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The classroom video has a complex background and dense targets. This study utilizes small object detection technology to analyze and evaluate students’ behavior in the classroom, aiming to objectively and accurately assess classroom quality. Firstly, noise is removed from the images using a median filter, and the contrast of the images is enhanced through histogram equalization. Label smoothing is applied to reduce the model’s sensitivity to labels. Then, features are extracted from the preprocessed images, and multi-scale feature fusion is employed to enhance semantic expression across multiple scales. Finally, a combination loss function is utilized to improve the accuracy of multi-object recognition tasks. Real-time detection of students’ behaviors in the classroom is performed based on the small object detection model. The average head-up rate in the classroom is calculated, and the quality of teaching is evaluated and analyzed. This study explores the methods and applications of small object detection technology based on actual teaching cases and analyzes and evaluates its effectiveness in evaluating the quality of higher education classroom teaching. The research findings demonstrate the significant importance of small object detection technology in effectively evaluating students’ learning conditions in higher education classrooms, leading to improved teaching quality and personalized education.

Spermatogenesis is a complicated process involving mitotically proliferating spermatogonial cells, meiotically dividing spermatocytes, and spermatid going through maturation into spermatozoa. The post-translational modifications of proteins play important roles in this biological process. S-palmitoylation is one type of protein modifications catalyzed by zinc finger Asp-His-His-Cys (ZDHHC)-family palmitoyl S-acyltransferases. There are 23 mammalian ZDHHCs that have been identified in mouse. Among them, Zdhhc19 is highly expressed in adult testis. However, the in vivo function of Zdhhc19 in mouse spermatogenesis and fertility remains unknown. In this study, we knocked out the Zdhhc19 gene by generating a 2609 bp deletion from exon 3 to exon 6 in mice. No differences were found in testis morphology and testis/body weight ratios upon Zdhhc19 deletion. Spermatogenesis was not disrupted in Zdhhc19 knockout mice, in which properly developed TRA98+ germ cells, SYCP3+ spermatocytes, and TNP1+ spermatids/spermatozoa were detected in seminiferous tubules. Nevertheless, Zdhhc19 knockout mice were male infertile. Zdhhc19 deficient spermatozoa exhibited multiple defects including abnormal morphology of sperm tails and heads, decreased motility, and disturbed acrosome reaction. All of these led to the inability of Zdhhc19 mutant sperm to fertilize oocytes in IVF assays. Taken together, our results support the fact that Zdhhc19 is a testis enriched gene dispensable for spermatogenesis, but is essential for sperm functions in mice.

Iso-butene (iso-C 4 H 8 ) is an important raw material in chemical industry, whereas its efficient separation remains challenging due to similar molecular properties of C 4 olefins. The ideal adsorbent should possess simultaneous high uptakes for 1,3-butadiene (C 4 H 6 ) and n-butene (n-C 4 H 8 ) counterparts, endowing high efficiency for iso-C 4 H 8 separation in adsorption columns. Herein, a sulfate-pillared adsorbent, SOFOUR-DPDS-Ni (DPDS = 4,4′-dipyridyldisulfide), is reported for the efficient iso-C 4 H 8 separation from binary and ternary C 4 olefin mixtures. The rigidity in pore sizes and shapes of SOFOUR-DPDS-Ni exerts the molecular sieving of iso-C 4 H 8 , while exhibiting high C 4 H 6 and n-C 4 H 8 uptakes. The benchmark Henry’s selectivity for C 4 H 6 /iso-C 4 H 8 (2321.8) and n-C 4 H 8 /iso-C 4 H 8 (233.5) outperforms most reported adsorbents. Computational simulations reveal the strong interactions for C 4 H 6 and n-C 4 H 8 . Furthermore, dynamic breakthrough experiments demonstrate the direct production of high-purity iso-C 4 H 8 (>99.9%) from C 4 H 6 /iso-C 4 H 8 (50/50, v / v ), n-C 4 H 8 /iso-C 4 H 8 (50/50, v / v ), and C 4 H 6 /n-C 4 H 8 /iso-C 4 H 8 (50/15/35, v / v / v ) gas-mixtures. The efficient separation of iso-butene, an important raw material in chemical industry, remains challenging due to similar molecular properties of C 4 olefins. Here, the authors report a sulfate-pillared adsorbent for the molecular sieving of iso-C 4 H 8 from C 4 H 6 and n-C 4 H 8 with good benchmark uptake ratios and Henry’s selectivities.

Currently, the identification of unsafe behaviors among construction workers predominantly relies on manual methods, which are time-consuming, labor intensive, and inefficient. To enhance identification accuracy and ensure real-time performance, this paper proposes an enhanced YOLOv5s framework with three strategic improvements: (1) adoption of the Focal-EIoU loss function to resolve sample imbalance and localization inaccuracies in complex scenarios; (2) integration of the Coordinate Attention (CA) mechanism, which enhances spatial perception through channel-direction feature encoding, outperforming conventional SE blocks in positional sensitivity; and (3) development of a dedicated small-target detection layer to capture critical fine-grained features. Based on the improved model, a method for identifying unsafe behaviors of construction workers is proposed. Validated through a sluice renovation project in Jiangsu Province, the optimized model demonstrates a 3.6% higher recall (reducing missed detections) and a 2.2% mAP improvement over baseline, while maintaining a 42 FPS processing speed. The model effectively identifies unsafe behaviors at water conservancy construction sites, accurately detecting relevant unsafe actions, while meeting real-time performance requirements.

