Search Results (56)

Object detection in soccer scenes serves as a fundamental task for soccer video analysis and target tracking. This paper proposes WCC-YOLO, a symmetry-enhanced object detection framework based on YOLOv11n. Our approach integrates symmetry principles at multiple levels: (1) The novel C3k2-WTConv module synergistically combines conventional convolution with wavelet decomposition, leveraging the orthogonal symmetry of Haar wavelet quadrature mirror filters (QMFs) to achieve balanced frequency-domain decomposition and enhance multi-scale feature representation. (2) The Channel Prior Convolutional Attention (CPCA) mechanism incorporates symmetrical operations—using average-max pooling pairs in channel attention and multi-scale convolutional kernels in spatial attention—to automatically learn to prioritize semantically salient regions through channel-wise feature recalibration, thereby enabling balanced feature representation. Coupled with InnerShape-IoU for refined bounding box regression, WCC-YOLO achieves a 4.5% improvement in mAP@0.5:0.95 and a 5.7% gain in mAP@0.5 compared to the baseline YOLOv11n while simultaneously reducing the number of parameters and maintaining near-identical inference latency (δ < 0.1 ms). This work demonstrates the value of explicit symmetry-aware modeling for sports analytics. Full article

This study presents a novel ensemble deep-learning framework integrating Convolutional Neural Networks (CNN), self-attention mechanisms, and Long Short-Term Memory (LSTM) networks, designed to generate high-resolution drought susceptibility maps for the Oroqen Autonomous Banner of Inner Mongolia. The model was further enhanced through two metaheuristic optimization techniques—Differential Evolution (DE) and Biogeography-Based Optimization (BBO)—which tuned hyperparameters including CNN filters, LSTM units, and learning rate. Model evaluation—quantified via predictive accuracy (RMSE = 0.22 and MAE = 0.12), goodness-of-fit (R² = 0.79), and classification discrimination [Area Under the Receiver Operating Characteristic curve (AUROC) = 0.91]—revealed that the BBO-optimized ensemble achieved the best overall performance on the test set, outperforming the DE-enhanced (AUROC = 0.86) and baseline models (AUROC = 0.80). Pairwise z-statistics confirmed the statistical superiority of the BBO-enhanced ensemble with a p-value < 0.001. The final susceptibility map—classified into five levels using the Jenks natural breaks method—identified western rangelands and transitional ecotones as high-susceptibility zones, while eastern areas were marked by lower susceptibility. The resulting outputs offer decision-makers and land managers an interpretable, high-precision tool to guide drought preparedness, implement resource allocation strategies, and design early-warning systems. This research establishes a scalable, interpretable, and statistically robust approach for drought susceptibility assessment in vulnerable landscapes. Full article

This innovative study introduces an eco-conscious and cost-effective approach to synthesizing gelatin-based carbon dots (CDs) via two distinctive methods: hydrothermal processing in a muffle furnace (CDs-MF) and domestic microwave (CDs-MW). Both strategies harness natural, low-cost materials and prioritize simplicity, sustainability, and environmental friendliness, culminating in effective fluorescent sensing of the pesticide thiamethoxam (TMX). For the hydrothermal route, the investigation explores two purification approaches—ultracentrifugation (CDs-MF-C) and 0.22 µm syringe filtration (CDs-MF-F)—while the microwave-derived CDs (CDs-MW) undergo dialysis alone. This study aims to investigate how synthesis and purification impact the CDs structural, morphological, and photophysical characteristics. The difference in size was obtained from transmission electron microscopy (TEM): 30–40 nm for CDs-MF-C, 12–15 nm for CDs-MF-F, and 3–6 nm for CDs-MW. Fluorescence emission performance reveals that CDs-MF-F performs a fluorescence quantum yield of 27%, CDs-MF-C at 23%, and CDs-MW at a modest 3%. All variants exhibit TMX detection via fluorescence quenching through the inner filter effect (IFE). Analytically, CDs-MF-C stands out with the lowest detection limit (LOD = 0.396 ppm) and quantification limit (LOQ = 1.317 ppm), followed by CDs-MF-F (LOD = 0.475 ppm; LOQ = 1.585 ppm) and CDs-MW (LOD = 0.549 ppm; LOQ = 1.831 ppm). These findings emphasize the unique interplay between the synthesis pathway, purification strategy, and functional performance, demonstrating the critical importance of tuning structural properties for optimizing carbon-dot sensors. Full article

