武夷学院

Simultaneous abatement of NOx and volatile organic compounds (VOCs) is severely hampered by mutual inhibition on conventional catalysts. Here, we rationally design a bifunctional Ce-Mn-Ti oxide catalyst that overcomes this challenge via an 'active site decoupling' strategy. The Ti-doping plays a pivotal dual role. It engineers abundant oxygen vacancies on Ce-Mn centers, dedicated to toluene deep oxidation, while concurrently forming robust Ti Lewis acid sites for selective NOx activation in the NH3-SCR reaction. This spatial segregation of catalytic functions is unequivocally confirmed by in-situ DRIFTS and DFT calculations, which show that the two reactions proceed on distinct, non-interfering sites. This elegant site-separation circumvents competitive inhibition, unlocking unprecedented synergy: the optimized catalyst achieves nearly 90% simultaneous removal of both pollutants over a broad 240-300 degrees C window, with excellent durability against H2O and SO2. This work offers a new paradigm for designing multifunctional catalysts, demonstrating that spatially engineering active sites is a powerful strategy for complex multi-pollutant abatement.

Artificial intelligence (AI) shopping assistants explain why a product is selected, yet the appropriate defaults remain unclear. We define recommendation information volume as the amount of nonredundant, product-relevant information and compare five ordered explanation packages. Study 1 identifies an inverted-U response in a randomized Chinese mobile-retail experiment. Study S1 compares identical messages attributed to an AI assistant or a human salesperson, with separate source-neutral measurement validation. Study 2 reports conditional positive indirect associations through perceived usefulness, trust in AI, and decision comfort, and conditional negative indirect associations through information overload and algorithmic over-justification. Same-session estimates do not establish causal mediation. Its product-version comparison combines complexity, functionality, and safety considerations. Study 3 provides behavioral evidence across 51,248 recommendation impressions and service outcomes for 5000 distinct users. Moderate packages perform best within the tested sets. Bounded information processing explains the benefit–burden trade-off; persuasion knowledge suggests that disproportionate justification depends on expectations of selective versus comprehensive advice, across AI and human sources. Because amount, diagnostic priority, and content composition vary jointly, the experiments identify assigned-package effects, not pure quantity effects. The findings support category-specific testing of default explanations without establishing an exclusively algorithmic mechanism.

Glioblastoma multiforme (GBM) remains difficult to treat due to complex biological barriers and a high rate of recurrence. Near-infrared II (NIR-II) phototheranostic nanomedicine, which offers superior tissue penetration depth and enhanced photothermal effects, has emerged as a a promising approach for GBM theranostics. In this study, we first propose a molecular design strategy that introduces expanded free space within aggregates to enhance nonradiative decay and maximize the photothermal efficacy (PCE). Building on this, we developed a holo-transferrin (holo-Tf)-based nanomedicine incorporating the designed phototheranostic molecules. This platform enables efficient blood-brain barrier (BBB) penetration via transferrin receptor (TfR)-mediated transcytosis and targeted delivery to tumor. Under 808 nm laser irradiation, this nanomedicine facilitates precise photothermal therapy (PTT) while simultaneously inducing ferroptosis. This dual action synergistically improves therapeutic outcomes by suppressing of heat shock proteins (HSPs) through ferroptosis. Overall, we developed a one-step self-assembled nanomedicine that integrates five functions: BBB penetration, tumor targeting, fluorescence imaging (FLI), photothermal imaging (PTI), and photothermal-ferroptosis combinatorial therapy. This innovation effectively addresses key challenges in BBB traversal and tumor-specific delivery, establishing an integrated paradigm that combines molecular design, biomimetic engineering, and multimodal therapeutic synergy for advanced GBM theranostics.

With the advancement of machine learning, domain adaptation has become increasingly important. Traditional research in domain adaptation has primarily focused on Unsupervised Domain Adaptation (UDA) and Semi-Supervised Domain Adaptation (SSDA). However, in many practical applications, it is common to encounter scenarios where both domains have labeled and unlabeled samples, which complicates the handling of domain adaptation. The scarcity of solutions to these scenarios further underscores the necessity of developing new methods to effectively explore the labeled and unlabeled samples. This paper proposes the problem of Bi-directional Semi-Supervised Domain Adaptation (BiSSDA) and a method of Gradient discrepancy minimization and labeled Class Centroid Align (GCCA) to address this problem. In GCCA, labeled and unlabeled samples from both domains are passed through a generator G and two classifiers F1 and F2, the generator G opposes with F1 and F2 during training and in which both domains are better aligned via gradient and class centroid alignment. Extensive experiments on three widely used datasets demonstrate that GCCA significantly outperforms CGDM and several previous SSDA methods in terms of exploring the labeled and unlabeled samples in both domains and significantly reduce the reliance on labeled data in bi-directional domain adaptation through cooperation between two domains. The code of the proposed method is available at the website of gitee.com/ymw12345/gcca.

Microbial carbon use efficiency (CUE) and nitrogen use efficiency (NUE) are key parameters that determine the fate of carbon (C) and nitrogen (N) in soils. However, the responses of microbial CUE and NUE to N deposition across soil depths remain poorly understood. In this study, we conducted an N-addition experiment in a Castanopsis faberi forest. Soil samples were collected from the topsoil (0-10 cm) and subsoil (20-30 cm) under three N addition levels to investigate depth-specific responses of microbial CUE and NUE. Changes in soil C fractions, microbial biomass, enzyme activities, and microbial community composition were assessed. Results showed a significant positive correlation between CUE and NUE, indicating a closed relationship between microbial C and N metabolism. Nitrogen addition reduced CUE and NUE at both depths, though the negative effects were less pronounced in the subsoil. Nitrogen addition significantly altered soil C fractions: labile C and particulate organic C increased in the topsoil, whereas mineral-associated organic C and recalcitrant C decreased in the subsoil. Microbial CUE and NUE were significantly correlated with the quantity of soil C fractions. Compared to the topsoil, the subsoil had lower CUE, NUE and dissolved organic C content but a higher C/N ratio, suggesting that differences in CUE and NUE between soil depths are regulated by both the quantity and quality of soil C. These findings reveal a depth-dependent yet directionally consistent effect of N addition on microbial resource-use efficiency, offering new insights into C-N coupling processes in forest ecosystems. This study investigated the changes in soil microbial carbon use efficiency and nitrogen use efficiency across different soil layers of Castanopsis faberi forests under various nitrogen addition gradients. By integrating data on soil carbon fractions, enzyme activities, and microbial community structure, it revealed a depth-dependent yet consistently inhibitory response of microbial resource use efficiency to nitrogen addition, providing new experimental evidence for a understanding of the coupling mechanisms of carbon and nitrogen cycling in forest ecosystems. (sic)(sic): (sic)(sic)(sic)(sic)/(sic)(sic)(sic)(sic)(sic)((sic)(sic)(sic)CUE(sic)NUE(sic)(sic))(sic)(sic)(sic)(sic)(sic)(sic)(C)(sic)(sic)(N)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)CUE(sic)NUE(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(Castanopsis faberi)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(0-10 cm)(sic)(sic)(sic)(sic)(sic)(sic)(20-30 cm)(sic)(sic)(sic)CUE(sic)NUE, (sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)CUE(sic)NUE(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic):1)(sic)(sic)(sic)CUE(sic)NUE(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)CUE(sic)NUE, (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).2)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic);(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)CUE(sic)NUE(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).3)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)CUE,NUE(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)C/N(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)CUE(sic)NUE(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)-(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).