Search Results (3,866)

Decarbonising aquaculture support vessels is pivotal to reducing greenhouse gas (GHG) emissions across both the aquaculture and maritime sectors. This study evaluates the technical and economic feasibility of deploying hydrogen as a marine fuel for a 14.95 m net cleaning vessel (NCV) operating in Tasmania, Australia. The analysis retains the vessel’s original layout and subdivision to enable a like-for-like comparison between conventional diesel and hydrogen-based systems. Two options are evaluated: (i) replacing both the main propulsion engines and auxiliary generator sets with hydrogen-based systems—either proton exchange membrane fuel cells (PEMFCs) or internal combustion engines (ICEs); and (ii) replacing only the diesel generator sets with hydrogen power systems. The assessment covers system sizing, onboard hydrogen storage integration, operational constraints, lifecycle cost, and GHG abatement. Option (i) is constrained by the sizes and weights of PEMFC systems and hydrogen-fuelled ICEs, rendering full conversion unfeasible within current spatial and technological limits. Option (ii) is technically feasible: sixteen 700 bar cylinders (131.2 kg H₂ total) meet one day of onboard power demand for net-cleaning operations, with bunkering via swap-and-go skids at the berth. The annualised total cost of ownership for the PEMFC systems is 1.98 times that of diesel generator sets, while enabling annual CO₂ reductions of 433 t. The findings provide a practical decarbonisation pathway for small- to medium-sized service vessels in niche maritime sectors such as aquaculture, while clarifying near-term trade-offs between cost and emissions. Full article

Background/Objectives: Lifestyle-related diseases such as obesity, diabetes, hypertension, metabolic syndrome, non-alcoholic fatty liver disease (NAFLD), and osteoarthritis disproportionately affect women due to hormonal, metabolic, and socio-cultural factors. Emerging evidence suggests that combining structured exercise with nano-curcumin, a bioavailable phytochemical formulation with potent antioxidant and anti-inflammatory properties, may provide synergistic benefits. This scoping review systematically synthesizes available evidence on the combined effects of nano-curcumin supplementation and exercise interventions on health outcomes in women with lifestyle-related diseases. Methods: Following the Joanna Briggs Institute methodology and the PRISMA-ScR framework, a comprehensive database search was conducted in March 2025 and updated in June 2025. Records were retrieved from Scopus (n = 30), Web of Science (n = 22), PubMed (n = 18), and other sources (n = 71), yielding a total of 141 studies. After screening and deduplication, eight studies met the inclusion criteria and were included in this review. All the studies were conducted in Iran with small sample sizes (12–53 participants) and short intervention durations (6–16 weeks). Therefore, the current evidence is geographically and demographically limited. Results: Across the included trials, the combined interventions produced additive or synergistic improvements in oxidative stress markers, inflammatory cytokines, lipid and glucose metabolism, cardiovascular function, pulmonary capacity, muscle fitness, and psychological outcomes (e.g., depression). When paired with nano-curcumin supplementation at different concentrations, high-intensity interval training, aerobic exercise, Pilates, and resistance training consistently outperformed exercise or supplementation alone in modulating antioxidant defenses, reducing systemic inflammation, and improving metabolic risk factors. Conclusions: The integration of exercise and nano-curcumin supplementation appears to confer superior benefits for women with lifestyle-related diseases compared with either approach alone. These findings highlight the potential of combining phytochemicals with lifestyle interventions to optimize women’s health outcomes. However, most available evidence originates from small, short-term studies in single geographic regions. Large-scale, multicenter, randomized controlled trials with diverse populations are warranted to establish standardized protocols and optimal dosing strategies, and to assess long-term safety and efficacy. Full article