Today, several conventional wastes (fly ash, ground granulated blast furnace slags, etc.) are used as valid precursors for geopolymer synthesis. However, there are several new wastes that can be studied to replace geopolymer precursors. This study investigates the behavior of four industrial wastes—suction dust (SW1), red mud (SW2), electro-filter dust (SW3), and extraction sludge (SW4)—as 20 wt.% substitutes for metakaolin in geopolymer synthesis. The objective is to assess how their incorporation before alkali activation affects the structural, thermal, mechanical, chemical, and antimicrobial properties of the resulting geopolymers, namely GPSW1–4. FT-IR analysis confirmed successful geopolymerization in all samples (the main Si-O-T band underwent redshift, confirming Al incorporation in geopolymer structures after alkaline activation), and stability tests revealed that none of the GPSW1–4 samples disintegrated under thermal or water stress. However, GPSW3 showed an increase in efflorescence phenomena after these tests. Moreover, compressive strength was reduced across all waste-containing geopolymers (from 22.0 MPa for GP to 12.6 MPa for GPSW4 and values lower than 8.1 MPa for GPSW1–3), while leaching tests showed that GPSW1 and GPSW4 released antimony (127.5 and 0.128 ppm, respectively) above the legal limits for landfill disposal (0.07 ppm). Thermal analysis indicated that waste composition influenced dehydration and decomposition behavior. The antimicrobial activity of waste-based geopolymers was observed against E. coli, while E. faecalis showed stronger resistance. Overall, considering leaching properties, SW2 and SW3 were properly entrapped in the GP structure, but showed lower mechanical properties. However, their antimicrobial activity could be useful for surface coating applications. Regarding GPSW1 and GPSW4, the former needs some treatment before incorporation, since Sb is not stable, while the latter, showing a good compressive strength, higher thermal stability, and leaching Sb value not far from the legal limit, could be used for the inner reinforcement of building materials. Full article

Accurate detection of cherry tomato clusters and their ripeness stages is critical for the development of intelligent harvesting systems in modern agriculture. In response to the challenges posed by occlusion, overlapping clusters, and subtle ripeness variations under complex greenhouse environments, an improved YOLO11-based deep convolutional neural network detection model, called AFBF-YOLO, is proposed in this paper. First, a dataset comprising 486 RGB images and over 150,000 annotated instances was constructed and augmented, covering four ripeness stages and fruit clusters. Then, based on YOLO11, the ACmix attention mechanism was incorporated to strengthen feature representation under occluded and cluttered conditions. Additionally, a novel neck structure, FreqFusion-BiFPN, was designed to improve multi-scale feature fusion through frequency-aware filtering. Finally, a refined loss function, Inner-Focaler-IoU, was applied to enhance bounding box localization by emphasizing inner-region overlap and focusing on difficult samples. Experimental results show that AFBF-YOLO achieves a precision of 81.2%, a recall of 81.3%, and an mAP@0.5 of 85.6%, outperforming multiple mainstream YOLO series. High accuracy across ripeness stages and low computational complexity indicate it excels in simultaneous detection of cherry tomato fruit bunches and fruit maturity, supporting automated maturity assessment and robotic harvesting in precision agriculture. Full article

