The discharge of organic pollutants by the textile and dyeing industries presents an escalating threat to aquatic environments, necessitating the development of effective remediation strategies. This study introduces the utilization of graphite-like structured activated carbon (AC), derived from highland barley straw-a biomass unique to the Plateau regions of China, including Tibet, Qinghai, and Gansu-as a support material for the TiO₂ catalyst. TiO₂/AC composites with different TiO₂ loadings were synthesized by ultrasonic impregnation. The TiO₂/AC composites were found to be polycrystalline materials composed of anatase and rutile phases. The TiO₂ nanoparticles are well-dispersed over the surface of the AC. The photocatalytic activity of these composites was evaluated through their capacity to degrade a methylene blue (MB) solution upon irradiation. It was observed that the inclusion of TiO₂ increases the number of adsorption sites and active sites for methylene blue, with the photocatalytic activity being notably higher at a 3-wt% TiO₂ loading, achieving a remarkable 99.6 % degradation efficiency for 100 mg/L MB within 100 min. The experimental kinetic data for the photocatalytic process follow the pseudo-first-order kinetic model. Furthermore, TiO₂/AC retains high photocatalytic activity after five reaction cycles. This research provides valuable insights into the application of biomass-derived materials for the purification of water, offering a sustainable solution to both pollution and agricultural waste challenges in Plateau areas of China.

Extra scalar fields are common in beyond Standard Model (SM) new physics, and they may mix with the 125 GeV SM-like Higgs boson discovered at the LHC. This fact suggests possible discovery channels for these new scalar fields with their decay modes involving the 125 GeV Higgs boson. In this work, we explore the LHC search potential of the heavy $CP$-even Higgs boson $H$ in the two-Higgs-doublet model. We focus on the channel of $H$ decaying to a pair of light $CP$-even Higgs bosons $h$, with two $h$’s decaying to two $b$ jets and diphoton sequentially. This channel is particularly involved when the relevant cubic coupling is enhanced. We find such enhancement to be possible when taking a large $CP$-odd Higgs mass input for the two-Higgs-doublet model spectrum. Analogous to the SM Higgs self-coupling measurement, the two $b$ jets plus diphoton final states are of particular interest due to the manageable SM background. After performing a cut-based analysis of both signal and background processes, we demonstrate the LHC search sensitivities for the heavy $CP$-even Higgs boson in a broad mass range via the two $b$ jets plus diphoton final states.

Physics-based inverse rendering enables joint optimization of shape, material, and lighting based on captured 2D images. To ensure accurate reconstruction, using a light model that closely resembles the captured environment is essential. Although the widely adopted distant environmental lighting model is adequate in many cases, we demonstrate that its inability to capture spatially varying illumination can lead to inaccurate reconstructions in many real-world inverse rendering scenarios. To address this limitation, we incorporate NeRF as a non-distant environment emitter into the inverse rendering pipeline. Additionally, we introduce an emitter importance sampling technique for NeRF to reduce the rendering variance. Through comparisons on both real and synthetic datasets, our results demonstrate that our NeRF-based emitter offers a more precise representation of scene lighting, thereby improving the accuracy of inverse rendering.

The Graph Convolutional Network (GCN) has recently achieved promising performance in human motion prediction by modeling the nodes and edges of the human skeleton. However, most previous methods still suffer from two unaddressed drawbacks. First, in the inference stage, their graph topologies are static and fixed, resulting in dependencies between nodes that cannot be dynamically adjusted for different actions. Second, the implicit relationships between pose sequences are ignored, which makes the prior advantages of the graph structure invalid in temporal feature fusion. To address these limitations, we propose an adaptive spatial-temporal graph-mixer (GraphMixer) for human motion prediction, which consists of a series of fully separated spatial-temporal graph convolution structures. In spatial GCN, we construct an additional adaptive skeleton graph to capture the node features of action-specific poses. In temporal GCN, we introduce a variety of graph topologies to enhance feature fusion between pose sequences. Comparing state-of-the-art algorithms on the Human 3.6 M and the 3 DPW datasets and ablation studies shows that our GraphMixer and the proposed multiple graph topologies are effective and critical.

The escalating problem of water pollution has become an urgent concern, as it significantly undermines people's quality of life and overall public health. The increasing severity of water pollution represents a global challenge, with profound implications for human society. In this study, hydrothermal carbonization coupled with alkaline activation was utilized to repurpose barley straw into activated carbon (AC) as an absorbent. Silver phosphate (Ag₃PO₄) was synthesized as a potent photocatalyst. Subsequent ultrasound-assisted loading integrated the robust adsorptive capabilities of the AC with the advanced photocatalytic efficiency of silver phosphate, resulting in a superior composite material (AC/Ag₃PO₄) and implementing a novel "absorption-photocatalysis" active circular degradation strategy to remove hazardous organics in water. Comprehensive characterization assays confirmed the successful synthesis and incorporation of Ag₃PO₄ onto the AC scaffold. The composite with a Ag₃PO₄ concentration of 3 wt % exhibited a high methylene blue (MB) removal efficiency of 99.4% within 100 min. The reaction rate of this composite surpassed that of standalone AC by a factor of 2.89. Furthermore, cyclic regeneration studies via adsorption-desorption methodologies revealed the composite's resilience and sustained performance. The MB removal efficiency was maintained at 85.5% over five consecutive cycles, demonstrating the composite's remarkable stability. The integration of adsorptive and photocatalytic functionalities within a single system mitigates potential secondary pollution arising during the AC's desorption phase and enhances the organic contaminant removal efficiency. Moreover, the utilization of this integrated material reduces the quantity of chemicals and energy required for conventional adsorption water treatment techniques, as the material harnesses sunlight or alternative light sources to catalyze contaminant decomposition. This reduces the dependence on chemical treatment agents, contributing to resource conservation and alleviating environmental burdens. This pioneering approach offers a novel paradigm for addressing pollutant challenges in aqueous environments.

The usually considered vacuum of the two-Higgs-doublet model (2HDM) could be unstable if it locates at a local but not global minimum (GM) of the scalar potential. By requiring the vacuum to be a GM, we obtain an additional constraint, namely the GM constraint, on the scalar potential. In this work, we explore the GM constraint on the $CP$-conserving general 2HDM. This constraint is found to put limits on the soft ${\mathbb{Z}}_2$ breaking mass parameter $m_{12}^2$ and also squeeze the heavy $CP$-even Higgs boson mass into larger values for the $m_{12}^2<0$ case. Combined with the current global signal fits from the LHC measurements of the 125 GeV Higgs boson, we discuss the phenomenological implications for the heavy Higgs boson searches at the LHC.