Search Results (561)

Introduction: Breast density is a well-recognized factor in breast cancer risk assessment, with higher density linked to increased malignancy risk and reduced sensitivity of conventional mammography. Background parenchymal enhancement (BPE), observed in contrast-enhanced imaging, reflects physiological contrast uptake in non-pathologic breast tissue. While extensively characterized in breast MRI, the role of BPE in contrast-enhanced mammography (CEM) remains uncertain due to inconsistent findings regarding its correlation with breast density and cancer risk. Unlike breast density—standardized through the ACR BI-RADS lexicon—BPE lacks a uniform classification system in CEM, leading to variability in clinical interpretation and research outcomes. To address this gap, we introduce the BPE-CEM Standard Scale (BCSS), a structured four-tiered classification system specifically tailored to the two-dimensional characteristics of CEM, aiming to improve consistency and diagnostic alignment in BPE evaluation. Materials and Methods: In this retrospective single-center study, 213 patients who underwent mammography (MG), ultrasound (US), and contrast-enhanced mammography (CEM) between May 2022 and June 2023 at the “A. Perrino” Hospital in Brindisi were included. Breast density was classified according to ACR BI-RADS (categories A–D). BPE was categorized into four levels: Minimal (< 10% enhancement), Light (10–25%), Moderate (25–50%), and Marked (> 50%). Three radiologists independently assessed BPE in a subset of 50 randomly selected cases to evaluate inter-observer agreement using Cohen’s kappa. Correlations between BPE, breast density, and age were examined through regression analysis. Results: BPE was Minimal in 57% of patients, Light in 31%, Moderate in 10%, and Marked in 2%. A significant positive association was found between higher breast density (BI-RADS C–D) and increased BPE (p < 0.05), whereas lower-density breasts (A–B) were predominantly associated with minimal or light BPE. Regression analysis confirmed a modest but statistically significant association between breast density and BPE (R² = 0.144), while age showed no significant effect. Inter-observer agreement for BPE categorization using the BCSS was excellent (κ = 0.85; 95% CI: 0.78–0.92), supporting its reproducibility. Conclusions: Our findings indicate that breast density is a key determinant of BPE in CEM. The proposed BCSS offers a reproducible, four-level framework for standardized BPE assessment tailored to the imaging characteristics of CEM. By reducing variability in interpretation, the BCSS has the potential to improve diagnostic consistency and facilitate integration of BPE into personalized breast cancer risk models. Further prospective multicenter studies are needed to validate this classification and assess its clinical impact. Full article

The bis-thiourea chiral solvating agent (CSA) BTDA enables the NMR-based determination of absolute configuration in N-3,5-dinitrobenzoyl (DNB) amino acid derivatives without requiring covalent derivatization. A reliable trend of the sense of nonequivalence and absolute configuration is found in both ¹H and ¹³C NMR spectra. A dual-enantiomer approach, using (R,R)- and (S,S)-BTDA, generates diastereomeric complexes with the enantiopure substrate, and distinct spatial arrangements are reflected in consistent and interpretable Δδ values. The observed chemical shift differences correlate reliably with the stereochemistry of the chiral center and are further supported by ROESY (Rotating-frame Overhauser Enhancement SpectroscopY) experiments and binding constants’ measurements, confirming the formation of stereoselective non-covalent complexes. This methodology extends the logic of Mosher’s analysis to solvating agents and remains effective even in samples containing single pure enantiomers of the amino acid derivative. The BTDA-based dual-CSA system thus represents a robust, non-derivatizing strategy for stereochemical assignment by NMR, combining operational simplicity with broad applicability to DNB derivatives of amino acids with free carboxyl function. Full article

