Huaibei Normal University

Bacterial contamination is a thorny issue for public health protection in the 21st century, which causes a huge threat to human life and economic development. Photocatalytic disinfection has been verified as a promising technique to address the issue owing to its inexpensive, green, and sustainable process. Nevertheless, continuous external light illumination is indispensable for the photocatalytic disinfection reaction, which becomes an Achilles’ Heel for the practical application of this technique. Long afterglow luminescent material with a unique “light storage” effect can effectively support photocatalytic disinfection reaction under conditions of no light or even darkness, brightening the prospect of continuous bacteria inactivation. Herein, we critically envisage the perspective of bacterial disinfection by long afterglow luminescent material, and outlook the ongoing challenge and study direction of the material fabrication, mechanistic exploration, and disinfection applications in this frontier field.

To investigate the mechanisms through which negative life events, self-concealment, and maladaptive emotion regulation influence non-suicidal self-injurious behavior among Chinese college students. A total of 655 college students were surveyed using the Adolescents Self-Harm Scale (ASHS), Self-Concealment Scale (SCS), the Adolescent self-rating life events checklist (ASLEC), and Cognitive Emotion Regulation Questionnaire (CERQ). The findings revealed that: (1) negative life events exhibited a significant positive correlation with non-suicidal self-injurious behavior; (2) maladaptive emotion regulation served as mediators in the relationship between negative life events and non-suicidal self-injurious behavior; and (3) both self-concealment and maladaptive emotion regulation functioned as chain mediators in the impact of negative life events on non-suicidal self-injurious behavior.

Owing to its abundant coal reserves, Huaibei serves as a critical energy supply base in East China. However, coal exploitation and utilization have led to severe environmental challenges. To improve pollution source control and advance soil contamination remediation in mining areas, we investigated the pollution characteristics, source apportionment, and health risks of polycyclic aromatic compounds (PACs) in soils around the Liuqiao coal mining area in Huaibei. The total PAC concentration (ΣPACs) ranged from 142.0 to 11,400ng/g (mean: 1440ng/g), with alkylated polycyclic aromatic hydrocarbons being the dominant contributors (49.4%). Seven high-carcinogenicity PAHs (BaA, CHR, BbF, BkF, BaP, DBA, and InP) accounted for 40.4% of the Σ16PAHs, indicating potential health concerns. Integrated analysis using diagnostic ratios, positive matrix factorization, and absolute principal component score-multivariate linear regression indicated multiple PAC sources, including petrogenic inputs and combustion-related sources (e.g., diesel/traffic-related combustion, biomass/coke ovens, and coal combustion). Deterministic human health risk assessment and Monte Carlo uncertainty analysis suggested that total carcinogenic risks for adults and children exceed the United States Environmental Protection Agency benchmark (1 × 10-6). Source-oriented risk modeling further indicated that petrogenic and combustion-related sources are the main contributors to carcinogenic risk, although their relative importance differed between PMF and APCS-MLR. This study provides an integrated framework for PAC source tracing and health risk assessment in mining-impacted regions and supports targeted pollution control and management.

Cognitive modeling, as an emerging technology in the field of computer-aided education, aims to explore students’ knowledge levels and learning abilities to achieve various intelligent educational applications. Although some existing work focuses on addressing the problem of student forgetting, it is still a less explored area how to naturally integrate the forgetting effect caused by the time interval between answering exercises into student knowledge state modeling. Additionally, traditional cognitive modeling methods mostly assume that students answer exercises one by one, which often does not align with real answering behavior and cannot be directly extended to diverse learning scenarios. Therefore, in this article, we propose a Continuous Time-based Neural Cognitive (CT-NC) framework and several implemented models (CT-NCM and two extensions) to effectively integrate the dynamic and continuous characteristics of knowledge forgetting into student learning process modeling, making it more natural. Specifically, we adopt a specially designed learning event encoding method to adjust the neural Hawkes process to capture the relationship between knowledge learning and forgetting over continuous time. Furthermore, we propose a customizable learning function to jointly model the changes in different knowledge states and their interaction with each practice moment. In the end, we demonstrate an extension CT-NCM+ that can adapt well to diverse learning scenarios, indicating that CT-NCM can solve real-world problems by flexibly adjusting its structure. Extensive experimental results on real datasets clearly demonstrate that CT-NCM and CT-NCM+ outperform the current state-of-the-art KT methods in student performance prediction, while our work points out a realistic research direction for KT and demonstrates its interpretability in knowledge learning visualization.

Optical digital computing, leveraging optical signals for high-speed, efficient, and high-precision discretized digital computations and information processing, is widely applied in artificial intelligence, communication, and network. However, the development of multiplication/division, pivotal components within digital optical computing systems, has been constrained by the absence of effective computational physical dimensions conducive to manipulating optical signals and the stringent requirement for precise operational control. We propose a fixed-base multiplication and division scheme based on orbital angular momentum (OAM) modes using optical diffractive neural networks (ODNNs). Utilizing the OAM mode as the computational physical dimension, and employing ODNN to perform mode-parallel and independent transformations on it for achieving numerical equivalent shifts, it is feasible to realize 2n-fold multiplication and division operations. Using this mechanism, we have constructed a 3-layer ODNN to realize OAM mode fixed-base multiplication and division for n = 1, 2, and 3, with mode purities of the operation outputs reaching 99%. Furthermore, a dynamic switching between multiplication and division operations has been achieved within the same system through rotation of the phase matrix. Our design suggests a feasible pathway for fixed-base optical multiplication and division, and may offer useful insights for future research on optical digital computing architectures.

Abstract Six novel Zn(II), Cd(II) and Co(II) mixed-ligand coordination complexes, namely, Cd(HOBA) 2 (DPE) 2 (H 2 O) 2 ( 1 ), Co(HOBA) 2 (DPE) 2 (H 2 O) 2 ( 2 ), [Zn(DPA) 2 (DPE)] n ( 3 ), [Zn(CPA) 2 (BPP)] n ( 4 ), [Cd 2 (CPA) 4 (BPP) 2 (H 2 O)] n ( 5 ), and [Cd(DPA) 2 (DPE)] n ( 6 ) (H 2 OBA = 4-carboxylphenoxyacetic acid, HDPA = 2,4-dichlorophenoxyacetic acid, HCPA = 2-chlorophenoxyacetic acid, DPE = 1,2-di(pyridin-4-yl)ethylene, BPP = 1,3-bis(4-pyridyl)propane) have been synthesized hydrothermally by the self-assembly of R-phenoxyacetic acid (R = 2,4-dichloro, 2-chloro and 4-carboxyl), N-donor ligands and Zn(II), Cd(II) or Co(II) salts. Single crystal X-ray analyses reveal that in complexes 1 and 2 , the H 2 OBA and DPE act as terminal ligands, generating 0D Cd(II) and Co(II) mononuclear molecules. Complexes 3 and 4 both show 1D chain structures, where the four-coordinated Zn(II) ions are bridged by DPE and BPP, respectively. For complex 5 , the six- and seven-coordinated Cd(II) ions are interconnected through carboxyl groups to form [Cd 2 (CPA) 4 ] building units, which are subsequently extended by BPP ligands into 1D chains. In complex 6 , adjacent Cd(II) ions are bridged by DPA − anions to form a 1D linear chain. Through the bridging of DPE ligands, the 1D chains undergo dimensional expansion and eventually evolve into 2D supramolecular architectures. Furthermore, the thermal stabilities and fluorescence properties of these complexes have also been investigated.