Efficient splitting of alkane isomers by a bismuth-based metal-organic framework with auxetic reentrant pore structures

10.1002/anie.202211808Angew. Chem. Int. Ed.6147e20221180

Study on the grain refinement mechanism of the machined surface of Inconel 718

In machining processes, the high temperature and stress can lead to plastic deformations of the workpiece material. Thermomechanical loading has a significant impact on the microstructure of the machined surface, including grain deformation, recrystallization, and refinement. Among these factors, grain refinement plays a crucial role in determining the mechanical properties of the materials. To investigate the mechanism of grain refinement on the machined surface of Inconel 718 at different cutting speeds, the experiments and finite element simulations were conducted. The microstructural characteristics were quantitative analyzed, including grain size, grain boundary distribution characteristics, average orientation (KAM), and geometrically necessary dislocation (GND) density distribution. The mapping relationship between the multi-physical fields (equivalent plastic strain, temperature) during cutting and the microstructural evolution of Inconel 718 was established. The research indicated that the increasing the cutting speed leads to a higher degree of grain refinement. At a cutting speed of 450 m/min, the maximum grain refinement is achieved with an approximately grain size of 2.48 μm. The contribution from plastic deformation (dynamic recuperation) gradually increases while high temperature remains dominant as factors influencing grain refinement. Conversely, the equivalent plastic strain becomes the primary factor contributing to grain refinement, with a gradual increase in the proportion due to dynamic recrystallization at cutting speeds of 250 m/min and 350 m/min

Porous nanocomposites with enhanced intrinsic piezoresistive sensitivity for bioinspired multimodal tactile sensors

Abstract In this work, we propose porous fluororubber/thermoplastic urethane nanocomposites (PFTNs) and explore their intrinsic piezoresistive sensitivity to pressure. Our experiments reveal that the intrinsic sensitivity of the PFTN-based sensor to pressure up to 10 kPa increases up to 900% compared to the porous thermoplastic urethane nanocomposite (PTN) counterpart and up to 275% compared to the porous fluororubber nanocomposite (PFN) counterpart. For pressures exceeding 10 kPa, the resistance-pressure relationship of PFTN follows a logarithmic function, and the sensitivity is 221% and 125% higher than that of PTN and PFN, respectively. With the excellent intrinsic sensitivity of the thick PFTN film, a single sensing unit with integrated electrode design can imitate human skin for touch detection, pressure perception and traction sensation. The sensing range of our multimodal tactile sensor reaches ~150 Pa, and it exhibits a linear fit over 97% for both normal pressure and shear force. We also demonstrate that an electronic skin, made of an array of sensing units, is capable of accurately recognizing complex tactile interactions including pinch, spread, and tweak motions

Revisiting pixel-wise supervision for face anti-spoofing

Abstract Face anti-spoofing (FAS) plays a vital role in securing face recognition systems from the presentation attacks (PAs). As more and more realistic PAs with novel types spring up, it is necessary to develop robust algorithms for detecting unknown attacks even in unseen scenarios. However, deep models supervised by traditional binary loss (e.g., `0' for bonafide vs. `1' for PAs) are weak in describing intrinsic and discriminative spoofing patterns. Recently, pixel-wise supervision has been proposed for the FAS task, intending to provide more fine-grained pixel/patch-level cues. In this paper, we firstly give a comprehensive review and analysis about the existing pixel-wise supervision methods for FAS. Then we propose a novel pyramid supervision, which guides deep models to learn both local details and global semantics from multi-scale spatial context. Extensive experiments are performed on five FAS benchmark datasets to show that, without bells and whistles, the proposed pyramid supervision could not only improve the performance beyond existing pixel-wise supervision frameworks, but also enhance the model's interpretability (i.e., locating the patch-level positions of PAs more reasonably). Furthermore, elaborate studies are conducted for exploring the efficacy of different architecture configurations with two kinds of pixel-wise supervisions (binary mask and depth map supervisions), which provides inspirable insights for future architecture/supervision design

Downregulation of miR-221 Inhibits Cell Migration and Invasion through Targeting Methyl-CpG Binding Domain Protein 2 in Human Oral Squamous Cell Carcinoma Cells

Oral squamous cell carcinoma (OSCC), the most frequent of all oral cancers, is a type of highly malignant tumors with a high capacity to invade locally and form distant metastases. An increasing number of studies have shown that microRNAs (miRNAs) play an important role in regulating cancer metastasis and invasion. In the present study, we detected the expression of miR-221 in two highly metastatic OSCC cell lines and two OSCC cell lines that are less metastatic using quantitative real-time PCR analysis (qRT-PCR). The qRT-PCR results indicate that miR-221 is upregulated in highly metastatic OSCC cell lines. Then, miR-221 expression was knocked down by transfection with miR-221 inhibitor, and UM1 cell migration and invasion were assessed using transwell migration and invasion assays. The results indicate that inhibition of miR-221 suppressed migration and invasion of UM1 cells. Furthermore, methyl-CpG binding domain protein 2 (MBD2) was identified as a direct target gene of miR-221. Additionally, MBD2 silencing could partly reverse the effect of miR-221 on cell migration and invasion. In conclusion, downregulation of miR-221 inhibits cell migration and invasion at least partially through targeting MBD2 in the human OSCC cell line UM1

