Facile construction of copper-doped metal organic framework as a novel visible light-responsive photocatalyst for contaminant degradation.

ABSTRACTMetal-organic frameworks (MOFs) with photocatalytic activity have garnered significant attentions in environmental remediation. Herein, copper-doped zeolitic imidazolate framework-7 (Cu-doped ZIF-7) was synthesized rapidly and easily using a microwave-assisted technique. Various analytical and spectroscopic methods were employed to access the framework, morphology, light absorption, photo-electrochemical and photocatalytic performance of the synthesized materials. Compared to ZIF-7, Cu/ZIF-7 (molar ratio of Cu2+ to Zn2+ is 1:1) demonstrates superior visible light absorption ability, narrower band gap, enhanced charge separation capability, and reduced electron-hole recombination performance. Under visible light irradiation, Cu/ZIF-7 serves as a Fenton-like catalyst and demonstrates exceptional activity for contaminant degradation, while virgin ZIF-7 remains inactive. With the addition of 9.8 mmol H2O2 and exposure to visible light for 30 min, 10 mg of Cu/ZIF-7 can completely decompose RhB solution (10 mg/L, 50 mL). The synergistic effect of the Cu/ZIF-7/H2O2/visible light system is attributed to visible light photocatalysis and Fenton-like reactions. Cu/ZIF-7 demonstrates excellent catalytic performance stability, with only a slight decrease in degradation efficiency from an initial 97.0% to 95.4% over four cycles. Additionally, spin-trapping ESR measurements and active species trapping experiments revealed that h+ and ·OH occupied a significant position for Rhodamine B (RhB) degradation. Degradation intermediate products of Rhodamine B have been identified using UPLC-MS, and the degradation pathways have been proposed and discussed. This work offers a facile and efficient technique for developing MOF-based visible light photocatalysts for water purification.

Seeing Soft Materials Draped Over Objects: A Case Study of Intuitive Physics in Perception, Attention, and Memory.

We typically think of intuitive physics in terms of high-level cognition, but might aspects of physics also be extracted during lower-level visual processing? Might we not only think about physics, but also see it? We explored this using multiple tasks in online adult samples with objects covered by soft materials-as when you see a chair with a blanket draped over it-where you must account for the physical interactions between cloth, gravity, and object. In multiple change-detection experiments (n = 200), observers from an online testing marketplace were better at detecting image changes involving underlying object structure versus those involving only the superficial folds of cloths-even when the latter were more extreme along several dimensions. And in probe-comparison experiments (n = 100), performance was worse when both probes (vs. only one) appeared on image regions reflective of underlying object structure (equating visual properties). This work collectively shows how vision uses intuitive physics to recover the deeper underlying structure of scenes.

Effect of geometric sharpness on translucent material perception.

When judging the optical properties of a translucent object, humans often look at sharp geometric features such as edges and thin parts. An analysis of the physics of light transport shows that these sharp geometries are necessary for scientific imaging systems to be able to accurately measure the underlying material optical properties. In this article, we examine whether human perception of translucency is likewise affected by the presence of sharp geometry, by confounding our perceptual inferences about an object's optical properties. We use physically accurate simulations to create visual stimuli of translucent materials with varying shapes and optical properties under different illuminations. We then use these stimuli in psychophysical experiments, where human observers are asked to match an image of a target object by adjusting the material parameters of a match object with different geometric sharpness, lighting, and three-dimensional geometry. We find that the level of geometric sharpness significantly affects perceived translucency by observers. These findings generalize across a few illumination conditions and object shapes. Our results suggest that the perceived translucency of an object depends on both the underlying material's optical parameters and the three-dimensional shape of the object. We also find that models based on image contrast cannot fully predict the perceptual results.

Manipulating patterns of dynamic deformation elicits the impression of cloth with varying stiffness.

