the other machine for follow-up support. The high absolute accuracy of the five-axis machine tools themselves and the high synchronous motion accuracy between the two machines are both crucial to ensure machining accuracy. This paper proposes an efficient method to measure and identify geometric and dynamic errors of dual five-axis machine tools. Using the R-test combined with three measurement trajectories to measure the absolute motion error of two five-axis machine tools and the synchronous motion error between the two machines. The designed trajectories include the main rotary axis linkage conditions and can fully reflect the primary motion forms of the dual five-axis machine tool. The main position-independent geometric errors and rotational axis linkage dynamic errors are identified by converting quasi-static and dynamic measurement data from three different trajectories into a unified reference coordinate system. The entire process requires only one instrument installation, effectively avoiding time-consuming repetitive installations and calibration processes while reducing the impact of installation errors on results. The effectiveness of the proposed method for measuring and identifying the geometric and dynamic errors is analyzed combined with Monte Carlo simulation. Experiments were carried out on a dual five-axis mirror milling system (MMS) with a 5000 mm X-stroke. Both simulations and experiments confirmed that the proposed method is efficient in quickly identifying key error sources of the MMS. [Display omitted] • An efficient method to measure and identify geometric and dynamic errors during synchronous motion of the MMS is proposed. • A geometric and dynamic error model is introduced for identifying key errors using error sensitivity theory. • A 3-step measurement strategy that enables rapid separation of linkage errors of the MMS is introduced. • Both simulation and experiment show the proposed method could obtain key error sources of the MMS with high efficiency. [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]

Position-sensitive detectors are widely used in industry due to accurate sensing of changes in light position. The introduction of additional wavelength selectors can cause deviations in light position and affect the performance of the devices. In this work, an organic–inorganic heterojunction of polyaniline-poly (p-styrenesulfonic acid) (PANI:PSS)/p-Si is proposed to achieve selective detection at optical wavelengths using the lateral photovoltaic effect. The maximum reduction of sensitivity in the detection of 405 nm laser can reach up to 127.59 mV/mm, with a decrease in about 99%. When the device is exposed to blue-violet light, the absorption layer changes from a Si layer to a PANI:PSS layer, which weakens the photon utilization efficiency and charges carrier transport. The self-generated longitudinal voltage further enhances the absorption of the PANI:PSS layer for blue-violet light. PANI absorbs photon energy to generate electron–hole pairs and transitions from the reduced state to the oxidized state in the depletion region at the contact interface. The oxide layer hinders carrier separation and increases carrier recombination. Due to the inherent properties of the structure, the wavelength selection function is realized by the detector itself, enriching its original single function. The sensitivity in other light bands has been improved, including more than three times at 520 nm compared to p-Si. These results have provided the theoretical foundation for highly selective and tunable optoelectronic devices while helping to overcome the challenges of high manufacturing costs and customized application scenarios. They provide a viable solution for the intelligent development of optoelectronic devices. [ABSTRACT FROM AUTHOR]

A photoelectrochemical (PEC) immunosensor was designed based on MgIn2S4-decorated inorganic halide perovskite CsPbBr3 combined with the signal polarity conversion strategy for neuron-specific enolase (NSE) detection. CsPbBr3 was applied as the basic photoactive material owing to its excellent optical and electronic properties, which provide a good PEC performance for sensor construction. In order to improve the stability of this perovskite, the three-dimensional flower-like MgIn2S4 with a desirable direct band gap was applied to enhance the PEC response. Also, the excellent structure of MgIn2S4 provides large surface-active sites for CsPbBr3 loaded. For enhancing the detection sensitivity of PEC immunosensor, p-type CuInS2 was used as a signal probe which fixed on detection antibody (Ab2). When the target NSE was present, the photogenerated electrons produced by CuInS2 were transferred to the test solution, and the polarity of PEC signal changes. Based on the above photosensitive materials and signal conversion strategy, the proposed PEC immunosensor showed favorable detection performance, and the linear detection range is 0.0001 ~ 100 ng/mL with a 38 fg/mL of detection limit. The proposed strategy improved the adhibition of CsPbBr3 in the analytical chemistry field as well as provided a reference method for other protein detections. [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]