Pancreaticobiliary endoscopy, encompassing endoscopic ultrasound (EUS), endoscopic retrograde cholangiopancreatography (ERCP), and digital single-operator cholangioscopy (DSOC), is essential for diagnosing and managing pancreatic and biliary diseases. However, these procedures are limited by operator dependency, variable diagnostic accuracy, and technical complexity. Artificial intelligence (AI), particularly through machine learning (ML) and deep learning (DL), has emerged as a promising tool to address these challenges. Early studies show that AI can enhance lesion detection, improve differentiation of pancreatic masses, classify cystic lesions, and aid in diagnosing malignant biliary strictures. AI has also been used to predict post-ERCP pancreatitis risk and reduce radiation exposure during ERCP. Despite this promise, current AI models are largely experimental—limited by small, single-center datasets, lack of external validation, and no FDA-approved systems for these indications. Major barriers include inconsistent data acquisition, limited interoperability across hardware platforms, and integration into real-time workflows. Future progress depends on multicenter data sharing, standardized imaging protocols, interpretable AI design, and regulatory pathways for model deployment and updates. AI can be developed as a valuable partner to endoscopists, enhancing diagnostic accuracy, reducing complications, and supporting more efficient, personalized care in pancreaticobiliary endoscopy. Full article

Colorectal cancer (CRC) is a major cause of cancer mortality worldwide, with metastatic disease remaining the main driver of poor prognosis. In recent years, the concept of oligometastatic disease, where patients present with a limited number of metastases, has created an opportunity to use local therapies with curative intent. Stereotactic ablative radiotherapy (SABR) has become increasingly important in this setting, as it allows the delivery of high, ablative doses with excellent local control and generally low toxicity. Notably, randomised data such as SABR-COMET, alongside large prospective series including SABR-5, have demonstrated improvements in survival outcomes in the context of oligometastatic disease across mixed primary tumour types, with CRC patients making up a relatively small proportion in these trials. This has presented SABR as a practical treatment option for patients with oligometastatic CRC, although more CRC-specific phase III trials are needed. Other challenges include the radioresistance of CRC metastases, and treatment outcomes that vary depending on the anatomical site, tumour biology, and prior therapies. Technical issues such as motion management and organ-at-risk constraints also continue to limit dose escalation. Emerging strategies—including MR-guided radiotherapy, proton-based SABR, integration with systemic agents such as immunotherapy, and the use of biomarkers and artificial intelligence to refine patient selection—are beginning to address these limitations. This review summarises the current evidence and emerging advancements to highlight how SABR may evolve as part of an integrated approach to oligometastatic CRC. Full article

Biliary tract carcinoma (BTC) is a group of highly heterogeneous malignancies arising from the biliary epithelium. Anatomically, BTC is categorized into gallbladder cancer (GBC) and cholangiocarcinoma (CCA), with the latter further subdivided into intrahepatic (iCCA), perihilar (pCCA), and distal cholangiocarcinoma (dCCA). Epidemiological studies reveal a dismal five-year survival rate of less than 20% for BTC patients, with limited responses to current chemotherapy regimens, underscoring the urgent need to unravel its complex molecular pathogenesis. Recent research has increasingly focused on the regulatory networks of post-translational modifications, particularly the ubiquitin-proteasome system (UPS), in tumorigenesis. As the largest subfamily of deubiquitinating enzymes (DUBs), ubiquitin-specific proteases (USPs) regulate the stability of key oncoproteins such as phosphatase and tensin homolog (PTEN) and c-Myc, playing pivotal roles in tumor cell proliferation, apoptosis evasion, invasion, and metastasis. This review systematically summarizes the differential expression profiles of USP family members (e.g., USP1, USP3, USP7, USP8, USP9X, USP21, and USP22) in BTC and their clinical significance, with a focus on elucidating how specific USPs regulate tumor progression through key substrates, including poly(ADP-ribose) polymerase 1 (PARP1), dynamin-1-like protein (DNM1L), and O-GlcNAc transferase (OGT). Furthermore, based on recent advances, we discuss the therapeutic potential of small-molecule USP inhibitors in BTC targeted therapy, providing a theoretical foundation for developing novel precision treatment strategies. Full article