Functional engineered exosomes mitigate pathological ischemic retinopathy through a dual strategy of inflammatory microenvironment modulation and angiogenic factor control

Retinal neovascularization (RNV), a major cause of blindness, is usually treated with anti-VEGF drugs. Despite successes, incomplete patient responses push for alternative strategies. In this study, a combined approach was devised by conjugating exosomes (Exo) derived from adipose mesenchymal stromal cells (ADMSCs) with specially designed peptides called KAI, using a cleavable linker controlled by matrix metalloproteinases (MMPs). This allowed for an environmentally responsive release of the peptide from Exo. Intravitreal injection of Exo resulted in the inhibition of pathological angiogenesis, accompanied by downregulation of immune response genes. Mechanistically, Exo were specifically phagocytized by microglia, resetting their activation status through the inhibition of the innate STING/NF-κB signaling pathway. Moreover, upon MMP stimulation in the retina, KAI was cleaved, effectively quenching multiple angiogenic factors simultaneously. This dual anti-inflammatory and anti-angiogenic strategy demonstrated significant therapeutic effects, including suppressed neovascularization, and reduced vascular leakage in the retina. ExoKAI treatment demonstrated no noticeable side effects, positioning these engineered nanodrugs as a promising alternative for ischemic retinopathy and refractory ocular neovascularization due to their combined effects

Effect of Ion-Exchange Sequences on Catalytic Performance of Cerium-Modified Cu-SSZ-13 Catalysts for NH3-SCR

Cerium-modified Cu-SSZ-13 catalysts were prepared by an aqueous ion-exchange method, and Ce and Cu were incorporated through different ion-exchange sequences. The results of NH3-SCR activity evaluations displayed that Cu1(CeCu)2 catalyst presented excellent catalytic activity, and over 90% NOx conversion was obtained across the temperature range of 200–500 °C. The characterization results showed that the ion-exchange sequence of Cu and Ce species influenced the crystallinity of the zeolites and the coordination of Al. A small amount of Ce could participate in the reduction process and change the location and coordination environment of copper ions. Furthermore, Ce-modified Cu-SSZ-13 catalysts possessed more acidic sites due to their containing replacement of Ce and movement of Cu in the preparation process. The cooperation of strong redox abilities and NH3 storage capacity led to the increase of active adsorbed species adsorption and resulted in better activity of Cu1(CeCu)2

Ce and Zr Modified WO3-TiO2 Catalysts for Selective Catalytic Reduction of NOx by NH3

A series of Ce and/or Zr modified WO3-TiO2 catalysts were synthesized by the impregnation method, which were employed for NH3-SCR reaction. The T50 contour lines of NOx were used to quickly optimize catalyst composition, the Ce20Zr12.5WTi catalyst was considered to be the optimization result, and also exhibited excellent NH3-SCR activity and thermal stability with broad operation temperature window, which is a very promising catalyst for NOx abatement from diesel engine exhaust. The excellent catalytic performance is associated with the formation of Ce-Zr solid solution. The introduction of Zr to CeWTi catalyst facilitated the redox of Ce4+/Ce3+ and the formation of more acid sites, more Ce3+ ions, more oxygen vacancies, larger quantities of surface adsorbed oxygen species and NH3, which were beneficial for the excellent selective catalytic reduction (SCR) performance

Spatio-temporal pain estimation network with measuring pseudo heart rate gain

Abstract Pain is a significant indicator that shows people are suffering from an unwell experience and its automatic estimation has attracted much interest in recent years. Of late, most estimation methods are designed to capture the dynamic pain information from visual signals while a few physiological-signal based methods can provide extra potential cues to analyze the pain more accurately. However, it is still challenging to capture the physiological data from patients as it requires contact devices and patients’ cooperation. In this paper, we propose to leverage the pseudo physiological information by generating new modal data from the original visual videos and jointly estimating the pain by an end-to-end network. To extract the representations from bi-modal data, we design a spatio-temporal pain estimation network, which employs a dual-branch framework for extracting pain-aware visual and pseudo physiological features separately and fuses the features in a probabilistic way. The inherent vital sign, i.e., heart rate gain (HRG), from pseudo physiological information can be utilized as an auxiliary signal and integrated with the visual pain estimation framework. Moreover, specially-designed 3D convolution filters and attention structures are employed to extract spatio-temporal features for both branches. To use the HRG as an auxiliary way for pain estimation, we propose a probabilistic inference model by jointly considering the visual branch and physiological branch, which makes our model estimate the pain comprehensively. Experiments on two publicly-available datasets show the effectiveness of introducing the pseudo modality, and the proposed method can outperform the state-of-the-art methods