Three fluorophenyl-substituted cyclometalated Ir(III) complexes (Ir1–Ir3) have been synthesized by changing the position of the fluorine atom. All complexes exhibit distinct aggregation-induced phosphorescence emission (AIPE) characteristics in CH₃CN/H₂O and demonstrate satisfactory detection performance for 2,4,6-trinitrophenols (TNPs) with limits of detection of 124 nM, 101 nM, and 127 nM, respectively. In addition, Ir1–Ir3 possess excellent selectivity and anti-interference capability for TNP detection, showing outstanding performance even in different common water samples. The ultraviolet–visible absorption spectra and luminescence lifetimes of the complexes show that their quenching processes include both a static process and dynamic process, and the detection mechanism may be assigned to a combination of photo-induced electron transfer and an inner-filter effect. Full article

Background/Objectives: In rhegmatogenous retinal detachment (RRD), vitreous cortex remnants (VCRs) may contribute to the development and progression of proliferative vitreoretinopathy (PVR). This study aimed to evaluate potential toxicity and trauma secondary to VCRs visualization and removal during pars plana vitrectomy (PPV) for RRD. Methods: Prospective study on patients with primary RRD who underwent PPV. Imaging assessment included widefield OCT (WF-OCT), ultra-WF retinography and fundus autofluorescence (FAF). During PPV, a filtered and diluted triamcinolone acetonide (TA) solution (20 mg/mL) was used to evaluate the presence and extension of VCRs, removed using an extendible diamond-dusted sweeper (EDDS). After six months, retinal and retinal pigment epithelium toxicity and retinal trauma due to VCRs removal were investigated. Results: Retinal reattachment was achieved in 21/21 cases included in the study. No signs of retinal or RPE toxicity were detected and WF-OCT performed in the areas of VCRs removal revealed an intact inner retinal architecture in the majority of eyes, with minor and localized inner retinal indentations in 4 cases. Conclusions: VCRs visualization and removal using TA and EDDS appears to be safe, with no retinal toxicity and very limited and circumscribed mechanical trauma. This approach may contribute to reducing the risk of postoperative PVR. Full article

Cross-document relation extraction (CodRE) aims to predict the semantic relationships between target entities located in different documents, a critical capability for comprehensive knowledge graph construction and multi-source intelligence analysis. Existing approaches primarily rely on bridge entities to capture interdependencies between target entities across documents. However, these models face two potential limitations: they employ entity-centered context filters that overlook relation-specific information, and they fail to account for varying semantic distances between document paths. To address these challenges, we propose CLEAR (Cross-document Link-Enhanced Attention for Relations), a novel framework integrating three key components: (1) the Relation-aware Context Filter that incorporates relation type descriptions to preserve critical relation-specific evidence; (2) the Path Distance-Weighted Attention mechanism that dynamically adjusts attention weights based on semantic distances between document paths; and (3) a cross-path entity matrix that leverages inner- and inter-path relations to enrich target entity representations. Experimental results on the CodRED benchmark demonstrate that CLEAR outperforms all competitive baselines, achieving state-of-the-art performance, with 68.78% AUC and 68.42% F1 scores, confirming the effectiveness of our framework. Full article

About ten years ago, we established the first coronagraph that has been continuously operating on the high plateau of western China. This coronagraph is an internal occulting, 10 cm aperture instrument, installed at Lijiang Station through a collaboration with the Norikura Station of the National Astronomical Observatory of Japan. To ensure high efficiency in current and future coronal observations, developing integrated observation systems is essential for reliable, autonomous, and remote operation of coronagraphs. This paper introduces an advanced integrated observation and control system, based on the Lijiang 10 cm coronagraph. The coronagraph focuses on the observations for the solar inner corona, capturing the coronal green-line emission within a field range from $1.03R_{⨀}$ to $2.5R_{⨀}$. To enhance the observational precision and efficiency, a comprehensive integrated system has been designed, incorporating various subsystems, including precise pointing and tracking mechanisms, a multi-band filter system, a protective dome system, and a robust data storage infrastructure. This paper details the hardware architecture and software frameworks supporting each subsystem. Results from extended operational testing confirm the stability of the system, its capacity for autonomous and remote observations, and significant improvements in the automation and efficiency of coronal imaging. The automated observation system will be further improved and used for our future coronagraphs to be developed for coronal magnetism diagnosis. Full article