The phototherapeutic applications of porphyrin-based nanoscale metal–organic frameworks (nMOFs) are limited by the poor penetration of conventional excitation light sources into biological tissues. Radiodynamic therapy (RDT), which directly excites photosensitizers using X-rays, can overcome the issue of tissue penetration. However, RDT faces the problems of low energy conversion efficiency, requiring a relatively high radiation dose, and the potential to cause damage to normal tissues. Researchers have found that by using some metals with high atomic numbers (high Z) as X-ray scintillators and coordinating them with porphyrin photosensitizers to form MOF materials, the excellent antitumor effect of radiotherapy (RT) and RDT can be achieved under low-dose X-ray irradiation, which can not only effectively avoid the penetration limitations of light excitation methods but also eliminate the defect issues associated with directly using X-rays to excite photosensitizers. This review summarizes the relevant research work in recent years, in which researchers have used metal ions with high Z, such as Hf⁴⁺, Th⁴⁺, Ta⁵⁺, and Bi³⁺, in coordination with carboxyl porphyrins to form MOF materials for combined RT and RDT toward various cancer cells. This review compares the therapeutic effects and advantages of using different high-Z metals and introduces the application of the heavy atom effect. Furthermore, it explores the introduction of a chemodynamic therapy (CDT) mechanism through iron coordination at the porphyrin center, along with optimization strategies such as oxygen delivery using hemoglobin to enhance the efficacy of these MOFs as radiosensitizers. This review also summarizes the potential of these materials in preclinical applications and highlights the current challenges they face. It is expected that the summary and prospects outlined in this review can further promote preclinical biomedical research into and the development of porphyrin-based nMOFs. Full article

As China’s third-largest lead–zinc ore field, the Xicheng Ore Field has significant potential for discovering concealed deposits. In this study, a tectono-geochemical survey was conducted, and 1329 composite samples (comprising 5614 subsamples) were collected from the central part of the field. The dataset was analyzed using staged factor analysis (SFA) and concentration–area (C–A) fractal model. Four geochemical factors were extracted from centered log-ratio (CLR)-transformed data: F_2-1 (Ag–Pb–Sb–Hg), F_2-2 (Mo–Sb–(Zn)), F_2-3 (Au–Bi), and F_2-4 (W–Sn). Known Pb–Zn deposits coincide with positive F_2-1 and negative F_2-2 anomalies, as identified by the C–A fractal model, suggesting these factors are reliable indicators of Pb–Zn mineralization. Five Pb–Zn exploration targets were delineated. Statistical analysis and anomaly maps for F_2-3 and F_2-4 also indicate the potential for Au and W mineralization. Notably, some anomalies from different factors spatially overlap, indicating the possibility of epithermal Pb–Zn mineralization at shallow depths and mesothermal to hyperthermal Au and W mineralization at great depths. Overall, the integration of tectono-geochemistry, targeted and composite sampling, SFA, and C–A fractal modeling proves to be an effective and economical approach for identifying and enhancing ore-related geochemical anomalies. Full article

To accurately monitor the operational state of Internet Data Centers (IDCs) and fulfill integrated management objectives, this paper introduces a bidirectional cross-attention LSTM–Informer with uncertainty-aware multi-task learning framework (BiCA-LI) for time series analysis. The architecture employs dual-branch temporal encoders—long short-term memory (LSTM) and Informer—to extract local transient dynamics and global long-term dependencies, respectively. A bidirectional cross-attention module is subsequently designed to synergistically fuse multi-scale temporal representations. Finally, task-specific regression and classification heads generate predictive outputs and anomaly detection results, while an uncertainty-aware dynamic loss weighting strategy adaptively balances task-specific gradients during training. Experimental results validate BiCA-LI’s superior performance across dual objectives. In regression tasks, it achieves an MAE of 0.086, MSE of 0.014, and RMSE of 0.117. For classification, the model attains 99.5% accuracy, 100% precision, and an AUC score of 0.950, demonstrating substantial improvements over standalone LSTM and Informer baselines. The dual-encoder design, coupled with cross-modal attention fusion and gradient-aware loss optimization, enables robust joint modeling of heterogeneous temporal patterns. This methodology establishes a scalable paradigm for intelligent IDC operations, enabling real-time anomaly mitigation and resource orchestration in energy-intensive infrastructures. Full article

In order to enhance the management and application of fault knowledge within intelligent production lines, thereby increasing the efficiency of fault diagnosis and ensuring the stable and reliable operation of these systems, we propose a fault diagnosis methodology that leverages knowledge graphs. First, we designed an ontology model for fault knowledge by integrating textual features from various components of the production line with expert insights. Second, we employed the ALBERT–BiLSTM–Attention–CRF model to achieve named entity and relationship recognition for faults in intelligent production lines. The introduction of the ALBERT model resulted in a 7.3% improvement in the F₁ score compared to the BiLSTM–CRF model. Additionally, incorporating the attention mechanism in relationship extraction led to a 7.37% increase in the F₁ score. Finally, we utilized the Neo4j graph database to facilitate the storage and visualization of fault knowledge, validating the effectiveness of our proposed method through a case study on fault diagnosis in CNC machining centers. The research findings indicate that this method excels in recognizing textual entities and relationships related to faults in intelligent production lines, effectively leveraging prior knowledge of faults across various components and elucidating their causes. This approach provides maintenance personnel with an intuitive tool for fault diagnosis and decision support, thereby enhancing diagnostic accuracy and efficiency. Full article