Salient object detection (SOD) must capture the multi-level features from both global and local view. Furthermore, interiors and boundaries of salient objects must be processed simultaneously in order to generate a clear salient map with sharp boundaries. In addition, the object-part relationship should be taken into consideration to segment the salient object as a whole. To address above issues, we propose a novel multi-source feature extraction network (MFEN), which is capable of integrating salient features, boundary features and global feature, simultaneously. First of all, the multi-source global and local module (MGLM) is introduced to integrate multi-source features, composing of a series of hybrid dilation convolution modules with different dilated rate. Furthermore, the boundary detection module is introduced to predict the boundary map and boundary features, helping for locating the salient object and sharpen edge. In addition, the adjacent features from MGLM are fused progressively to generate the final salient map by feature fusion modules. Experimental results on five datasets demonstrate that our proposed MFEN outperforms recent 18 SOD methods. More importantly, the ablation study shows that the MGLM is an effective feature fusion module for multi-level and multi-source feature. [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]

Deep learning advancements have resulted in breakthroughs in facial forgery techniques. Facial forgery videos are growing increasingly lifelike, making it impossible for people to tell the difference between the real and the fake. The proliferation of facial forgery techniques, as well as the slowness with which they may be detected, could jeopardize personal data security. As a result, it's critical to look at approaches that can be trained on both real and fake videos and then utilized to identify facial forgeries or not in videos. This study found that forged face videos undergo truncation between consecutive frames of optical flow imaging after dense optical flow processing. We present an approach for detecting video face forgery that extracts and analyzes characteristics from real and fake material, then use those features to train classification models on Celeb-DF and FaceForensics++. In addition, we employ a unique facial double-triangle region to assist in the extraction of video inter-frame feature data. Experiments results show that the facial motion features extracted from the double triangle region successfully assist in capturing the dense optical flow truncation. Extensive evaluation suggests that our proposed approach is effective for video face forgery detection. [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]

The risk of coal mine gas explosion seriously threatens the continuous safe production of coal mines, which in turn affects the national energy security, so it is important to prevent and control the coal mine gas risk. Current risk assessment methods are difficult to fully express the uncertainty in the assessment process, and calculating index weights is easy to deviate from reality. This study introduces Decision-making Trial and Evaluation Laboratory (DEMATEL) as well as the cloud model, and proposes a new coal mine gas explosion risk assessment model based on cloud integrated similarity and fuzzy DEMATEL. The model fully expresses the uncertainty in the whole risk assessment process and makes the index weights assignment more reasonable. It also combines the calculation of cloud integrated similarity to more accurately determine the risk level based on the advantage that the cloud model can visually display the risk status of the assessment object. An example study was conducted on a mine of a large state-owned coal mine enterprise in Shaanxi Province, China. The results show that the method helps coal mine enterprises to accurately assess gas explosion risks, identify weak links in risk prevention and control, and provide a powerful means for continuous improvement of risk management level. [ABSTRACT FROM AUTHOR]

This article deals with the false data injection attack (FDIA) detection problem for multi‐area power systems. Considering the large‐scale characteristic of the multi‐area power systems, a novel decentralized detection scheme is proposed to detect FDIAs. First, an unknown input sliding mode observer (UI‐SMO) is designed to decouple the interconnected terms, meanwhile, a robust term in the UI‐SMO can attenuate the effect of the load variation, by which the obtained residual is only sensitive to local FDIAs. The strict reachability of the sliding surface in the estimate error space is ensured by the robust term with an auxiliary variable, and the stability of the sliding mode dynamics is achieved. Then, a detection logic is delicately designed based on a two‐phase residual threshold. Due to the strong attenuating ability to load variation, the proposed detection scheme shows better detectability than some existing works with only decoupling interconnections. Finally, the theoretical results are backed up by a three‐area power system simulation with comparison between proposed UI‐SMO‐based and traditional UIO‐based detection scheme. [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 rapid development of science and technology, the current ordinary industrial manipulator cannot complete the task well, because it is difficult to control. This research mainly discusses the planning and control of the mobile manipulator for the operation of restricted motion objects in an intelligent environment. In this study, the rapid search random tree (RRT) method is used to study the obstacle avoidance motion planning of the manipulator. The 6-axis robotic arm system uses CAN (controller area network) bus to connect each joint in series and then connect to the multi-axis controller Maestro, and the host computer and Maestro send and receive control commands based on the TCP/IP protocol. A 1-DOF grip is installed at the end of the robotic arm, and the grip is connected to the end of the robotic arm (i.e., at the wrist joint of the robotic arm) through a 6-dimensional force 1 torque sensor. The operating system of the host computer is Ubuntu 14.04. The position of the object is recognized through Kinect, and the position of the object is sent to the robotic arm control software. The PTP (precision time protocol) of the robotic arm moves to a certain distance in front of the object, and then the movement of the robotic arm is controlled by visual servoing to complete the object capture. Each joint of the manipulator uses a speed control mode. In a single control cycle, the joint angular velocity of the manipulator remains unchanged. The controller used by the robotic arm is a 51-core STC12C5410AD single-chip microcomputer, which ensures the response speed of the joint motor linkage. In the environment of multiple obstacles, the RRT algorithm has 10 simulation experiments, the average sampling time is 95.651 s, and the average sampling point is 1308. The results show that the RRT algorithm proposed in this study enables the manipulator to move from the starting point to the endpoint in the environment of multiple obstacles, while avoiding the obstacles, and the mobile manipulator can better operate the motion-limited objects. [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]

