Guangdong University of Technology

Emerging contaminants (ECs) including carbamazepine (CBZ) in aquatic systems pose non-target risks to wildlife. We introduce an innovative advanced oxidation process (AOP) utilizing sodium hypochlorite (NaClO), which achieved 45.3% degradation and mineralization of CBZ within 60 minutes. Natural saturated state dissolved oxygen (DO, ∼7.5 mg·L-1) played a crucial role in synergistically activating NaClO with dithionite (DTN) without extra energy consumption. In DO@NaClO/DTN system, scavenging tests and electron spin resonance (ESR) analysis confirmed that ·OH and Cl· were dominant for CBZ degradation. The critical DO was responsible for the direct simultaneous production of ·OH and Cl·, confirmed by the greater thermodynamic data ΔG from density functional theory (DFT) calculation. These reactive species participate in subsequent transformations of SO4·-, O2·-, and 1O2. Preferential hydroxylation of CBZ first occurred due to the attacking at the reactive sites of C(21) and C(22) atoms. LC-MS/MS detection and DFT theoretical calculations also verified the sequent mechanisms of Meinwald rearrangement, deamidation and hydroxylation, cyclized hydroxylated and dehydrated with the decreasing ΔG. Ubiquitous Cl- accelerated CBZ degradation remarkably, regardless of its concentration. The significant enhancement of Cl- for CBZ degradation in DO@NaClO/DTN system suggest its promising application for ECs degradation in high-chloride seawater including offshore wastewater and tailwater in mariculture.

Producing 5‐hydroxymethylfurfural (5‐HMF) from abundant and renewable cellulose is a practical method for lignocellulosic biomass valorization. Nonetheless, the high crystallinity of cellulose restricts the accessibility of catalysts, and the complex reaction pathway generally results in the formation of intermediate by‐products and 5‐HMF degradation. Molten salt hydrates (MSHs) are unique in dissolving crystalline cellulose and their weak Brønsted acidity can facilitate cellulose hydrolysis to glucose. In this work, one‐pot conversion of cellulose into 5‐HMF was carried out in LiBr MSHs/acetone biphasic system. The solid acid, Sn‐β, was used in the conversion to compensate for the shortages of MSH Lewis acidity. Under the optimized reaction condition at 180 °C for 20 min, a high 5‐HMF yield of 66.88 % was obtained from cellulose conversion. The influences of reaction conditions on 5‐HMF production were studied, and the synergistic effects of solvents and solid acid were established. The catalyzed can be readily recycled and regenerated via calcination. This technique provides a theoretical foundation and technical basis for constructing a one‐step conversion of commercial cellulose to value‐added 5‐HMF, which proposes significant effects on lignocellulose valorization.

This paper analyzes the form of content characterized by nodes in the text complex network model, and points out the way of constructing text network with text words as network nodes. The lexical co-occurrence relationship based on lexical semantics is delineated, and combined with the implementation process of the lexical co-occurrence analysis method, the keyword extraction method of lexical co-occurrence network based on the improved TextRank algorithm is proposed. Combine the features of complex networks and utilize the FWN short text clustering algorithm to reveal the semantic associations between words and words. Analyze the advantages of the improved TextRank algorithm. To count the distribution of lexical co-occurrence network node word classes in the English corpus in the fields of literature, journalism, and law, and to calculate the semantic relevance. In the total network of the English corpus (which contains word co-occurrence network in the field of news, word co-occurrence network in the field of literature, word co-occurrence network in the field of law), nouns have the highest number of nodes as nodes, followed by verbs. Time words have the least number of times as nodes.

A patch filtenna with high out‐of‐band suppression levels is presented in this letter. The proposed antenna is configured with a parasitic patch and a driven patch fed by a rectangular strip connected to a vertical coaxial probe. Etching four rectangular slots on the rhombus‐shaped driven patch can introduce a high‐frequency radiation null. One open rectangular ring connected to the rectangular feeding strip will produce a low‐frequency radiation null and introduce a resonance mode, making the operating bandwidth wider. Meanwhile, the parasitic patch is placed above the driven patch further to improve the impedance bandwidth and the high‐frequency filtering performance. The designed filtenna is 0.62λ0 × 0.62 λ0 × 0.13 λ0, where λ0 is the free space wavelength at the center frequency. The measured prototype demonstrates that the proposed antenna has a flat gain of 7.9 ± 0.4 dBi over the −10‐dB fractional bandwidth of 12.4% from 2.05 to 2.32 GHz, as well as a high suppression level of 26.1 and 20.6 dB at low‐ and high‐frequency out‐band. These advantages make the antenna suitable for 5G n34 band communication systems.