What are the main findings? We found that deep HAD Transformers are limited by “uniform processing” and proposed the Fidelity-Gated Context-Aware Transformer (GCAT), a novel dual-branch architecture with a fidelity-based gating module named the Contextual Feature Matching Module (CFMM) to explicitly separate background and anomaly processing paths. We are the first to introduce a KAN-MLP module into the HAD Transformer, addressing the “fixed activation” limitation of all prior deep models by using learnable, spline-based functions for superior non-linear approximation. What are the implications of the main finding? The complete Synergistic Kolmogorov–Arnold Networks and Fidelity-Gated Transformer (KANGT) framework achieves new state-of-the-art (SOTA) performance, demonstrating superior background suppression and anomaly separability across eight real-world HSI datasets. The synergistic design is validated by ablation studies, establishing a new paradigm for HAD that simultaneously solves both macro-architectural and micro-component limitations. Hyperspectral anomaly detection (HAD) remains a critical challenge in remote sensing, aiming to precisely separate sparse, unknown anomalies from complex, high-proportion backgrounds. Although deep learning architectures, particularly the Transformer, dominate HAD, their effectiveness is constrained by two fundamental deficiencies: the architectural flaw of “uniform processing” across feature tokens and the microscopic reliance on fixed non-linear activation functions, which are mathematically insufficient for modeling the complex HSI spectral features. To address this dual challenge, this paper introduces the Synergistic Kolmogorov–Arnold Network and Fidelity-Gated Transformer (KANGT) framework. This novel framework integrates two synergistic innovations: the Fidelity-Gated Context-Aware Transformer (GCAT), which employs a reconstruction fidelity-based gating module named the Contextual Feature Matching Module (CFMM) to explicitly and dynamically separate background and anomaly processing streams, and the KAN-MLP module, which replaces traditional Feed-Forward Networks (FFNs) with learnable, spline-based functions, enabling superior adaptive non-linear feature approximation. Extensive experiments on challenging real-world HSI datasets consistently demonstrate KANGT’s superior performance compared to existing methods, and the average AUC reached 0.9921 on eight datasets. This work establishes a robust new paradigm for HAD, with future efforts aimed at optimizing the computational efficiency of KANs to meet real-time application demands.

To address the issues of link mismatch and channel impairment in wireless optical communication across atmospheric-oceanic media, this paper proposes a two-hop relay transmission architecture based on the multiple-input multiple-output (MIMO)-enhanced multi-level hybrid multiplexing. The system implements decode-and-forward operations via maritime buoy/ship relays, achieving physical layer isolation between atmospheric and oceanic channels. The transmitter employs coherent orthogonal frequency division multiplexing technology with quadrature amplitude modulation to achieve frequency division multiplexing of baseband signals, combines with orthogonal polarization modulation to generate polarization-multiplexed signal beams, and finally realizes multi-dimensional signal transmission through MIMO spatial diversity. To cope with cross-medium environmental interference, a composite channel model is established, which includes atmospheric turbulence (Gamma–Gamma model), rain attenuation, and oceanic chlorophyll absorption and scattering effects. Simulation results show that the multi-level hybrid multiplexing method can significantly improve the data transmission rate of the system. Since the system adopts three channels of polarization-state data, the data transmission rate is increased by 200%; the two-hop relay method can effectively improve the communication performance of cross-medium optical communication and fundamentally solve the problem of light transmission in cross-medium planes; the use of MIMO technology has a compensating effect on the impacts of both atmospheric and marine environments, and as the number of light beams increases, the system performance can be further improved. This research provides technical implementation schemes and reference data for the design of high-capacity optical communication systems across air-sea media.

HighlightsA novel method is developed for precise control over the structure of 3D anodic aluminum oxide templates, enabling fine-tuning of both the vertical pore diameter and interspace within the templates.3D carbon tube nanoarrays featuring significantly thinner and denser tubes are constructed as high-quality electrodes for miniaturized filter capacitors.The 3D compactly arranged carbon tube-based capacitor achieves a remarkable specific areal capacitance of 3.23 mF cm−2 with a phase angle of − 80.2° at 120 Hz.Electric double-layer capacitors (EDLCs) with fast frequency response are regarded as small-scale alternatives to the commercial bulky aluminum electrolytic capacitors. Creating carbon-based nanoarray electrodes with precise alignment and smooth ion channels is crucial for enhancing EDLCs’ performance. However, controlling the density of macropore-dominated nanoarray electrodes poses challenges in boosting the capacitance of line-filtering EDLCs. Herein, a simple technique to finely adjust the vertical-pore diameter and inter-spacing in three-dimensional nanoporous anodic aluminum oxide (3D-AAO) template is achieved, and 3D compactly arranged carbon tube (3D-CACT) nanoarrays are created as electrodes for symmetrical EDLCs using nanoporous 3D-AAO template-assisted chemical vapor deposition of carbon. The 3D-CACT electrodes demonstrate a high surface area of 253.0 m2 g−1, a D/G band intensity ratio of 0.94, and a C/O atomic ratio of 8. As a result, the high-density 3D-CT nanoarray-based sandwich-type EDLCs demonstrate a record high specific areal capacitance of 3.23 mF cm−2 at 120 Hz and exceptional fast frequency response due to the vertically aligned and highly ordered nanoarray of closely packed CT units. The 3D-CT nanoarray electrode-based EDLCs could serve as line filters in integrated circuits, aiding power system miniaturization.