With the in-depth development of high-tech industries, especially in the fields of production, manufacturing, aviation, and medical care, most of the work needs to be accomplished with the help of machines. As a high-tech product, a robotic arm plays an irreplaceable role in high-risk and high-precision engineering, such as arc welding, spraying, and assembly. At the same time, with the increasing requirements of scientific and technological production processes, robotic arm tasks are becoming increasingly complicated. Robotic arm trajectory tracking control in industry also has increasingly higher standards. Furthermore, external interference sources invariably affect the robotic arm control system when it is in operation. Therefore, existing manipulator control systems can no longer meet the requirements of industrial production. This paper aims to realize the tracking control of the trajectory of a robotic arm through a neural network algorithm. This research offers an adaptive neural network control method to solve the manipulator trajectory tracking control problem. To increase the control effect and overall performance of the manipulator, a neural network is employed to address the uncertainty in the control system as well as the interference of external elements. Experiments reveal that a neural network-based manipulator trajectory control and tracking system can effectively regulate the manipulator's operation and improve its overall performance. [ABSTRACT FROM AUTHOR]

Key message: A novel splice-site mutation in the P. vulgarisgene for TETRAKETIDE α-PYRONE REDUCTASE 2 impairs male fertility, and parthenocarpic pod development can be improved by external application of IAA. Snap bean (Phaseolus vulgaris L.) is an important vegetable crop in many parts of the world, and the main edible part is the fresh pod. Here, we report the characterization of the genic male sterility (ms-2) mutant in common bean. Loss of function of MS-2 accelerates degradation of the tapetum, resulting in a complete male sterility. Through fine-mapping, co-segregation, and re-sequencing analysis, we identified Phvul.003G032100, which encodes the TETRAKETIDE α-PYRONE REDUCTASE 2 (PvTKPR2) protein in common bean, as the causal gene for MS-2. PvTKPR2 is predominantly expressed at the early stages of flower development. A novel 7-bp (+ 6028 bp to + 6034 bp) deletion mutation spans the splice site between the fourth intron and fifth exon, leading to a 9-bp deletion in transcribed mRNA and a 3-amino acid (G210M211V212) deletion in the protein coding sequence of the PvTKPR2ms−2 gene. The 3-D structural changes in the protein due to the mutation may impair the activities of NAD-dependent epimerase/dehydratase and the NAD(P)-binding domains of PvTKPR2ms−2 protein. The ms-2 mutant plants produce many small parthenocarpic pods, and the size of the pods can be doubled by external application of 2 mM indole-3-acetic acid (IAA). Our results demonstrate that a novel mutation in PvTKPR2 impairs male fertility through premature degradation of the tapetum. [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]

