Advancing Open Science

To address the challenges of insufficient robustness and limited feature extraction in photovoltaic module image segmentation under complex scenarios, we propose a high-precision PV module segmentation model (Pv-UNet) that integrates Transformer and improved U-Net architecture. The model introduces a MultiScale Transformer in the encoding path to achieve cross-scale feature correlation and semantic enhancement, combines residual structure with dynamic channel adaptation mechanism in the DoubleConv module to improve feature transfer stability, and incorporates an Attention Gate module in the decoding path to suppress complex background interference. Experimental data were obtained from UAV visible light images of a photovoltaic power station in Yuezhe Town, Qiubei County, Yunnan Province. Compared with U-Net, BatchNorm-UNet, and Seg-UNet, Pv-UNet achieved significant improvements in IoU, Dice, and Precision metrics to 97.69%, 93.88%, and 97.99% respectively, while reducing the Loss value to 0.0393. The results demonstrate that our method offers notable advantages in both accuracy and robustness for PV module segmentation, providing technical support for automated inspection and intelligent monitoring of photovoltaic power stations.

Quantitative analyses in drug-delivery research are frequently distributed across multiple tools, which increases manual handling and the risk of transcription errors. NanoEDW 1.0 is an open source Python application that integrates calibration-curve generation, encapsulation-efficiency (EE%) calculation, and release kinetics modeling in a single, streamlined workflow. This study aims to validate the performance of NanoEDW 1.0 by benchmarking it against spreadsheet/OriginLab^® OriginPro 2025 analyses on experimental datasets from polymeric nanocarrier systems commonly used in drug encapsulation. The software performs linear regression to convert absorbance into concentration, computes EE% from raw experimental values, and fits drug-release profiles to classical models (including zero/first-order, Higuchi, Korsmeyer–Peppas, Weibull, and Modified Gompertz) using non-linear least squares with standard goodness-of-fit metrics (R², RMSE). Results show close agreement with reference workflows for calibration parameters and EE%, as well as statistically comparable release-model fits, while reducing manual steps and analysis time. In conclusion, the validation confirms that NanoEDW 1.0 can streamline routine analyses and enhance reproducibility and accessibility in nanopharmaceutical research; source code and example datasets are provided to foster adoption.

Artificial intelligence (AI) technology has brought unprecedented impact and opportunities for the sustainable development of family firms. This paper examines the impact of AI on innovation investment in family firms using a sample of Chinese A-share listed family firms from 2007 to 2024. The results show that AI significantly promotes innovation investment in family firms to achieve sustainable development. Mechanism analysis shows that AI enhances both the willingness and capability of family firms to invest in innovation by improving their risk-taking levels and resource allocation efficiency, thereby promoting innovation investment. Heterogeneity analysis shows that the promotion effect of AI on innovation investment of family firms is more significant in smaller family firms, those directly founded by families, those with more family involvement in management, and those prior to intergenerational succession. Furthermore, the study finds that AI significantly improves the innovation performance of family firms. Our findings provide important theoretical and practical guidance for enterprises seeking to leverage AI to catalyze innovation investment and thereby achieve long-term value growth and sustainable development.

Background/Objectives: Frailty represents a critical aging-related condition, but evidence on how different sources of vitamin C relate to frailty risk remains limited. Thus, this study aimed to examine the relationship between frailty risk and sources of vitamin C intake (dietary, including fruit and vegetable (FV) vs. supplemental) among Korean adults. Method: We analyzed data from 9478 adults in the Korea National Health and Nutrition Examination Survey (KNHANES 2018–2019). Frailty was assessed using a modified Fried phenotype. A multivariable logistic regression model was used to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) for frailty according to vitamin C intake source. Results: More than 60% of participants had inadequate FV intake. Significant associations were observed primarily in women. Increased FV intake (OR = 0.44, 95% CI = 0.264–0.731, comparing the highest intake group (fourth quartile, Q4) vs. the lowest intake group (first quartile, Q1)) for dietary vitamin C intake (OR = 0.60, 95% CI = 0.393–0.914, Q4 vs. Q1) and vitamin C intake from FV (OR = 0.54, 95% CI = 0.348–0.851, Q4 vs. Q1), was significantly associated with a lower risk of frailty. Women with inadequate FV intake had a higher risk of frailty (OR = 2.06, 95% CI = 1.34–3.16) compared to those with adequate intake, regardless of vitamin C supplement use. In contrast, vitamin C supplementation was not significantly associated with frailty risk in either men or women. Conclusion: A higher intake of FV and dietary vitamin C, but not supplemental vitamin C, was associated with a lower risk of frailty, particularly among women. These findings suggest that improving overall diet quality through increased FV consumption may be more effective for frailty prevention than relying on single-nutrient supplementation.