Cloth is a common material, and humans can visually estimate its mechanical properties by observing how it deforms under external forces. Here, we ask whether and how dynamic deformation can affect the perception of mechanical properties of cloth. In Experiment 1, we find that both intrinsic mechanical properties and optical properties affect stiffness perception when the stimuli are presented as images. By contrast, in videos, humans can partially discount the effect of optical appearances and exhibit higher sensitivity to stiffness. We further identified an idiosyncratic deformation pattern (i.e., movement uniformity) to differentiate stiffness, which can be reliably measured by six optical flow features. In Experiment 2, we isolate the deformation by creating dynamic dot stimuli from the 3-D mesh of the cloth. We directly alter the movement pattern by manipulating the uniformity of the displacement vectors on the dot stimuli and show that changing the pattern of dynamic deformation alone can alter the perceived stiffness of cloth in a variety of scene setups. Furthermore, by analyzing optical flow fields extracted from the manipulated dynamic dot stimuli, we confirmed the same six optical flow features can be diagnostic of the degree of stiffness of moving cloth across different scenes. Overall, our study demonstrates that manipulating patterns of dynamic deformation alone can elicit the impression of cloth with varying stiffness, suggesting that the human visual system might rely on the idiosyncratic pattern of dynamic deformation for estimating stiffness.

Estimating mechanical properties of cloth from videos using dense motion trajectories: Human psychophysics and machine learning.

Humans can visually estimate the mechanical properties of deformable objects (e.g., cloth stiffness). While much of the recent work on material perception has focused on static image cues (e.g., textures and shape), little is known about whether humans can integrate information over time to make a judgment. Here we investigated the effect of spatiotemporal information across multiple frames (multiframe motion) on estimating the bending stiffness of cloth. Using high-fidelity cloth animations, we first examined how the perceived bending stiffness changed as a function of the physical bending stiffness defined in the simulation model. Using maximum-likelihood difference-scaling methods, we found that the perceived stiffness and physical bending stiffness were highly correlated. A second experiment in which we scrambled the frame sequences diminished this correlation. This suggests that multiframe motion plays an important role. To provide further evidence for this finding, we extracted dense motion trajectories from the videos across 15 consecutive frames and used the trajectory descriptors to train a machine-learning model with the measured perceptual scales. The model can predict human perceptual scales in new videos with varied winds, optical properties of cloth, and scene setups. When the correct multiframe was removed (using either scrambled videos or two-frame optical flow to train the model), the predictions significantly worsened. Our findings demonstrate that multiframe motion information is important for both humans and machines to estimate the mechanical properties. In addition, we show that dense motion trajectories are effective features to build a successful automatic cloth-estimation system.

Can you see what you feel? Color and folding properties affect visual-tactile material discrimination of fabrics.

Humans can often estimate tactile properties of objects from vision alone. For example, during online shopping, we can often infer material properties of clothing from images and judge how the material would feel against our skin. What visual information is important for tactile perception? Previous studies in material perception have focused on measuring surface appearance, such as gloss and roughness, and using verbal reports of material attributes and categories. However, in real life, predicting tactile properties of an object might not require accurate verbal descriptions of its surface attributes or categories. In this paper, we use tactile perception as ground truth to measure visual material perception. Using fabrics as our stimuli, we measure how observers match what they see (photographs of fabric samples) with what they feel (physical fabric samples). The data shows that color has a significant main effect in that removing color significantly reduces accuracy, especially when the images contain 3-D folds. We also find that images of draped fabrics, which revealed 3-D shape information, achieved better matching accuracy than images with flattened fabrics. The data shows a strong interaction between color and folding conditions on matching accuracy, suggesting that, in 3-D folding conditions, the visual system takes advantage of chromatic gradients to infer tactile properties but not in flattened conditions. Together, using a visual-tactile matching task, we show that humans use folding and color information in matching the visual and tactile properties of fabrics.

Inhibitory effects of sulfated 20(S)-ginsenoside Rh2 on the release of pro-inflammatory mediators in LPS-induced RAW 264.7 cells.