Objectives: To investigate the function and regulatory mechanisms of delphinidin in the treatment of hepatocellular carcinoma. Methods: HepG2 and HuH-7 cells were treated with different concentrations of delphinidin. Cell viability was analysed by 3-(4,5-dimethyl-thiazol-2-yl)-2,5-diphenyltetrazolium bromide assay. The cell autophagy and autophagic flux were analysed by LC3b-green fluorescent protein (GFP)-Adv and LC3b-GFP-monomeric red fluorescent protein-Adv transfected HepG2 and HuH-7 cells, respectively. Cell apoptosis was analysed by Hoechst33342 staining, terminal deoxynucleotidyl transferase dUTP nick end labeling staining and DNA laddering. Cell autophagy, apoptosis and survival related protein expressions were detected by Western blotting. Key findings: After treatment with different concentrations of delphinidin, the cell survival rate was significantly decreased. Delphinidin could block the autophagic flux, resulting in a significant increase in autophagosomes, and led to an increase in cell apoptosis. The combined application of delphinidin and cisplatin could promote the antitumour effect and reduce the dose of cisplatin in tumour cells. Further mechanism studies reveal that delphinidin could inhibit the multidrug resistance gene 1 (MDR1) and the tumour-promoting transcription cofactor DEAD-box helicase 17 (DDX17) expression in tumour cells. Overexpression of DDX17 could reverse delphinidin's antitumor function in tumour cells. Conclusions: Delphinidin has a strong anti-tumour effect by inducing tumour cell autophagic flux blockage and apoptosis by inhibiting of both MDR1 and DDX17 expression. [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]

BaTiO3 sintered in different atmospheres to tune the oxygen-related defect configuration in BaTiO3. X-ray photoelectron spectroscopy (XPS) found that BaTiO3 sintered in different atmospheres has different defect compensation modes: BaTiO3 sintered in 100% Ar atmosphere mainly has V o · · - V Ba ″ ion compensation mode; BaTiO3 sintered in 1% H2&99% Ar atmosphere mainly has V o · · - 2 T i Ti ′ electron compensation mode. The effects of V o · · - V Ba ″ and V o · · - 2 T i Ti ′ defect configurations on the morphology, structure, and properties of BaTiO3 ceramics were studied. Benefiting from the ion-free doping approach, we report the V o · · - 2 T i Ti ′ defect configuration has a colossal permittivity effect (εr > 3.8 × 105,25℃ ~ 150℃, its 47 times than BaTiO3's εr) and low dielectric loss (tanδ < 0.1) at low frequency for the first time. These results provides an effective strategy to the design of super high-capacity multilayer ceramic capacitors (MLCCs). [ABSTRACT FROM AUTHOR]

The unprecedented coronavirus disease 2019 (COVID-19) pandemic has caused a disaster for public health in the last 2 years, without any sign of an ending. Various vaccines were developed rapidly as soon as the outbreak occurred. Clinical trials demonstrated the reactogenicity, immunogenicity and protection efficacy in humans, and some of the vaccines have been approved for clinical use. However, waves of infections such as the recently circulating Omicron variant still occur. Newly emerging variants, especially the variants of concern, and waning humoral responses pose serious challenges to the control of the COVID-19 pandemic. Previously, we summarized the humoral and cellular immunity, safety profiles and protection efficacy of COVID-19 vaccines with clinical data published by 21 May 2021. In this review, we summarize and update the published clinical data of COVID-19 vaccines and candidates up to 31 December 2021. [ABSTRACT FROM AUTHOR]

Rich functionalities have been identified for domain walls (DWs, naturally occurring interfaces in ferroics), e.g., enhanced conductance and photovoltaic effect, which specify the interest in their internal structure. The dimension/width and type are of particular interest, which is the carrier of their functionality. Recent attention has been focused on head‐to‐head or tail‐to‐tail charged DWs with greatly enhanced conductivity compared to the inner domains, which are found to be an order of magnitude thicker (tens of unit cells) than normal neutral DWs. In this study, ultrathin non‐Ising charged DWs are found, where polarization switched their direction within 2–3 unit cells in self‐assembled BiFeO3 nanocrystals. An analytical model and finite element method simulation are used to interpret the origin of this phenomenon, i.e., electrostatic constraints linked to DW configurations in a ferroelectric. This study indicates that as an intrinsic property, the width of the ferroic DWs varies with different electrostatic constraints and must be taken into consideration during its applications. [ABSTRACT FROM AUTHOR]