Levelers are indispensable additives for achieving void-free, bottom-up superconformal copper filling of microvias. Establishing the molecular-level correlation between leveler structure and performance is therefore essential to the continued advancement of microelectronic copper-plating technology. Herein, nitro blue tetrazolium chloride (NBT) is identified as an efficient leveler for copper microvia superfilling. A multiscale strategy—combining electrochemical measurements, X-ray photoelectron spectroscopy (XPS), density functional theory (DFT) calculations, and molecular dynamics (MD) simulations—is employed to elucidate the action mechanism of NBT and pinpoint its electroactive sites. Electrochemical tests show that NBT markedly suppresses copper deposition and, together with polyethylene glycol (PEG), effectively resists competitive adsorption by bis-(3-sulfopropyl) disulfide (SPS), thereby enhancing the microvia superfilling performance of the PEG–SPS–NBT additive system. DFT results reveal that the nitro groups and tetrazolium rings constitute the primary adsorption centers on the copper surface; the nitro groups additionally strengthen intermolecular interactions between NBT and PEG. MD simulations further confirm that NBT anchors onto the Cu(111) surface predominantly through these NO₂ groups and the tetrazolium ring, while co-adsorbed PEG enhances the overall adsorption strength of NBT. The electroplating experiment demonstrates that NBT can act as an effective leveler for microvia superfilling. Moreover, XPS analyses further confirm the synergistic co-adsorption of NBT and PEG and verify that the NO₂ groups and tetrazolium rings are the dominant adsorption sites of NBT. Collectively, the electroplating, XPS, electrochemical, DFT, and MD findings clarify the structure–activity relationship of NBT and provide rational guidelines for designing next-generation copper-plating levelers. Full article

This study investigates the electromagnetic performance of two carbon fiber monopole antennas integrated into a UAV copter frame, with emphasis on design adaptation, impedance matching, and propagation behavior. A comprehensive experimental campaign was conducted to characterize key parameters such as center frequency, bandwidth, gain, VSWR, and S₁₁. Both antennas exhibited dual-band resonance at approximately 381 MHz and 1.19 GHz, each achieving a 500 MHz bandwidth where VSWR ≤ 2. The modified antenna achieved a minimum reflection coefficient of –14.6 dB and a VSWR of 1.95 at 381.45 MHz, closely aligning with theoretical predictions. Gain deviations between measured (0.15–0.19 dBi) and calculated (0.19 dBi) values remained within 0.04 dB, while received power fluctuations did not exceed 1.3 dB under standard test conditions despite the composite material’s finite conductivity. Free-space link-budget tests at 0.5 m and 2 m of separation revealed received-power deviations of 0.9 dB and 1.3 dB, respectively, corroborating the Friis model. Radiation pattern measurements in both azimuth and elevation planes confirmed good directional behavior, with minor side lobe variations, where Antenna A displayed variations between 270° and 330° in azimuth, while Antenna B remained more uniform. A 90° polarization mismatch led to a 15 dBm signal drop, and environmental obstructions caused losses of 9.4 dB, 12.6 dB, and 18.3 dB, respectively, demonstrating the system’s sensitivity to alignment and surroundings. Additionally, signal strength changes observed in a Two-Ray propagation setup validated the importance of ground reflection effects. Small-scale fading analysis at 5 m LOS indicated a Rician-distributed envelope with mean attenuation of 53.96 dB, σ_dB = 5.57 dB, and a two-sigma interval spanning 42.82 dB to 65.11 dB; the fitted K-factor confirmed the dominance of the LOS component. The findings confirm that carbon fiber UAV frames can serve as effective directional antenna supports, providing proper alignment and tuning. These results support the future integration of lightweight, structure-embedded antennas in UAV systems, with potential benefits in communication efficiency, stealth, and design simplification. Full article

