Search Results (14,710)

In the digital era, online attention has become a key indicator of tourism competitiveness and destination visibility. This study proposes a two-dimensional framework to evaluate the competitive state of online attention by combining its current magnitude and growth dynamics. Using Baidu Index data, the study applies the Boston Consulting Group (BCG) matrix and the coefficient of variation to analyze online attention patterns of Beijing’s 5A–level tourist attractions from 2011 to 2025. The results show clear polarization in online attention. A small number of iconic attractions consistently dominate digital visibility, while many other sites exhibit unstable and uneven attention trajectories. These patterns reflect the cumulative effects of consumer behavior, information-seeking preferences, and algorithmically mediated content environments, which reinforce attention concentration and competitive inequality over time. External shocks, particularly the COVID–19 pandemic, caused sharp declines in online attention in 2020, followed by an uneven recovery in subsequent years, highlighting the volatility of digital attention systems. The study also demonstrates the managerial value of the proposed framework. By classifying attractions according to attention levels and growth potential, the framework supports differentiated marketing and demand–redistribution strategies. For instance, increasing the visibility of high-potential but under-visited attractions can help redirect visitors away from overcrowded “Star/GC” sites and encourage more balanced spatial and temporal visitation. Overall, this study proposes a quantitative and replicable framework that integrates digital attention dynamics, algorithmic filtering, and consumer behavior into destination competitiveness analysis. The framework supports evidence-based and sustainability-oriented destination management by informing adaptive marketing and demand management strategies that can help alleviate overtourism and balance visitor flows. However, the study relies on a single digital platform and lacks direct sustainability indicators. Future research should integrate multi-platform data and link online attention metrics to measurable environmental, social, and economic sustainability outcomes. Full article

Evaporation is a key component of air–sea coupling processes and understanding the uncertainty in its estimation is essential for climate research and prediction. Based on four widely used datasets (OAFlux, NCEP2, MERRA2 and ERA5), this study systematically analyzes the seasonal evolution of inter-dataset uncertainty in evaporation variation over the tropical Indian Ocean using an evaporation decomposition method. Our main contribution is to show that evaporation variation uncertainty is not seasonally uniform but organized into distinct seasonal regimes with different dominant controlling factors and sensitivity structures. The results reveal significant seasonal dependence of evaporation variation uncertainty: the uncertainty is relatively small in boreal spring and autumn but larger in boreal summer and winter. The evaporation variation is primarily controlled by the relative humidity term (RH^*) in boreal summer and by the wind speed term (U^*) in other seasons. More importantly, the sources of uncertainty differ fundamentally between seasons: the large uncertainty of RH^* in boreal summer mainly originates from the high and variable sensitivity of evaporation to relative humidity, whereas the large uncertainty of U^* in boreal winter primarily stems from substantial inter-dataset discrepancies in wind speed data itself. These findings reveal that evaporation variation uncertainty arises from both input data discrepancies and the nonlinear sensitivity of evaporation processes, with their relative contributions varying seasonally. This study provides a physically based explanation for evaporation uncertainty and offers a useful basis for evaporation dataset selection and climate model evaluation. Full article

This study presents a comprehensive assessment of historical and projected variability in the wind climate over Ireland and its adjacent marine regions, including the North Atlantic Ocean, Irish Sea, and Celtic Sea. First, the long-term wind characteristics are examined using the ERA5 reanalysis dataset for the historical period (1979–2008), followed by an evaluation of five CMIP6 Global Climate Models (GCMs) to determine their performance in representing regional wind climatology. Based on spatial validation and relative bias analyses, the most suitable model is selected to investigate future wind changes under the SSP2-4.5 and 5-8.5 scenarios. The CMIP6 historical data is also compared locally at seven measurement stations. Two future projections are considered for the near-term (2031–2060) and mid-term (2071–2100), focusing on inter- and intra-annual variability and extreme wind behaviour. The results indicate an overall decrease in mean wind speed across the study area, with more pronounced reductions under SSP5-8.5 and during the mid-term period. In terms of seasonality, reductions are more pronounced during winter and summer than in the transitional seasons. According to the extreme value analysis based on the generalised extreme value distribution, general declines in extreme values are detected at selected critical locations, especially at wind speeds with large return periods. Full article