Summary: Tuned mass damper inerter (TMDI) is a promising device for structural vibration control. Existing design formulas for TMDI are derived based on an undamped single‐degree‐of‐freedom primary structure. When applied to vortex‐induced vibration (VIV) control of bridges, it may lead to a suboptimal design of TMDI, since VIV is characterized by nonlinear aeroelastic effect and sensitive to the structural damping. This study proposes closed‐form design formulas of TMDI that are suitable for VIV control of bridges. Governing equations of the bridge‐TMDI system are first established in modal coordinate. Based on these equations, the equivalent damping of TMDI to the bridge is derived. Then, the design formulas for TMDI frequency and damping ratio with predetermined TMDI mass, inertance, and inerter arrangement are developed to achieve the required equivalent damping of TMDI. The reliability of the proposed formulas is validated by utilizing the wind tunnel experimental data of a bridge. It is found that the effect of TMDI to the bridge can be treated as an increase of the structural damping. It is also found that the TMDI parameters will betray the optimum values if the VIV force model fails to correctly predict the required equivalent damping of TMDI. To eliminate this disadvantage, some design suggestions are presented. The comparison with existing TMDI design formulas and discussions on the application scope of the proposed formulas are also conducted. The proposed formulas can achieve a better control efficiency for the same predetermined TMDI parameters and have high accuracy within the scope of practical engineering applications. [ABSTRACT FROM AUTHOR]

Appropriate burden profile in shaft furnace may benefit to improve the efficiency of gas-solid mass transfer, thereby increasing the solid metallization rate (MR) in shaft furnace and reducing the energy consumption in the COREX process. For example, the "V" shape burden profile is obtained by charging the mixed particles to the point near the furnace wall through a chute, so that the burden spontaneously forms a pile with the tip near the furnace wall and the pile foot at the center of the furnace. Keywords: bed structure; CFD; COREX shaft furnace; metallization rate; pressure drop EN bed structure CFD COREX shaft furnace metallization rate pressure drop 1073 1081 9 11/02/22 20221001 NES 221001 1 Introduction The gas-solid countercurrent moving bed is a common reactor in many industrial processes, such as ironmaking, coal gasification, waste heat recovery, chemical catalysis and other industries. [Extracted from the article]

Background: DNA damage in airway epithelia under exogenous disruptors can trigger various pulmonary diseases. Integrin beta 4 (ITGB4) is a structural adhesion molecule, which is indicated to regulate the process of DNA damage in airway epithelia for its unique long cytoplasmic domain subunit. Methods: The expression level of ITGB4 and the degree of DNA damage were observed in the house dust mite (HDM)‐stressed model and ozone‐challenged model, respectively. Besides, ITGB4 conditional knockout mice and ITGB4‐deficient airway epithelial cells were constructed to observe the influence of ITGB4 deficiency on DNA damage. Furthermore, the influence of ITGB4 deficiency on HDAC1 expression in airway epithelia was determined under stress stimulation. Finally, corresponding intervention strategies were carried out to verify the involvement of the ITGB4‐mediated HDAC1 pathway in DNA damage of airway epithelial cells. Results: HDM stress and ozone challenge reduced the expression of ITGB4, which is accompanied by the increased expression of 8‐oxoG and γ‐H2AX both in vivo and in vitro. Moreover, ITGB4 deficiency in airway epithelia aggravates the degree of DNA damage under HDM stimulation and ozone stress, respectively. Furthermore, ITGB4 deficiency downregulated the expression of HDAC1 during DNA damage, and restoring HDAC1 can reverse the enhanced DNA damage in airway epithelial cells after exogenous stress. Conclusions: This study confirmed the involvement of ITGB4 in the regulation of DNA damage through mediating HDAC1 in airway epithelial cells under exogenous stress. These results supply some useful insights into the mechanism of DNA damage in airway epithelial cells, which would provide possible targets for early prediction and intervention of pulmonary diseases. [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]

The predictions of the multiple-regime flows from continuum regime to free molecular regime are crucial for the aerodynamic design in a large number of engineering applications, such as the near-space craft, the ultra-low orbit spacecraft and the micro- electro-mechanical systems (MEMS). Since the essence of this multiple-regime problem is a complex system composed by different scales and mechanics, the modeling and numerical prediction of these multiple-regime flows are very challenging at both theoretical and practical levels. Moreover, the single flow field with multiple flow regimes will make the problem extremly complicated. Unfortunately, this typical flow field is very common in hypersonic application and important for the development of multiple-regime aerodynamics. On the other hand, both the constructions of the low density wind tunnel with high enthalpy and the high altitude flight experiment are also very challenging at the present stage. Therefore, the researches on the multiple- regime flows and the corresponding complex science hit a worldwide bottleneck. This paper reviews the breakthroughs in the computational methods for multiple-regime flows in the last ten years, which can be used as numerical experimental tools for studying the multiple-scale flow mechanism and providing data for aerodynamic designs and thermal protections. This paper focuses on the progress of the unified wave-particle methods established in recent years, which are proved to be both accurate and efficient for multiple-regime flows with extremly high speed. [ABSTRACT FROM AUTHOR]