Efficient and stable treatment of oily wastewater has garnered significant attention from society. Nanofiber membranes, prepared by electrostatic spinning technology, offer advantages such as high porosity and a large specific surface area, making them widely applicable in oily wastewater treatment. However, conventional nanofiber membranes often suffer from drawbacks such as low strength and poor hydrophilicity, which hinder their further development. In this study, a high-strength and hydrophilic composite nanofiber membrane was successfully fabricated through electrostatic spinning of polyacrylonitrile (PAN) and polyurethane (PU), with tannic acid (TA) serving as a blending agent. The mechanical properties’ characterization revealed that the obtained modified composite nanofiber membrane exhibited a tensile strength of 6.42 MPa and an elongation at break of 132.52%. The addition of TA significantly enhanced the wettability of the composite nanofiber membranes. The PAN/PU-TA composite nanofiber membranes demonstrated impressive separation flux (up to 3176.75 L m −2 ·h −1 ) and separation efficiency (up to 99%) for various oil compounds. Moreover, the separation efficiencies for different types of oil-in-water (O/W) emulsions were consistently above 95.44%. In general, the utilization of TA for hydrophilic modification of PAN/PU composite nanofiber membranes not only enhanced the mechanical and wetting properties of the nanofiber membranes but also offered new insights into the modified nanofiber membrane process and electrostatic spinning technology. Graphical Abstract

Background Apoprotein A-I (ApoA-I) and Apoprotein B (ApoB) have emerged as novel cardiovascular risk biomarkers influenced by feeding behavior. Hypothalamic appetite peptides regulate feeding behavior and impact lipoprotein levels, which effects vary in different weight states. This study explores the intricate relationship between body mass index (BMI), hypothalamic appetite peptides, and apolipoproteins with emphasis on the moderating role of body weight in the association between neuropeptide Y (NPY), ghrelin, orexin A (OXA), oxytocin in cerebrospinal fluid (CSF) and peripheral ApoA-I and ApoB. Methods In this cross-sectional study, we included participants with a mean age of 31.77 ± 10.25 years, categorized into a normal weight (NW) ( n  = 73) and an overweight/obese (OW/OB) ( n  = 117) group based on BMI. NPY, ghrelin, OXA, and oxytocin levels in CSF were measured. Results In the NW group, peripheral ApoA-I levels were higher, while ApoB levels were lower than in the OW/OB group (all p  < 0.05). CSF NPY exhibited a positive correlation with peripheral ApoA-I in the NW group ( r  = 0.39, p  = 0.001). Notably, participants with higher CSF NPY levels had higher peripheral ApoA-I levels in the NW group and lower peripheral ApoA-I levels in the OW/OB group, showing the significant moderating effect of BMI on this association (R 2  = 0.144, β=-0.54, p  < 0.001). The correlation between ghrelin, OXA and oxytocin in CSF and peripheral ApoB in both groups exhibited opposing trends (Ghrelin:  r  = -0.03 and r  = 0.04; OXA: r  = 0.23 and r =-0.01; Oxytocin: r =-0.09 and r  = 0.04). Conclusion This study provides hitherto undocumented evidence that BMI moderates the relationship between CSF NPY and peripheral ApoA-I levels. It also reveals the protective role of NPY in the NW population, contrasting with its risk factor role in the OW/OB population, which was associated with the at-risk for cardiovascular disease.

This paper studies the problem of planning and scheduling in selective maintenance tasks of mission requirements and the health condition of the fleet. In order to deal with the problems of high maintenance cost and long time consumption in maintenance systems, a two-stage fleet maintenance optimization method is proposed. Firstly, a selective maintenance model of fleets based on age reduction is established to maximize the probability of completing the next mission and minimize the maintenance cost. Secondly, a multiobjective sparrow search algorithm is designed to solve the maintenance planning problem in the first stage, and a nondominated solution set of maintenance strategies satisfying the mission constraint is obtained. In the second stage, the simulated annealing algorithm is used to schedule the maintenance task and obtain the minimum maintenance hours required by the maintenance strategy. An example analysis of a vehicle fleet is launched to prove the effectiveness of this method. In a word, this method not only meets the mission requirements but also achieves the purpose of reducing maintenance cost and maintenance hours, which can provide reference for other types of equipment maintenance.