Stimuli‐responsive circularly polarized luminescence (CPL) materials show great promise for dynamic camouflage, information encryption, and smart sensing. However, synthesis complexity and limited practical versatility hinder current research. This study demonstrates novel thermochromic CPL microcapsules that contain chiral aggregation‐induced emission luminogens (AIEgens) doped alkane phase change materials (PCMs). The synthesized AIEgens, characterized by a high photoluminescence quantum yield of 73.3% and obvious chiroptical properties, are successfully incorporated into PCMs to form thermochromic CPL materials. Microencapsulation of the AIEgen‐doped PCMs effectively addresses practical concerns of leakage and corrosion, yielding stable and thermally reliable microcapsules. These microcapsules exhibit versatility across diverse polymeric matrices and substrate surfaces, highlighting their adaptability. Leveraging the thermochromic CPL properties, 2 and 3D information encryption systems based on microcapsule‐embedded coatings are developed, ensuring high‐level data security. Furthermore, their application in automotive camouflage and personalized decoration effectively adapts car coatings to diverse environmental terrains, improving aesthetics and versatility. The easy scalable fabrication and multifunctionality of these thermochromic CPL microcapsule‐embedded coatings hold transformative potential for security and camouflage, offering innovative solutions for protecting sensitive information and enhancing vehicle aesthetics.

As vocational undergraduate students in China face increasing challenges in the job market, understanding the factors that shape their employment expectations is crucial. Psychological capital is considered a key factor influencing students’ career outlooks. This study aims to examine the relationship between psychological capital (PC) and employment expectations (EE), while exploring the mediating roles of educational flow experience (EFE) and active coping style (ACS) in this relationship. Based on positive psychology and career development theories, a theoretical model was constructed to understand how psychological capital affects employment expectations through the chain mediation of educational flow experience and active coping style. A sample of 693 vocational undergraduate students (316 males and 377 females) from a university in Guangdong Province participated in the study. Participants completed the Psychological Capital Scale (PCS), the Career Expectation Scale (CES), the Educational Flow Experience Scale (EduFlow-2), and the Coping Style Scale (CSS). Results indicate that higher levels of psychological capital significantly predict stronger employment expectations. Moreover, educational flow experience and active coping style both serve as significant mediators in the relationship between psychological capital and employment expectations, with a chain mediation effect also observed. These findings provide valuable insights into the psychological processes that influence career expectations among vocational undergraduates, highlighting the importance of fostering psychological capital and creating supportive learning environments to improve students’ employability. The results offer practical implications for educators and policymakers, suggesting that vocational institutions should integrate strategies to enhance psychological capital, promote educational flow experiences, and support active coping styles to better prepare students for the labor market.

Owing to significant advantages of radar sensing, gait recognition based on radar point clouds has gained attention as a promising noninvasive human identification solution. However, it is difficult for radar point clouds to provide sufficient characterization of human gait features for the specular reflection and inconsistency across multiple frames. To address this issue, a Skeleton-aware Radar-based Gait recognition Network with cross-modal supervision is proposed, which is named SRGaitNet. To improve radar point clouds-based gait characterization, two key points are considered in the proposed network. On the one hand, the understanding of human structure from the visual modality is leveraged to guide the extraction of human pose-aware features from radar point cloud sequences. On the other hand, to effectively make use of the extracted human skeleton and enhance gait features, a transformer-based feature fusion module is designed to aggregate the spatial-temporal and human pose features. The SRGaitNet is comprised of three modules: the first is a base module for spatial-temporal feature extraction from radar point cloud sequences, the second is a pose estimator for human skeleton reconstruction, and the last is a transformer-based fusion module for integrating skeletal and spatial-temporal features. The network is jointly trained on dual-tasks and optimized by a combination of human identification cross-entropy and pose estimation mean square error loss. Comprehensive experimental evaluation demonstrates that the SRGaitNet is superior to existing radar point clouds-based gait recognition methods, with an average accuracy of 85.24% over different walking paths.