Advancing Open Science

Amid growing international pressure for carbon neutrality, the maritime industry is facing mounting institutional demands for environmental innovation. Drawing on protection motivation theory, this study surveyed 499 employees from 1519 shipping service firms to examine how coercive, mimetic, and normative pressures shape green innovative work behavior. By extending protection motivation theory to a highly regulated maritime context, this study demonstrates that institutional pressures do not directly drive green innovation; instead, they enhance employees’ self-protective motivation, which subsequently fosters eco-innovation. Moreover, these relationships are stronger when firms perceive greater climate risks or receive government subsidies, indicating that contextual conditions amplify the translation of motivation into behavior. Overall, the findings reveal how macro-level institutional forces shape the sustainable transition of maritime services through employee psychology, offering governance-relevant insights for policymakers and firms seeking to promote green innovation.

Since the dawn of civilization, humanity has looked to the sky, seeking to expand knowledge beyond Earth’s boundaries. The last eight decades have witnessed remarkable progress in space exploration, paving the way for increasingly longer space journeys and the establishment of human settlements on the Moon and Mars. These achievements have been made possible by advances in multiple scientific disciplines, including the rise of space medicine, astropharmacy, astrobiology, and astrobotany, each addressing how biological and technological systems adapt to extraterrestrial environments. Nevertheless, the space environment remains profoundly inhospitable to human life, making the protection of health and the assurance of long-term sustainability a key strategic goal in space exploration programs. Within this multidisciplinary framework, the potential role of medicinal plants remains underexplored. Historically central to healthcare, medicinal plants provide a vast repertoire of bioactive compounds and molecular scaffolds, many of which have inspired modern drugs. This review explores how medicinal plants could contribute to human well-being beyond Earth—not only as sources of therapeutic agents to mitigate spaceflight-induced ailments but also as biomanufacturing platforms for on-demand production of pharmaceuticals. Ultimately, medicinal plants could continue to play a pivotal role in supporting human health, also in space, but it poses new challenges and requires further scientific and technological advances.

Person re-identification (Re-ID) using infrared surveillance cameras has attracted increasing attention due to its robustness under low-light conditions. However, infrared images generally suffer from a low spatial resolution, which degrades Re-ID performance. To address this issue, this study proposes a part attention and contrastive loss-based super-resolution reconstruction network (PCSR-Net) and a unified infrared-only Re-ID framework. The proposed PCSR-Net consists of a correlation-based super-resolution reconstruction network (CoSR-Net), a feature extractor for Re-ID, and a part attention mechanism that estimates the importance of different body regions. In addition, contrastive loss and part-aware reconstruction loss are incorporated to guide the super-resolution process toward identity-discriminative representations. Experimental results on DBPerson-Recog-DB1 and SYSU-MM01 demonstrate that the proposed method outperforms state-of-the-art approaches in terms of the equal error rate (EER), mean average precision (mAP), and rank-1 accuracy, validating its effectiveness for infrared-based person Re-ID.

Introduction: Reliable identification regarding interfascial spaces proves essential to achieve successful nerve block analgesia; however, ultrasound guided approaches are recognized as challenging, particularly in obese or pediatric patients. In prior cadaveric and clinical investigations, multiple approaches were evaluated to identify methods for measuring injection pressures as a function of needle position relative to fascia. Our previous study proposed simpler method of finding interfascial spaces with the needle tip. In this study, it was examined whether needle tip design influences injection pressures during regional anesthesia procedures, via an ex vivo pig specimen setup. Methods: A bespoke apparatus for tracking injection pressure was deployed to enable continuous measurement of intraluminal pressure generated while delivering saline throughout ultrasound guided peripheral nerve block needles conducted within pig thigh specimens. Delivery was performed using an infusion pump. Three types of needles of the same manufacturer (Pajunk) and same diameter (22G) but with different tips (Facet, Facet S and Sprotte) were used to measure injection pressures during penetration through tissues until interfascial plane hydrodissection was created. Statistical analyses were performed to compare pressure levels, variability, and temporal pressure trends. Results: Ninety ultrasound guided injections in porcine thigh tissue were analyzed, with thirty procedures per needle type. Injection pressure differed significantly between intramuscular, fascial puncture, and interfascial phases, showing a distinct puncture peak (p ≤ 3.44 × 10⁻¹⁴). Needle geometry significantly affected pressures across all phases (Kruskal–Wallis intramuscular p = 2.0 × 10⁻⁶, puncture p = 7.52 × 10⁻⁸, interfascial p = 9.2 × 10⁻⁵), with large pairwise effects (Hedges g up to 1.51). The classical tip produced the highest intramuscular and higher interfascial pressures, the sharp tip required the lowest puncture pressure, and the lateral tip yielded the lowest intramuscular and interfascial pressures. Conclusions: Needle tip geometry substantially influences pressure dynamics throughout the injection process, with the classical design associated with the highest fascia-penetration injection pressures and the sharp needle exhibiting the lowest, while the lateral design associated with lowest intramuscular-penetration and interfascial pressures.