• Presents a novel framework combining residual network (ResNet) with bidirectional long short-term memory network (BiLSTM) for enhanced terahertz signal analysis. • Introduces a sophisticated method for automatic defect detection and interface localization in non-metallic materials, surpassing traditional manual analysis in efficiency and accuracy. • Achieves interface positioning accuracy surpassing 80 µm in coating sample thickness, demonstrating superior performance to conventional approaches. • Provides robust validation against X-ray CT results, revealing an error margin of only 1.07% to 5.39% in detecting adhesive layer defects. This manuscript presents a framework that integrates a residual network (ResNet) with a bidirectional long short-term memory network (BiLSTM) for effective feature extraction and interface positioning in terahertz signal analysis. This innovative approach employs spatial and temporal feature extraction modules to process terahertz signals, enabling the automatic detection of interfaces and defects in both coating and bonded structure samples. The experimental results indicate that the interface positioning accuracy of the method aligns with the manual analysis outcomes for coating samples exceeding 80 µm in thickness. Furthermore, it exhibits a high degree of consistency with X-ray CT detection results when detecting defects in the adhesive layer, with an error margin ranging from 1.07 % to 5.39 %. Significantly, we have also conducted preliminary analyses on actual samples, further underscoring the robustness and generalizability of our model. This method offers an efficient automated tool for terahertz signal analysis and holds promise for industrial detection applications. Future research will aim to broaden the range of samples and application scenarios, thereby increasing the technology's practicality in quality control and production line detection. [ABSTRACT FROM AUTHOR]

[Display omitted] • This is the initial time that UV irradiation has been obtained to activate PI on CoFe 2 O 4 materials. • Approximately 100 % OTC degradation was attained within 12 min in the UV/CoFe 2 O 4 /PI system. • The contaminants were oxidized by radical and non-radical mechanisms utilizing UV/CoFe 2 O 4 /PI. • This UV/CoFe 2 O 4 /PI system is resistant to inorganic ions, realistic water conditions and pH variations. There is currently plenty of emphasis on measures to handle the water pollution spurred on by the misuse of antibiotics. Given its exceptional degradation accomplishment, periodate (PI), a steady solid oxidant, has promising future applications in the breakdown of antibiotics. In this research, PI was activated with UV/CoFe 2 O 4 (CFO) for the first time in an attempt to eliminate oxytetracycline (OTC). The UV/CFO/PI system eliminated 30 mg∙L-1 OTC with a removal effectiveness of almost 100 % in 12 min (OTC 30 mg∙L-1, CFO 0.2 g∙L-1, PI 2 mM, pH 5.5). In addition, the ferromagnetism of the CFO assisted to the system's remarkable cycling achievement, with 85.9 % of the OTC still removed after ten cycles. Various organic contaminants, which include reactive blue KN-R (KN-R), ciprofloxacin (CIP), chlortetracycline (CTC), and levofloxacin (LVX), further demonstrated the UV/CFO/PI system to be useful for degrading. The primary active substances for OTC elimination were revealed and recognized through scavenging experiments and EPR analysis as h+, •IO 4 , •IO 3 , 1O 2 , •OH, and •O 2 –. Simultaneously, redox cycles of Fe(III)/Fe(II) and Co(III)/Co(II) were also observed by XPS test to hasten OTC deterioration. It appeared that this system may be a green approach for antibiotic elimination by investigating the degradation route of OTC and the influence it has on the surroundings employing FuKui functions, LC-MS, and toxicological analysis software (T.E.S.T.), respectively. Additionally, we observed that the CFO (2 2 2) crystal surface has the best adsorption impact on PI by computing Eads from DFT. [ABSTRACT FROM AUTHOR]