Advancing Open Science

Current microgrid research primarily focuses on radial topologies and their control strategies, while exploration of the time-domain dynamic behavior of closed-loop controlled microgrids remains relatively insufficient. This research gap makes it difficult to directly observe and deeply analyze the evolution mechanisms of critical phenomena, such as oscillations and instability, when they occur. Therefore, conducting time-domain analysis on closed-loop structures is crucial for revealing system instability mechanisms and ensuring their safe and stable operation. This paper establishes a state-space model for a closed-loop microgrid structure composed of multiple parallel inverters and conducts time-domain stability analysis under grid-connected operation. First, a mathematical model of the closed-loop microgrid system is constructed using state-space equations. Subsequently, time-domain analysis of small-signal stability is performed on the model. By varying key parameters such as the droop coefficient, the influence patterns on system stability are investigated. The results indicate that the droop control coefficient and LC filter parameters exert the most significant impact on system dynamic characteristics. Simulation experiments validate the correctness and effectiveness of the theoretical model. Finally, the time-domain characteristics of this model were further analyzed and validated through simulations. Results demonstrate that the system maintains robust stability under disturbances even in grid-connected mode.

Background: Gold nanoparticles (GNPs) are widely used in nanomedicine as drug carriers, including in targeted radionuclide therapy where therapeutic radionuclides are bound to GNPs. Quantitative assessment of their biodistribution is essential. X-ray fluorescence imaging (XFI) is well suited for detecting high-Z elements, but its quantitative accuracy is compromised by strong attenuation effects, particularly in L-shell XFI where low-energy fluorescence (~10 to 12 keV) is heavily absorbed in tissue. Methods: We developed a computed tomography (CT)-guided attenuation correction algorithm for L-shell XFI. The method generates energy-dependent attenuation maps from co-registered CT data and performs voxel-wise corrections along both excitation and emission paths. The approach was tested on an ex vivo murine tumor sample resected three hours after intratumoral injection of 34.7 μg PEG-modified GNPs. Results: Application of the CT-guided correction substantially improved the relative accuracy of L-shell XFI reconstructions compared to uncorrected data. The corrected distribution maps showed consistent mass recovery across different measurement geometries, demonstrating that the algorithm compensates for the theoretically expected attenuation due to heterogeneous biological tissue. Conclusions: This study provides a proof-of-principle that CT-based attenuation correction enables more reliable and quantitative L-shell XFI of GNPs in biological samples. The approach represents a promising step toward accurate nanoparticle biodistribution assessment in biomedical research, including preclinical studies in targeted radionuclide therapy.

The strengthened role of agribusinesses as innovators depends on improvements in their innovation performance, yet how to achieve this remains unresolved. Grounded in the technology–organization–environment (TOE) framework and drawing on 2020–2022 panel data from 73 Chinese agribusinesses, we apply panel–QCA to examine how R&D personnel, managerial innovativeness, and digital technology adoption interact to generate superior innovation outcomes. The results reveal that no single technological, organizational, or environmental factor constitutes a necessary condition; instead, high innovation performance results from specific configurations. Three dominant pathways are identified: organization-driven, technology–organization synergistic, and organization–technology synergistic. In particular, organizational factors serve as core conditions across all configurations, offering stage-appropriate routes for firms at different development phases. Over time, all three configurations decline under external shocks. Furthermore, heterogeneity across firms underscores the need for tailored, dynamic strategies. Therefore, agribusinesses should “configure by context,” continuously monitor shifting configurational elements, and select adaptive pathways to sustain sustainable innovation performance amid environmental volatility.

Objective: Ongoing debates focus on the role of human leukocyte antigen (HLA) class II expression in shaping clinical phenotypes of chronic inflammatory airway diseases. This study seeks to clarify the impact of class II HLA on chronic obstructive pulmonary disease (COPD) and asthma–COPD overlap (ACO). Method: The expression levels of HLA-DQ/DR in blood immune cells were analyzed in 116 participants: 41 with COPD, 37 with ACO, 20 with pure asthma, and 18 healthy subjects (HS). Results: In the COPD group, HLA-DR protein expression levels were significantly elevated on blood M2a monocytes (7695 ± 3743 vs. 5391 ± 3153 MFI, p = 0.026), helper T cells (2551 ± 956 vs. 1836 ± 531 MFI, adjusted p = 0.018), cytotoxic T cells (1591 ± 531 vs. 1360 ± 477 MFI, adjusted p = 0.036), and B cells (20,667 ± 7985 vs. 15,694 ± 2003 MFI, adjusted p = 0.031) compared to the HS group. Conversely, no significant changes were observed in the asthma group. In ACO patients, helper T cells showed increased HLA-DR protein expression (2416 ± 914 MFI; adjusted p = 0.016) compared with the HS group. Higher levels of HLA-DR expression correlated with reduced pulmonary function, frequent exacerbations, and more severe symptoms. Following one year of treatment in 14 COPD and 16 ACO patients, HLA-DR protein expression on blood helper T cells, cytotoxic T cells, M2a monocytes, and neutrophils significantly declined (all p < 0.05). In vitro experiments demonstrated that exposure of M2- or M1-polarized THP-1 cells to a stimulus mix containing cigarette smoke extract, house dust mite antigens, and lipopolysaccharide led to up-regulation of HLA-DR expression. This response was linked to increased apoptosis and reduced production of reactive oxygen species. Conclusions: Up-regulation of HLA-DR in COPD and ACO patients may represent a novel biomarker for assessing disease severity and treatment response. Additionally, it could serve as a useful tool to distinguish COPD and ACO from asthma.