Pulmonary hypertension (PH) can be defined as a mean pulmonary artery pressure (mPAP) greater than 20 mm Hg at rest during right heart catheterization (RHC). The reported prevalence of PH throughout the globe has been estimated to impact approximately 1% of the total population, with a majority of those afflicted being women more than men. Numerous etiologies give rise to the pathophysiology of PH, including heart disease (i.e., left-sided heart failure), lung diseases, and other unclear causes related to chronic stages and complications surrounding long-standing pulmonary thromboembolisms, side effects of certain medications, and genetic and environmental factors. Untreated PH can lead to severe morbidities such as cardio-renal syndrome and congestive hepatopathy (cardiac cirrhosis). Management of PH focuses on decreasing pulmonary pressures by using vasodilators such as prostanoids, and phosphodiesterase type 5 (PDE-5) inhibitors, as well as newer treatments such as sotatercept, which inhibits activin signaling, thereby inhibiting excessive cell growth in the pulmonary artery vasculature and down-regulating the pro-proliferative pathways. Full article

Ocean surface currents (OSCs) are central to upper ocean dynamics and air–sea exchange, yet their retrieval from spaceborne synthetic aperture radar (SAR) is limited by wave-induced bias (WB). WB arises from the inherent motion of the scattering facets and from long-wave hydrodynamic and tilt modulations, and is therefore jointly controlled by sea state and radar viewing geometry. This study develops an observation geometry optimization framework. Five years of hourly ERA5 wind and wave reanalysis data over the Kuroshio are used as a representative ensemble of sea states to drive the KaDOP model, and an exhaustive grid search over line-of-sight (LOS) azimuth (0–360°) and incidence angle (20–60°) is performed to identify, for each location and season, the viewing geometry that minimizes the time-mean WB. These local optima are then summarized as mission-level metrics, including the minimum achievable WB, the coverage meeting prescribed WB thresholds, and the spatial coherence of the preferred LOS azimuth and incidence angle. Finally, the theoretical minima are compared with the fixed left-looking geometry of the Luojia-2 (LJ-2) satellite along a 213 km × 6 km observation corridor and with Gaofen-3 (GF-3) viewing geometries at four representative locations in the Kuroshio. Across these validation cases, the optimized geometry reduces mean absolute WB by about 20–60% for LJ-2 and 20–80% for GF-3, providing quantitative constraints for future SAR mission design targeting OSCs. Full article

The Zhuanghe coast in the northern part of the Yellow Sea is one of China’s important fishing and ocean engineering areas. Frequent storm surge events pose a significant threat to residents’ safety and properties. This study used the coupled Finite Volume Coastal Ocean Model (FVCOM) and the Surface Wave Model (FVCOM-SWAVE) to investigate storm surges and wave heights during Typhoons Muifa (1109) and Lekima (1909) in the northern parts of the Yellow Sea and analyze the impact of the typhoon parameters on flood inundation on the Zhuanghe coast. The wind stress comparison in the coupled wave–current model uses synthetic wind field data formed by superimposing ERA5 wind fields with a parameterized typhoon model. The results showed that the simulated and measured tide levels, wave heights, and storm surges were in good agreement, indicating that the coupled model accurately reproduced the dynamics of the storm surges and wave heights during the two typhoons. The maximum significant wave height (H_s) exhibited a right-skewed distribution in the two typhoons’ paths, with extreme values consistently located to the right of the typhoon’s center. The decrease in atmospheric pressure at the center of Typhoon Muifa was significantly, nonlinearly, and positively correlated with the severity of storm surge disasters. A significant correlation was observed between the path of Typhoon Muifa and the disaster intensity. Full article

Trastuzumab is the first humanised monoclonal antibody (Mab) developed for breast cancer (BC) therapy. The high affinity of Trastuzumab Fab-domain binding to the human epidermal growth factor receptor 2 (HER2) receptor, with a K_d value of <1 nM, is also accompanied by Fc domain interaction with Fc-receptors in natural killer cells and leukocytes, enabling the killing of tumour cells through antibody-directed cellular cytotoxicity (ADCC). Trastuzumab blocks the over-expressed HER2 receptor-mediated dimerization and consequent intracellular signalling, leading to cancerous growth. However, the trastuzumab resistance (TR) became the major problem within 1 year of treatment. The mutation in phosphatidylinositol 3′-kinase (PI3K) pathway, cross-talk with estrogen receptors, over-expression of Mucin 1 (MUC1) protein, insulin-like growth factor I receptor, etc., are key pathways involved in TR. In this review, we have provided a molecular view of TR and the possible remedies for overcoming TR using BC stem cell (BCSC)-based therapy, PI3K pathway inhibitors, MUC1-based treatment, etc. We have also analysed the patents and clinical trials from the pre-TR and post-TR era to rationalise the possible steps to overcome TR. Our analysis implies that Trastuzumab monotherapy no longer applies to HER2+ BC treatment. Further, combination therapy using other antibodies like pertuzumab and protein kinase inhibitors and targeting pathways like the ubiquitin proteasome pathway will be the future option for BC Treatment. Overall, this review provides a detailed summary of the molecular mechanisms involving TR and its potential ways of evasion, based on updated information from published research articles, clinical trial outcomes, and patent data. Full article