Background/Objectives: Sacral neuromodulation (SNM) is an established therapy for refractory overactive bladder and non-obstructive urinary retention. With the rapid adoption of large language models (LLMs) such as ChatGPT, their accuracy in procedure-specific domains requires evaluation. The aim of this study was to compare the accuracy, completeness, and reproducibility of ChatGPT versions 3.5, 4.0, and 5.0 in answering patient- and guideline-based questions on SNM. Methods: Twenty questions were developed from international guidelines, device information, and common patient inquiries, covering five domains (mechanism, technique, outcomes, complications, postoperative management), two source types (frequently asked question [FAQs] vs. guideline), and three difficulty levels. These thematic domains were derived from core clinical counseling areas routinely addressed in SNM evaluation and follow-up. Each was submitted to ChatGPT versions 3.5, 4.0, and 5.0. Responses were rated independently by two urologists on a four-point accuracy scale. Combined success (Grades 1–2) and accuracy trends were compared across versions. Chi-square tests were used to assess differences across versions, Cramer’s V to measure effect size, and Cohen’s kappa to evaluate reproducibility. Results: Accuracy improved progressively across versions. Combined success rates rose from 70% in version 3.5 to 85% in 4.0 and 90% in 5.0 (p = 0.031, Cramer’s V = 0.29). Highest accuracy was observed in mechanism and procedural technique, while complication- and guideline-based questions showed lower performance. FAQ and straightforward questions were answered more reliably than guideline-based or complex ones. Reproducibility was excellent across all versions (κ = 0.81–0.91). Conclusions: ChatGPT 4.0 and 5.0 show strong potential as adjunctive tools for patient education in SNM, particularly for FAQs and procedural explanations. However, because persistent limitations were observed in guideline interpretation and complication management, clinician oversight remains essential, and these models should not be regarded as substitutes for professional clinical judgment.

Hepatocellular carcinoma (HCC) is the most common primary liver cancer and a major cause of cancer mortality worldwide. Because HCC usually arises in cirrhotic livers, prognosis is shaped by the dual threats of tumor progression and hepatic decompensation, requiring treatment decisions that balance anticancer efficacy with preservation of liver function, portal hypertension control, and quality of life. In recent years, management has shifted from a predominantly locoregional approach to an integrated continuum that spans curative resection, ablation, and transplantation; refined transarterial and radiotherapy techniques; and modern systemic therapy dominated by immunotherapy-based combinations. These advances have improved response rates, enabled downstaging and conversion in selected patients, and expanded opportunities for sequential and multimodal treatment. However, challenges persist, including therapeutic decision-making in patients with Child–Pugh B liver function, lack of robust predictive biomarkers, and resistance after initial response. Emerging tools—liquid biopsy, radiomics, AI-assisted imaging, and microbiome modulation—may support future precision strategies and optimized treatment allocation. In this review, we summarize current evidence guiding staging and therapy selection, outline practical considerations across curative, locoregional, and systemic modalities, and discuss evolving biomarkers and next-generation immunotherapy as key steps toward more personalized, durable, and equitable global HCC care.

Maritime target detection under complex adverse weather conditions (e.g., fog, rain, and low light) is crucial for Unmanned Surface Vehicle (USV) navigation. However, achieving high detection accuracy and efficiency remains challenging due to coupled environmental interference and limited computing resources. In this paper, we propose W-MTD, a task-specific distillation framework designed for weather-robust and lightweight maritime target detection based on knowledge distillation. Building upon the Fine-grained Distribution Refinement (D-FINE) detection model, this method constructs a dual-path knowledge distillation framework tailored for maritime scenes. Through the synergistic optimization of feature similarity constraints and decoupled distillation, it facilitates multi-level knowledge transfer from a teacher model to a lightweight student model, mitigating feature degradation caused by model compression. A multi-scenario augmentation strategy is designed to balance convergence across different weather conditions. Experiments show that W-MTD’s student model improves detection accuracy by 7.0–13.9% under three adverse weather conditionscompared to the baseline teacher model trained solely on clear weather data while maintaining comparable clear-weather performance. With only 4 M parameters and 7 GFLOPs, the student model demonstrates favorable performance and efficiency compared to other real-time detectors, indicating its potential suitability for USV deployment.

Advanced Oxidation Processes (AOPs) are pivotal technologies for the effective degradation of a wide variety of organic and inorganic pollutants in water and wastewater treatment. This bibliometric analysis evaluates 481 publications from the Scopus database, covering the period from 2010 to November 2025, to explore research trends and developments in the field. The findings reveal a substantial increase in research output, with an average annual growth rate of 22.7%. China leads in publication count with 192 documents, followed closely by the United States with 64 publications, demonstrating their substantial contributions to AOP research. Prominent institutions include Tongji University and Università Degli Studi Di Salerno, emphasizing the global collaboration among 2335 authors from 158 institutions across 74 countries. Key themes emerging from the analysis include high oxidative efficiency of AOPs, their hybrid applications with biological and adsorption methods, and their adaptability in treating persistent pollutants and emerging contaminants. However, challenges such as high operational costs, hazardous byproduct formation, and reliance on specific water matrix conditions remain significant obstacles. Funding sources, notably the National Natural Science Foundation of China, play a crucial role, supporting numerous studies, while journals like “Water Research,” “Chemical Engineering Journal,” and “Science of the Total Environment” are identified as primary venues for disseminating impactful research. Overall, this study underscores the need for innovative strategies and interdisciplinary collaboration to enhance the efficacy and application of AOP technologies in addressing the growing challenges in water treatment and environmental sustainability.