A receipt information extraction task requires both textual and spatial analyses. Early receipt analysis systems primarily relied on template matching to extract data from spatially structured documents. However, these methods lack generalizability across various document layouts and require defining the specific spatial characteristics of unseen document sources. The advent of convolutional and recurrent neural networks has led to models that generalize better over unseen document layouts, and more recently, multi-modal transformer-based models, which consider a combination of text, visual, and layout inputs, have led to an even more significant boost in document-understanding capabilities. This work focuses on the joint use of a neural multi-modal transformer and a rule-based model and studies whether this combination achieves higher performance levels than the transformer on its own. A comprehensively annotated dataset, comprising real-world and synthetic receipts, was specifically developed for this study. The open source optical character recognition model DocTR was used to textually scan receipts and, together with an image, provided input to the classifier model. The open-source pre-trained LayoutLMv3 transformer-based model was augmented with a classifier model head, which was trained for classifying textual data into 12 predefined labels, such as date, price, and shop name. The methods implemented in the rule-based model were manually designed and consisted of four types: pattern-matching rules based on regular expressions and logic, database search-based methods for named entities, spatial pattern discovery guided by statistical metrics, and error correcting mechanisms based on confidence scores and local distance metrics. Following hyperparameter tuning of the classifier head and the integration of a rule-based model, the system achieved an overall F1 score of 0.98 in classifying textual data, including line items, from receipts.

Percutaneous coronary intervention (PCI) has evolved significantly over the past two decades, yet challenges in achieving optimal stent deployment and long-term outcomes persist, particularly in complex coronary anatomy. Intravascular imaging (IVI) modalities such as intravascular ultrasound (IVUS), optical coherence tomography (OCT), and near-infrared spectroscopy (NIRS) have transformed the precision of PCI by providing detailed cross-sectional visualization of vessel architecture, plaque morphology, and stent apposition. Compared to angiography-guided PCI, imaging-guided PCI enables more accurate lesion assessment, appropriate stent sizing, and detection of suboptimal results including under-expansion, malapposition, and edge dissections, factors strongly linked to restenosis and stent thrombosis. Large-scale randomized trials (e.g., ULTIMATE, ILUMIEN) and meta-analyses have demonstrated that imaging-guided PCI reduces major adverse cardiovascular events (MACE) and improves long-term stent patency, particularly in left main, bifurcation, and calcified lesions. Despite these benefits, adoption remains variable due to cost, procedural complexity, and training gaps. Emerging advances, including artificial intelligence-enhanced imaging, hybrid devices, and fusion of imaging with physiologic assessments, promise to integrate imaging more seamlessly into routine practice. This review summarizes current evidence, practical applications, and future directions of IVI-guided PCI, underscoring its growing role in contemporary interventional cardiology and its potential to personalize and optimize coronary revascularization strategies.

Microwave heating has a good number of advantages in the synthesis of inorganic compounds when opportunely exploited. A deep knowledge of the interaction of the electromagnetic waves and matter is necessary to optimize irradiation of the reactor vessel so as to obtain homogeneous heating for homogeneous nucleation and growth of particles, localized heating of starting self-sustained high-temperature synthesis, and generation of a superfast heating and cooling profile to obtain metastable crystals. Case studies of pure oxides, mixed oxides, composites, phosphates, zeolites, and high-entropy alloys are discussed in the international frame of the academic and industrial research covering the last 20 years of microwave chemistry where Italian researchers covered a relevant role.

Nonalcoholic fatty liver disease (NAFLD) is a major public health concern with a global prevalence of approximately 32%. This study examined the association between the “weekend warrior”, other leisure-time physical activity patterns, and NAFLD in Korean adults. We included 44,264 individuals from the Korea National Health and Nutrition Examination Survey (2014–2023). Physical activity was measured using the Global Physical Activity Questionnaire (GPAQ), a self-reported instrument, and physical activity patterns were classified as inactive, weekend warrior (≥150 min/week of moderate-to-vigorous physical activity [MVPA] performed in 1–2 days), and regularly active. NAFLD was identified using the Hepatic Steatosis Index with a cutoff of >36. Weighted logistic regression was used to examine the association between physical activity patterns and NAFLD. The prevalence of NAFLD was 24%. After adjustment for sociodemographic and metabolic factors, both the weekend warrior (odds ratio [OR] = 0.80, 95% confidence interval [CI]: 0.64–0.99) and regularly active (OR = 0.83, 95% CI: 0.77–0.89) groups had significantly lower odds of NAFLD compared to the inactive group. When stratified by total MVPA level, both the weekend warrior and regularly active patterns with >300 min/week of MVPA showed even lower odds of NAFLD, compared to those with 150–300 min/week of MVPA. Both regularly active and weekend warrior patterns were associated with a lower prevalence of NAFLD, suggesting that the weekend warrior pattern may represent a feasible behavioral pattern associated with lower NAFLD prevalence for individuals with time constraints.