Background: CP (CP) and HCP (HCP) are rare and high-risk conditions, often historically managed with radical intervention and associated with hemorrhage and fertility loss. Objective: To summarize current evidence on the conservative, fertility-preserving management of cervical and heterotopic cervical pregnancies and to illustrate a stepwise pharmacologic protocol applied in our tertiary center. Methods: A narrative literature review (PubMed, Scopus, Web of Science; inception—July 2025) was conducted using the following key terms: “CP,” “HCP,” “methotrexate,” “mifepristone,” “misoprostol,” “uterine artery embolization,” “hysteroscopy,” and “Doppler ultrasound.” We integrated a personal institutional case that applied stepwise pharmacologic priming, Doppler-guided surveillance, and delayed evacuation. Results: Evidence—primarily from case reports and small series—supports conservative, multi-modal strategies combining systemic or local methotrexate ± mifepristone, timed to Doppler-confirmed vascular regression, before surgical intervention. Adjuncts such as misoprostol, hysteroscopic resection, balloon tamponade, and uterine artery embolization further reduce hemorrhage risk while maintaining fertility. Our case utilized a novel, incremental dosing strategy of mifepristone followed by methotrexate, a week-long interval to confirm vascular involution via Doppler, and delayed suction curettage with minimal blood loss. Conclusions: Conservative, imaging-guided management is promising for reducing hemorrhagic complications and preserving fertility in CP/HCP. Future multicenter registries and standardized Doppler-based protocols are urgently needed to refine decision-making and optimize outcomes. Full article

Turbulence and wind gusts pose significant risks to the safety and efficiency of UAVs (uncrewed aerial vehicles) in urban environments. In these settings, wind dynamics are strongly influenced by interactions with buildings and terrain, giving rise to small-scale phenomena such as vortex shedding and gusts. These wind speed oscillations generate unsteady forces that can destabilise UAV flight, particularly for small vehicles. Additionally, predicting their formation requires high-resolution Computational Fluid Dynamics (CFD) models, as current weather forecasting tools lack the resolution to capture these phenomena. However, such models require 3D representations of study areas with high geometric consistency and detail, which are not available for most cities. To address this issue, this work introduces an automated methodology for urban CFD mesh generation using open-source data. The proposed method generates error-free meshes compatible with OpenFOAM and includes tools for geometry modification, enhancing solver convergence and enabling adjustments to mesh complexity based on computational resources. Using this approach, CFD simulations are conducted for the city of Ourense, followed by an analysis of their impact on UAV operations and the integration of the system into a trajectory optimisation framework. The CFD model is also validated using experimental anemometer measurements. Full article

Background: Burnout is a widespread concern across frontline professions, with healthcare, education, and emergency services workers experiencing particularly high rates of stress and emotional exhaustion. Passive artificial intelligence (AI) technologies may provide novel means to monitor and predict burnout risk using data collected continuously and non-invasively. Objective: This review aims to synthesize recent evidence on passive AI approaches for detecting stress and burnout among frontline workers, identify key physiological and behavioral biomarkers, and highlight current limitations in implementation, validation, and generalizability. Methods: A narrative review of peer-reviewed literature was conducted across multiple databases and digital libraries, including PubMed, IEEE Xplore, Scopus, ACM Digital Library, and Web of Science. Eligible studies applied passive AI methods to infer stress or burnout in individuals in frontline roles. Only studies using passive data (e.g., wearables, Electronic Health Record (EHR) logs) and involving healthcare, education, emergency response, or retail workers were included. Studies focusing exclusively on self-reported or active measures were excluded. Results: Recent evidence indicates that biometric data (e.g., heart rate variability, skin conductance, sleep) from wearables are most frequently used and moderately predictive of stress, with reported accuracies often ranging from 75 to 95%. Workflow interaction logs (e.g., EHR usage patterns) and communication metrics (e.g., email timing and sentiment) show promise but remain underexplored. Organizational network analysis and ambient computing remain largely conceptual in nature. Few studies have examined cross-sector or long-term data, and limited work addresses the generalizability of demographic or cultural findings. Challenges persist in data standardization, privacy, ethical oversight, and integration with clinical or operational workflows. Conclusions: Passive AI systems offer significant promise for proactive burnout detection among frontline workers. However, current studies are limited by small sample sizes, short durations, and sector-specific focus. Future work should prioritize longitudinal, multi-sector validation, address inclusivity and bias, and establish ethical frameworks to support deployment in real-world settings. Full article