In this paper, the fabrication and testing of an integrated passive device (IPD) structure for X-band FMCW radar based on the fan-out wafer-level packaging (FOWLP) process are discussed. First, a transition line structure is added to the IPD structure to increase the upper impedance limit of the substrate, so as to reduce the process implementation difficulty and development cost. Second, the vertical soldered SubMiniature Push-On Micro (SMPM) interfaces testing method is proposed, reducing the testing difficulty of the dual-port structure with the antenna. Finally, the process fabrication as well as testing of the IPD structure are completed. The dimensions of the fabricated structure are 16.983 × 24.099 × 0.56 ${\mathrm{mm}}^3$. Test results show that, with a center frequency of 8.5 GHz, the actual operational bandwidth of the structure reaches 7.66% (8.095–8.74 GHz), with a maximum isolation of 33.9 dB. The bandwidth with isolation greater than 20 dB is 1.76% (8.455–8.605 GHz). The maximum gain at the center frequency is 2.02 dBi. Additionally, experimental uncertainty analysis is performed on different IPD structures, and the measurement results are basically consistent. These results validate the feasibility of the FOWLP process in the miniaturization of X-band FMCW radar antenna and other passive devices. Full article

This study presents WordMap, an integrated text mining application developed to enhance the efficiency and usability of text analysis over a network. As unstructured text data continues to grow across domains, effective tools for segmentation and topic modeling have become increasingly essential for extracting insightful information. However, most existing solutions depend on multiple disconnected tools, and these often compromise workflow efficiency and user experience. Unlike traditional tools, WordMap combines corpus segmentation, topic modeling, and result visualization into a unified workflow for both Chinese and English languages, thereby reducing workflow fragmentation and lowering the user threshold. To assess usability and user acceptance, this research adopts the Technology Acceptance Model (TAM). WordMap employs PKUSEG and NLTK for bilingual corpus segmentation, utilizes BERTopic for dynamic topic modeling, and integrates interactive visualization to enable intuitive analysis. The PLS-SEM result shows that the perceived ease of use (PEOU) has a significant impact on both perceived usefulness (PU) and user attitude (ATT), while ATT strongly predicts behavioral intention (BI) (β = 0.674, p < 0.001). The results indicate that integrating core text mining processes into a user-centered design significantly boosts user satisfaction and adoption. By combining key processes and empirically validating user perceptions, the proposed framework facilitates the development of efficient and accessible text mining tools. It offers both theoretical and practical insights for future advancement and deployment in the field of text mining. Full article

Background: Despite advances in artificial intelligence (AI) for Diabetic Retinopathy (DR) classification, traditional severity-based approaches often lack interpretability and fail to capture specific lesion-centered characteristics. To address these limitations, we constructed the National Medical Center (NMC) dataset, independently annotated by medical professionals with detailed labels of major DR lesions, including retinal hemorrhages, microaneurysms, and exudates. Methods: This study explores four critical research questions. First, we assess the analytical advantages of lesion-centered labeling compared to traditional severity-based labeling. Second, we investigate the potential complementarity between these labeling approaches through integration experiments. Third, we analyze how various model architectures and classification strategies perform under different labeling schemes. Finally, we evaluate decision-making differences between labeling methods using visualization techniques. We benchmarked the lesion-centered NMC dataset against the severity-based public Asia Pacific Tele-Ophthalmology Society (APTOS) dataset, conducting experiments with EfficientNet—a convolutional neural network architecture—and diverse classification strategies. Results: Our results demonstrate that binary classification effectively identifies severe non-proliferative Diabetic Retinopathy (Severe NPDR) exhibiting complex lesion patterns, while relationship-based learning enhances performance for underrepresented classes. Transfer learning from NMC to APTOS notably improved severity classification, achieving performance gains of 15.2% in mild cases and 66.3% in severe cases through feature fusion using Bidirectional Feature Pyramid Network (BiFPN) and Feature Pyramid Network (FPN). Visualization results confirmed that lesion-centered models focus more precisely on pathological features. Conclusions: Our findings highlight the benefits of integrating lesion-centered and severity-based information to enhance both accuracy and interpretability in DR classification. Future research directions include spatial lesion mapping and the development of clinically grounded learning methodologies. Full article