This paper presents a variable step-size efficient learning modified P&O (LMPO) MPPT algorithm and adaptive proportional–integral (API)-based control techniques for a two-stage three-phase grid-integrated photovoltaic (TS-GIPV) system using an LCL filter. The proposed novel controlled technique introduces two-stage systems under different meteorological conditions and load deviations. The two-stage system with the presented control technique includes maximum power point tracking (MPPT) techniques, intermediate DC-link voltage, and grid current synchronization with a voltage source converter (VSC), respectively. This technique is implemented to improve the extract MPP of the solar PV generator system. An innovative grid-side VSC control technique addresses DC link regulation. Furthermore, this method regulates DC link voltage with an outer voltage loop and an inner current loop controller. Distinctively, the proposed technique regulates the inner loop while avoiding the outer loop. A control mechanism uses an API controller to regulate DC link voltage, distribute power, and synchronize grid current in the face of different scenarios. The fluctuating voltage of the DC link will be kept stable through power balancing. Hence, this technique improves the system stability, dynamic response, and component longevity by effectively reducing oscillations in the fluctuating DC link voltage at twice the grid frequency. The total harmonic distortion (THD%) of the grid currents of the PV power generated in the grid is maintained within the recommended limits. The proposed technique is simulated and verified through MATLAB/Simulink 2019b under different scenarios. Full article

Bearing condition monitoring and prognosis are crucial tasks for ensuring the proper operation of rotating machinery and mechanical systems. Vibration signal analysis is one of the most effective techniques for bearing condition monitoring and prognosis. In this study, the wavelet scattering transform, derived from wavelet transforms and incorporating concepts from scattering transform and convolutional network architectures, was utilized to extract quantitative features from vibration signals. The number of wavelet scattering coefficients obtained from vibration signals of different lengths varied due to the use of predefined wavelet and scaling filters in the wavelet scattering network. Additionally, these wavelet scattering coefficients are associated with different scattering paths within the corresponding wavelet scattering networks. Eight different lengths of vibration signals, associated with fifteen classes of rolling element bearing faults and conditions, were investigated using wavelet scattering feature extraction. The classes of rolling element bearing faults and conditions included normal bearings as well as ball and inner race faults with various fault diameters ranging from 0.007 inches to 0.028 inches. For the specific dataset validated, the computational results indicated that excellent bearing fault classification was achievable using wavelet scattering feature vectors derived from vibration signals with lengths of at least 6000 samples. Full article

Bearings are the most vulnerable component in low-voltage induction motors from a maintenance standpoint. Vibration monitoring is the benchmark technique for identifying mechanical faults in rotating machinery, including the diagnosis of bearing defects. The study of different bearing fault phenomena under induction motor transient conditions offers interesting capabilities to enhance classic fault detection techniques. This study analyzes the low-frequency localized bearing fault signatures in both the inner and outer races during the start-up and steady-state operation of inverter-fed and line-started induction motors. For this aim, the classic vibration envelope spectrum technique is explored in the time–frequency domain by using a simple, resampling-free, Short Time Fourier Transform (STFT) and a band-pass filtering stage. The vibration data are acquired in the motor housing in the radial direction for different load points. In addition, two different localized defect sizes are considered to explore the influence of the defect width. The analysis of extracted low-frequency characteristic frequencies conducted in this study demonstrates the feasibility of detecting early-stage localized bearing defects in induction motors across various operating conditions and actuation modes. Full article