Smallholder farming plays a crucial role in global food security, contributing more than half of the world’s food supply. However, it is increasingly threatened by climate variability, declining soil fertility, and financial constraints, all of which suppress plant growth, reduce yields, and endanger livelihood stability. Addressing these challenges requires sustainable, eco-friendly alternatives to costly and environmentally damaging agrochemicals. Sorghum, a climate-resilient cereal, harbours a diverse microbiome that contributes significantly to its remarkable adaptability under adverse conditions. Harnessing the sorghum-associated microbiome, therefore, represents a promising, low-cost, and sustainable strategy to enhance sorghum productivity and resilience in smallholder farming systems. However, despite its potential, the adoption of microbiome-based technologies among smallholders remains limited due to a lack of local production units, poor government policies, knowledge gaps, and perceived risks. Although many studies report positive outcomes from microbiome-based interventions, translating this potential from controlled experiments to real-world field applications requires a critical evaluation of the efficacy, practicality, and limitations of microbial interventions. Furthermore, the outcomes of these studies are uneven, highly context-dependent, and often restricted to short-term or small-scale trials. This review, therefore, seeks to highlight current understanding of the sorghum microbiome, including its composition and the procedures for isolating and characterising beneficial microbes. It further evaluates the key challenges hindering adoption and proposes strategies to overcome them. Ultimately, this review advocates for integrating sorghum-associated microbiome technologies within integrated farming systems, underscoring their potential to enhance sustainable crop production, strengthen smallholder resilience, and contribute to the global sustainable development goals. Full article

Environmental protection is an essential path to achieving high-quality economic development, and green tax policies are an effective means of achieving environmental protection. This study categorizes green tax policies into environmental protection-oriented green tax policies, resource-oriented green tax policies, and guidance-oriented green tax policies based on the nature of the tax. The fixed-effect model, the system GMM model and the continuous DID model are used to explore the causal relationship between the overall green tax policy, the classified green tax policy and the use of natural resources. The spatial Durbin model is used to explore the spatial spillover effect of the green tax policy and the regional heterogeneity in the east, central, west and northeast of China. Finally, the role of trade openness in the relationship between the green tax policy and natural resource use is explored. The research results show that (1) the green tax policy has a positive effect on natural resource use, but the green tax policy in the previous period has no promoting effect, and the natural resource use in the previous period has a positive impact on the current period. Among them, there is no causal relationship between the resource-occupying green tax and natural resource use. (2) All three types of green tax policies studied in this paper have spatial spillover effects, but the spillover effects of the three types of green tax policies are relatively small in the eastern region. The spillover effects of the three types of green tax policies in the central region are significantly negative. In the western region, only the guiding green tax policy has a spillover effect. In the northeastern region, the environmental protection green tax policy and the resource-based green tax policy are significantly negative, while the guiding green tax spillover effect is significantly positive. (3) In the mechanism test, the guiding green tax policy has an impact on natural resource utilization through trade openness, while the environmental protection green tax policy and the resource-based green tax policy cannot affect natural resource utilization through the level of trade openness. Finally, based on the research conclusions, policy recommendations are proposed from the perspectives of policy timeliness, tax structure adjustment, and trade network optimization to maximize economic benefits. Full article