Ginsenoside Rh2 is one of the most important ginsenosides in ginseng with anti-inflammatory and antitumor effects. However, the extremely poor oral bioavailability induced by its low water solubility greatly limits the potency of Rh2 in vivo. In the previous study, we sulfated 20(S)-ginsenoside Rh2 with chlorosulfonic acid and pyridine method, and got one novel derivative, Rh2-B1, with higher water solubility and greater immunologic enhancement than Rh2. However, the anti-inflammatory effect of Rh2-B1 remains unclear. We therefore investigated the effects of Rh2-B1 on lipopolysaccharide (LPS)-induced proinflammatory mediators in RAW 264.7 macrophages. We found that Rh2-B1 dramatically inhibited LPS-induced overproduction of nitric oxide, prostaglandin E2, tumor necrosis factor (TNF)-α, interleukin (IL)-1ß, and IL-6. Consistently, the protein and mRNA expression levels of inducible nitric oxide synthase and cyclooxygenase-2 were remarkably decreased by Rh2-B1. In addition, Rh2-B1 significantly suppressed the phosphorylations of p38, c-Jun N-terminal kinase, and extracellular signal receptor-activated kinase 1/2 induced by LPS. Rh2-B1 was further shown to inhibit NF-κB p65 translocation into the nucleus by suppressing IκBα degradation. In conclusion, we demonstrate that Rh2-B1 inhibits the release of LPS-induced pro-inflammatory mediators through blocking mitogen-activated protein kinases and NF-κB signaling pathways, suggesting that sulfated ginsenosides could be potential agents for anti-inflammatory therapies.

Sulfated derivatives of 20(S)-ginsenoside Rh2 and their inhibitory effects on LPS-induced inflammatory cytokines and mediators.

Ginsenoside Rh2 is one of the most important ginsenosides in ginseng with antitumor, antidiabetic, antiallergic, and anti-inflammatory effects. However, the extremely poor oral bioavailability induced by its low water solubility greatly limits the potency of Rh2 in clinical use. Therefore, in this study we sulfated 20(S)-ginsenoside Rh2 with chlorosulfonic acid and pyridine method, and got two new sulfated derivatives, Rh2-B1 and Rh2-B2, with higher water solubility. Their chemical structures were characterized by spectroscopic methods (IR, MS and NMR). Additionally, Rh2-B1 and Rh2-B2 had the greater anti-inflammatory effects than Rh2 through inhibiting inflammatory cytokines and mediators in LPS-induced mouse RAW264.7 macrophages cells. These results suggested that the sulfated modification of Rh2 improved its water solubility and the sulfated derivatives could be more potential candidates for developing as anti-inflammatory agents.

Sulfated derivative of 20(S)-ginsenoside Rh2 inhibits inflammatory cytokines through MAPKs and NF-kappa B pathways in LPS-induced RAW264.7 macrophages.

In the previous study, we found that sulfated derivative B2 of ginsenoside Rh2 (Rh2-B2) has greater anti-inflammatory effects than 20(S)-ginsenoside Rh2. However, the anti-inflammatory mechanism of Rh2-B2 remains unclear. We therefore assessed the effects of Rh2-B2 on inflammatory cytokines in lipopolysaccharide (LPS)-stimulated RAW264.7 macrophages. We found that Rh2-B2 (1-5 mg/L) significantly inhibited tumor necrosis factor alpha, interleukin (IL)-6, IL-1ß, and increased IL-10 production from protein and mRNA levels. Furthermore, Rh2-B2 significantly inhibited the phosphorylation of p38 and c-Jun N-terminal kinase as well as decreased p65 nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) translocation into the nucleus by nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, alpha degradation. The present results indicate that Rh2-B2 inhibits the production of inflammatory cytokines induced by LPS through blocking mitogen-activated protein kinases and NF-κB signaling pathways.