A Dy(III) coordination polymer (CP), [Dy(spasds)(H₂O)₂]_n (1) (Na₂Hspasds = 5-(4-sulfophenylazo)salicylic disodium salt), has been synthesized using a hydrothermal method and characterized. 1 features a 2D layered structure, where the spasda³⁻ anions act as pentadentate ligands, adopting carboxylate, sulfonate and phenolate groups to bridge with four Dy centers in η₃-μ¹: μ², η₂-μ¹: μ¹, and monodentate coordination modes, respectively. It possesses a unique (4,4)-connected net with a Schläfli symbol of {4⁴·6²}{4}₂. The luminescence study revealed that 1 exhibited a broad fluorescent emission band at 392 nm. Moreover, the visual blue color has been confirmed by the CIE plot. 1 can serve as a dual-functional luminescent sensor toward Fe³⁺ and MnO₄⁻ through the luminescence quenching effect, with limits of detection (LODs) of 9.30 × 10⁻⁷ and 1.19 × 10⁻⁶ M, respectively. The LODs are relatively low in comparison with those of the reported CP-based sensors for Fe³⁺ and MnO₄⁻. In addition, 1 also has high selectivity and remarkable anti-interference ability, as well as good recyclability for at least five cycles. Furthermore, the potential application of the sensor for the detection of Fe³⁺ and MnO₄⁻ was studied through simulated wastewater samples with different concentrations. The possible sensing mechanisms were investigated using Ultraviolet-Visible (UV-Vis) absorption spectroscopy and density functional theory (DFT) calculations. The results revealed that the luminescence turn-off effects toward Fe³⁺ and MnO₄⁻ were caused by competitive absorption and photoinduced electron transfer (PET), and competitive absorption and inner filter effect (IFE), respectively. Full article

In power systems, nonlinear loads cause harmonic distortion, adversely affecting sensitive equipment such as induction motors, power electronics, and variable-speed drives. This paper presents a novel control strategy that integrates with existing hierarchical control systems to mitigate voltage imbalances and harmonic disturbances in AC-islanded microgrids. The proposed method utilizes selective harmonic order filtering through multiple second-order generalized integrators (MSOGI) to extract negative, positive, and harmonic order components. The distributed generation (DG) unit control mechanism is designed to immediately correct voltage imbalances and harmonic disruptions, distributing the compensatory load evenly to rectify real and reactive power imbalances and harmonic disturbances. The microgrid’s control architecture primarily includes droop controllers for real and reactive power of positive sequences, voltage and current regulation inner control loops, an additional loop for correcting imbalances and harmonics, and secondary controllers to maintain voltage magnitude and frequency at nominal levels, ensuring high-quality voltage at the point of common coupling (PCC). The effectiveness of this approach is demonstrated through simulation results on the MATLAB/Simulink platform, proving its ability to effectively mitigate voltage imbalances and harmonic issues with the total harmonic of voltage reduced to approximately THDv = 0.5% and voltage unbalance factor (VUF) within approximately 0.1%. Full article

The ratiometric fluorescent probe UiO-OH@Tb, a zirconium-based MOF functionalized with Tb³⁺, was synthesized using a hydrothermal method. This probe employs the fluorescence resonance energy transfer (FRET) mechanism between Tb³⁺ and malachite green (MG) for the double-inverse signal ratiometric fluorescence detection of MG. The probe’s color shifts from lime green to blue with an increasing concentration of MG. In contrast, the monometallic MOFs’ (UiO-OH) probe shows only blue fluorescence quenching due to the inner filter effect (IFE) after interacting with MG. Additionally, the composite fluorescent probe (UiO-OH@Tb) exhibits superior sensitivity, with a detection limit (LOD) of 0.19 μM, which is significantly lower than that of the monometallic MOFs (25 μM). Moreover, the content of MG can be detected on-site (LOD = 0.94 μM) using the RGB function of smartphones. Hence, the UiO-OH@Tb probe is proven to be an ideal material for MG detection, demonstrating significant practical value in real-world applications. Full article