Endometrial cancer is one of the most common malignancies of the female reproductive system, with incidence rising globally due to population ageing and life-style-related risk factors. Calcium (Ca²⁺) is a ubiquitous second messenger regulating diverse physiological processes, and its dysregulation has been increasingly implicated in carcinogenesis, including endometrial. Altered expression and function of Ca²⁺ channels, pumps, exchangers, and binding proteins disrupt the finely tuned balance of Ca²⁺ influx, efflux, and intracellular storage, leading to aberrant signalling that promotes tumour proliferation, migration, survival, and metastasis. This review summarises current knowledge on the molecular “Ca²⁺ toolkit” in the human uterus, highlighting the role of voltage-gated calcium channels (VGCCs), transient receptor potential (TRP) channels, store-operated calcium entry (SOCE) components, Na⁺/Ca²⁺ exchangers, purinergic receptors, P-type ATPases (SERCA, SPCA, PMCA), ryanodine (RyR) and inositol 1,4,5-trisphosphate (IP₃R) receptors, and mitochondrial Ca²⁺ uniporter (MCU) complexes in endometrial cancer progression. Multiple Ca²⁺-handling proteins, including CACNA1D, CACNA2D1, TRPV4, TRPV1, TRPM4, MCU, and RyR1, exhibit cancer-associated overexpression or functional changes, correlating with poor prognosis and aggressive disease features. Emerging evidence supports the therapeutic potential of targeting Ca²⁺ homeostasis using small-molecule inhibitors, ion channel modulators or gene-silencing strategies. These interventions may restore Ca²⁺ balance, induce apoptosis or autophagy, and suppress metastatic behaviour. While no clinical trials have yet explicitly focused on Ca²⁺ modulation in endometrial cancer, the diversity of dysregulated Ca²⁺ pathways offers a rich landscape for novel therapeutic strategies. Targeting key components of the Ca²⁺ signalling network holds promise for improving outcomes in endometrial cancer. Full article

Animal models have been pivotal in uncovering the orexin (hypocretin) system as the fulcrum of sleep–wake regulation and in shaping therapeutic discovery for narcolepsy. Early canine and murine models established that orexin loss underlies narcolepsy type 1, while conditional and receptor-specific manipulations refined mechanistic insight. However, current paradigms capture only fragments of the human phenotype, often exaggerating cataplexy and under-representing narcolepsy type 2. Here, we follow the evolution of narcolepsy modelling from classical knockout and receptor-deficient systems to immune-driven and cell-replacement models, identifying critical translational gaps and proposing strategies to bridge them. We highlight how immune-competent mouse lines, astrocyte-to-neuron reprogramming, and patient-derived hypothalamic organoids bridge pathogenic insight with therapeutic innovation. Integrating these advances with small-molecule OX2R agonists, gene therapy, and multi-omics-based patient stratification defines a roadmap for moving beyond symptomatic control. This review seeks to unify immune, cellular, and computational perspectives to guide the next generation of animal models toward the prevention, repair, and long-term cure of narcolepsy. Full article

Minor Southern Italian population centers present a fragmented and uneven urban landscape, resulting from abandonment and depopulation phenomena that have led, especially in historic city centers, to urban voids scattered with rubble, buildings in a state of ruin, and others with evident structural collapses. Within a broader urban regeneration strategy for these centers, aligned with current national and European policies, the recovery of these vacant spaces can play a decisive role in enhancing urban quality and the desired touristic appeal, with social, economic, and environmental implications. These areas may also become valuable resources for innovating the urban core in a green transition process, contributing to carbon neutrality goals while improving residents’ quality of life. This paper addresses the importance of pocket parks as systems of resilience against climate change and hydrogeological risks, as well as rainwater drainage systems in densely built urban areas with strong historical character. The study includes a case study application focusing on a location in the Sicilian hinterland, notable for its historical and architectural value. The urban center under examination, Naro in the province of Agrigento, has experienced significant depopulation over the past fifty years, and the designation of its provincial capital as the Italian Capital of Culture 2025 could provide the opportunity for revival through small-scale, low-cost, and sustainable actions. Full article