This paper presents a wideband circularly polarized (CP) substrate-integrated waveguide (SIW) cavity-backed slot antenna array arranged in a 2 × 2 configuration with differential feeding structures. The design features arc-shaped microstrips within the SIW cavity to excite the ${\mathrm{TE}}_{011}^x$/${\mathrm{TE}}_{101}^y$ and ${\mathrm{TE}}_{211}^y$/${\mathrm{TE}}_{121}^x$ modes. By overlapping the center frequencies of the two modes, wideband CP radiation is achieved. The introduction of four modified ring couplers composes a simple but efficient differential feeding network, eliminating the need for balanced resistors like baluns, making it more suitable for millimeter wave or even higher frequency applications. Experimental results show that the antenna array achieves a −10 dB impedance bandwidth of 32.6% (from 17.28 to 24.00 GHz), a 3 dB axial ratio (AR) bandwidth of 13.8% (from 17.05 to 19.57 GHz), a 3 dB gain bandwidth of 41.8% (from 15.39 to 23.51 GHz) and a peak gain of 10.6 dBi, with results closely matching simulation data. This study enhances the development of differential CP SIW cavity-backed slot antenna arrays, offering a potential solution for creating compact integrated front-end circuits in the millimeter wave or Terahertz frequency range. Full article

This study of the BaSO₄-Bi phosphor has revealed that the accumulated energy after external optical excitation exhibits specific characteristics. During irradiation with photon energy exceeding the bandgap, in addition to the intrinsic ultraviolet emission of the Bi³⁺ ion, several recombination emissions and emission from the Bi²⁺ ion are observed. At 80 K, the recombination luminescence states and Bi²⁺ ion emission form combined electronic states. Upon heating of the BaSO₄-Bi phosphor, these combined electronic states decay into recombination emissions at 2.34 eV, 2.4 eV, 3.1 eV, and 2.7 eV, as well as Bi²⁺ ion emission at 1.97 eV. It is assumed that the 2.34 eV, 2.4 eV, and 3.1 eV emissions are associated with the recombination of electrons released from ionized ${SO}_4^{3-}$ electron trapping centers with nonequivalently localized holes in the host lattice. The 2.7 eV emission is attributed to the decay of an exciton formed by electron–hole recombination near a Bi³⁺ ion. Full article

A dysprosium-based metal–organic framework (MOF), namely [DyLH₂O]_n (1) (H₃L = 4-((bis(carboxymethyl) amino)methyl)benzoic acid), was successfully synthesized via the hydrothermal method. According to the structural characterization, metal centers in this complex are linked by four bridges (two oxygens and two carboxylic groups), leading to Dy₂ units. On further connection by single carboxylic groups, the dimeric units extend to form a two-dimensional layer with a 4⁴ topological structure. Finally, the 2D layers were assembled into a 3D framework by the L⁻³ anions. A thermogravimetric test shows that [DyLH₂O]_n can maintain high thermal stability after losing water, until the temperature reaches 426 °C. Magnetic studies on 1 reveal antiferromagnetic exchange interactions of Dy³⁺…Dy³⁺ at low temperatures. Additionally, frequency-dependent out-of-phase signals were observed in alternating current (ac) magnetic susceptibility measurements for 1, indicating that it has slow magnetic relaxation features. Full article

Recently, the emerging class of hydroxamate-based metal–organic frameworks (MOFs) has demonstrated significant structural diversity and chemical robustness, both essential for potential applications. Combining the favorable hard–hard Bi-O interactions and chelating chemistry of hydroxamate groups, a rigid and symmetrical three-dimensional bismuth-hydroxamate metal–organic framework was successfully prepared via solvothermal synthesis and structurally elucidated via X-ray crystallography. The MOF, namely SUM-91 (SUM = Sichuan University Materials), features one-dimensional Bi-oxo secondary building blocks (SBUs), which are bridged by chelating 1,4-benzenedihydroxamate linkers. With the demonstrated permanent porosity and molecular sieving effect (CO₂ vs. N₂), SUM-91 was also found to be stable under harsh chemical conditions (aqueous solutions with pH = 2–12 and various organic solvents). As the structural robustness of SUM-91 could be attributed to the finetuning of the coordinative sphere of Bi centers, this work shed light on the further development of (ultra-)microporous materials with high stability and selective adsorption properties. Full article