The pervasive presence of nanoplastics (NPs) in the soil environment has been widely documented. However, the mechanisms governing their transport through soil remain poorly understood. This study investigated the migration and vertical distribution of NPs under simulated rainfall, examining the effects of NP properties (concentration, polymer type, aging) and rainfall conditions (duration, pH). The results demonstrated that rainfall facilitated the entry and retention of NPs in soil, with long-term rainfall promoting gradual migration to deeper layers or groundwater. NP mobility was inversely related to their contamination levels. Lower concentrations enhanced downward transport, while higher concentrations led to preferential retention in the topsoil. Due to its hydrophilicity, polyamide (PA) exhibits greater mobility in soil than hydrophobic polystyrene (PS). Both UV aging and acidic rainfall conditions inhibited the migration of NPs, which increased their long-term retention in soil, thereby elevating ecological risk. These results highlight the need for increased attention to the risk of groundwater contamination posed by hydrophilic NPs following long-term rainfall, as well as the threat posed by hydrophobic NPs, particularly after aging and under acidic rainfall conditions, to soil organisms and food safety. Our findings provide critical insights for assessing NP risks in soil environments.

Background/Objectives: Climate change is a major global issue affecting all facets of society, including dentistry. In response, the idea of green dentistry has developed, prioritising the reduction in environmental damage and the protection of patient health. This scoping review seeks to assess the level of awareness, understanding and practices of oral health professionals concerning the proper management of biomed. Methods: Searches were carried out in the Medline/PubMed, Scopus, Web of Science, Embase, and Google Scholar databases, analysing studies published between 2020 and 2025. Out of a total of 822 articles, 27 met the eligibility criteria. Results: In most of these studies, the respondents’ level of knowledge was found to be unsatisfactory or average, and only 17% of the studies reported respondents having a positive attitude towards adherence to sustainability principles. Although many professionals stated they were aware that dental waste could negatively impact the environment and human health if not properly managed, some still failed to provide correct answers to all the questions. Conclusions: The synthesis results indicated that oral health professionals have significant gaps in certain aspects of biomedical waste management, highlighting the need for proper training and to supplement the undergraduate and postgraduate curricula with courses on this topic.

This study reports the green synthesis of copper oxide nanoparticles (CuO NPs) using Oxystelma esculentum extract as a reducing and stabilizing agent. The state-of-the-art analysis confirmed their spherical morphology, with an average particle size ranging from 20 to 25 nm, while XRD indicated a crystalline structure consistent with the standard JCPDS card. The photocatalytic degradation of norfloxacin (NOR) was optimized using Response Surface Methodology (RSM), which identified the optimal conditions as a reaction time = 47.51 min, CuO-NPs dose = 48.46 mg, NOR dose = 35.90 ppm, and pH = 5.23. Under these optimized conditions, the CuO NPs achieved an initial degradation efficiency of 90%. In addition to photocatalytic degradation, the hydrogen (H₂) evolution performance of the CuO NPs was evaluated, yielding a H₂ production rate of 19.52 mmol g⁻¹ h⁻¹ under visible light. Moreover, the antimicrobial activity of the CuO NPs was assessed, showing significant antibacterial effects with inhibition zones of 8 mm and 9 mm against Klebsiella and Bacillus species. The CuO NPs also exhibited potent anticancer activity with an IC₅₀ value of 15.3 ± 1.40 μM against the HeLa cell line and notable antifungal activity with inhibition rates ranging from 70% to 90% against various fungal species.

Background/Objectives: Endoscopic retrograde cholangiopancreatography (ERCP) with biliary stent placement is a mainstay of current management for biliary obstruction, with stent occlusion being the most common and severe complication. The mechanism of stent occlusion is well known; however, factors affecting individual stent patency are still controversial. The objective of this study was to determine the duration and factors affecting plastic biliary stent patency. Methods: We conducted a retrospective analysis of the consecutive procedures of endoscopic retrograde cholangiopancreatography (ERCP) and biliary stent placement in a single tertiary center during the period of 2010–2019. The primary outcome of the study was the time of stent patency. Secondary outcomes were the development of cholangitis upon re-stenting and whether subsequent re-stenting was emergent. Re-stenting was considered emergent if it happened before the planned elective re-stenting date, irrespective of indication (development of cholangitis, rising jaundice, suspected dislodgement, etc.). Results: Between 2010 and 2019, a total of 5462 ERCP procedures were performed, with 2659 resulting in plastic biliary stent placement. On average, the plastic biliary stent was patent for 63 (25, 96) days with significant differences between the indications for ERCP groups. The strongest risk factors for the development of cholangitis upon re-stenting was cholangitis during index ERCP (HR = 1.83; 95% CI: 1.48–2.27; p < 0.001), intrabiliary malignancy being the indication for stenting (HR = 1.34; 95% CI: 1.12–1.60; p < 0.001) and increasing number of stents being placed (HR = 1.73; 95% CI: 1.27–2.36; p < 0.001). Conclusions: Patients with an underlying malignancy, history of cholangitis, and multiple biliary stents are at an increased risk for stent occlusion and cholangitis, warranting a tailored stent exchange interval to prevent complications.