Aiming at the speed chattering problem caused by high-frequency square wave injection in permanent magnet synchronous motors (PMSMs) during low-speed operation (200–500 r/min), this study intends to improve the rotor position estimation accuracy of sensorless control systems as well as the system’s ability to resist harmonic interference and sudden load changes. The goal is to enhance the control performance of traditional control schemes in this scenario and meet the requirement of stable low-speed operation of the motor. First, the study analyzes the harmonic error propagation mechanism of high-frequency square wave injection and finds that the traditional PI phase-locked loop (PI-PLL) is susceptible to high-order harmonic interference during demodulation, which in turn leads to position estimation errors and periodic speed fluctuations. Therefore, the extended state observer phase-locked loop (ESO-PLL) is adopted to replace the traditional PI-PLL. A third-order extended state observer (ESO) is used to uniformly regard the system’s unmodeled dynamics, external load disturbances, and harmonic interference as “total disturbances”, realizing real-time estimation and compensation of disturbances, and quickly suppressing the impacts of harmonic errors and sudden load changes. Meanwhile, a dynamic pole placement strategy for the speed loop is designed to adaptively adjust the controller’s damping ratio and bandwidth parameters according to the motor’s operating states (loaded/unloaded, steady-state/transient): large poles are used in the start-up phase to accelerate response, small poles are switched in the steady-state phase to reduce errors, and a smooth attenuation function is used in the transition phase to achieve stable parameter transition, balancing the system’s dynamic response and steady-state accuracy. In addition, high-frequency square wave voltage signals are injected into the dq axes of the rotating coordinate system, and effective rotor position information is extracted by combining signal demodulation with ESO-PLL to realize decoupling of high-frequency response currents. Verification through MATLAB/Simulink simulation experiments shows that the improved strategy exhibits significant advantages in the low-speed range of 200–300 r/min: in the scenario where the speed transitions from 200 r/min to 300 r/min with sudden load changes, the position estimation curve of ESO-PLL basically overlaps with the actual curve, while the PI-PLL shows obvious deviations; in the start-up and speed switching phases, dynamic pole placement enables the motor to respond quickly without overshoot and no obvious speed fluctuations, whereas the traditional fixed-pole PI control has problems of response lag or overshoot. In conclusion, the “ESO-PLL + dynamic pole placement” cooperative control strategy proposed in this study effectively solves the problems of harmonic interference and load disturbance caused by high-frequency square wave injection in the low-speed range and significantly improves the accuracy and robustness of PMSM sensorless control. This strategy requires no additional hardware cost and achieves performance improvement only through algorithm optimization. It can be directly applied to PMSM control systems that require stable low-speed operation, providing a reliable solution for the promotion of sensorless control technology in low-speed precision fields. Full article

Space-based infrared (IR) detection, with wide coverage, all-time operation, and stealth, is crucial for aerial target surveillance. Under low signal-to-noise ratio (SNR) conditions, however, its small target size, limited features, and strong clutters often lead to missed detections and false alarms, reducing stability and real-time performance. To overcome these issues of energy-integration imaging in perceiving dim targets, this paper proposes a biomimetic vision-inspired Infrared Temporal Differential Detection (ITDD) method. The ITDD method generates sparse event streams by triggering pixel-level radiation variations and establishes an irradiance-based sensitivity model with optimized threshold voltage, spectral bands, and optical aperture parameters. IR sequences are converted into differential event streams with inherent noise, upon which a lightweight multi-modal fusion detection network is developed. Simulation experiments demonstrate that ITDD reduces data volume by three orders of magnitude and improves the SNR by 4.21 times. On the SITP-QLEF dataset, the network achieves a detection rate of 99.31%, and a false alarm rate of $1.97\times {10}^{-5}$, confirming its effectiveness and application potential under complex backgrounds. As the current findings are based on simulated data, future work will focus on building an ITDD demonstration system to validate the approach with real-world IR measurements. Full article