As modern society grows increasingly complex, access to essential services such as healthcare, legal aid, tailored education, and psychological support remains heavily gated by socio-economic, neurological, and systemic barriers. This paper explores the transformative potential of Large Language Models (LLMs) and Generative Artificial Intelligence not merely as industrial productivity enhancers, but as vital “social scaffolds” capable of fostering a more inclusive society. Crucially, we propose a paradigm shift in the concept of Ethical Computing—moving from a passive defensive framework of non-maleficence (“do no harm”) to an active mandate of beneficence, where AI systems are explicitly developed to serve marginalized and un(der)served populations. Through this expanded ethical lens, we systematically analyze the democratizing impact of AI across four primary axes of inclusivity: socio-economic (providing zero-cost medical triage and legal translation for undocumented populations), neurospicy (acting as a non-judgmental communicative bridge for individuals with Autism Spectrum Disorder), pedagogical (delivering hyper-personalized executive function support for Special Educational Needs), and psychological (serving as an accessible, first-level triage system for mental health crises). By framing LLMs as a modern social safety net, we outline a clear trajectory for future research, advocating for an “ethical-by-design” development paradigm that explicitly prioritizes equity, accessibility, and the active dismantling of historical barriers for the digitally and socially disenfranchised. Full article

Notable advances in modal analysis in the last 50 years have paved the way for more widespread use of modal parameters, including those from in situ measurements, in Structural Health Monitoring and finite element model updating. Current state-of-the-art techniques in output-only modal analysis include Stochastic Subspace Identification techniques, such as Canonical Variate Analysis (SSI), and the Natural Excitation Technique with the Eigensystem Realization Algorithm (NExT-ERA). The former have been shown to struggle on very large systems and the latter suffers from the usual fitting problems arising in noisy environments. In this work, an output-only version of the frequency domain technique known as the Loewner Framework (LF) is pioneeringly applied to an aeronautical system. The implementation pairs the LF with NExT (NExT-LF) to exploit the fitting process efficiency of the former and robustness to noise of the latter. The thus-defined NExT-LF is then applied to the well-known experimental benchmark of the eXperimental BeaRDS 2 high-aspect-ratio wing main spar. The results are compared to the known experimental values and those obtained from SSI and NExT-ERA. Full article

Wind energy is an important form of clean energy, and its rational utilization represents a crucial solution for mitigating the energy crisis and global warming. In this study, wind energy potential and its long-term changes in the South China Sea (SCS) are evaluated using ERA5 100 m wind data from 1944 to 2023, validated against ASCAT observations. High wind speeds and high wind power density (WPD) are concentrated southwest of Taiwan and southeast of Vietnam. Annual wind availability exceeds 6457 h across most regions, reaching up to 8283 h in optimal locations. WPD and capacity factor peak in winter (up to 2.4 × 10⁸ Wh·m⁻² and >50% capacity factor), with the most stable conditions occurring in the southwestern Taiwan Strait, southeast of the Pearl River Delta, and the Beibu Gulf. Empirical orthogonal function analysis reveals that the first mode of winter WPD accounts for 65.7% of the total variance, with a statistically significant increasing trend since 1990. The interannual variation in wind energy resources in the SCS during winter is controlled by the combined effects of sea surface temperature (SST) anomalies in the tropical Pacific and the Arctic Barents Sea. Specifically, in the years with strong wind anomalies in the SCS, mega-La Niña-type SST patterns in the tropical Pacific trigger anomalous cyclonic circulation in the SCS and the eastern Philippine Sea, while warm anomalies in the Arctic Barents Sea surface drive a wave-like structure of “anticyclone–cyclone–anticyclone” from Siberia to South China. The coupling of the two systems jointly promotes the strengthening of the South China Sea monsoon, leading to increased wind speeds and elevated WPD in the northern SCS. These findings provide a scientific basis for wind farm siting and long-term operational planning in the region. Full article

Fallujah, by Jonathan Holmes (2007), is one of the archetypal examples of verbatim theatre, which addresses the truths of the Iraq War through dramatised eyewitness accounts and documentation reconstructions. Sketched in the Second Battle of Fallujah, the play reveals moral, political, and epistemological aspects of how modern warfare is presented. This article hinges on the postmodern theory of Jean-François Lyotard—especially the concepts of language games, paralogy, and the differend—to discuss the play Fallujah as a subversion of official grand narratives of the Iraq War. Through the use of testimonial intertextuality, irony and fragmentation, Holmes builds a multidimensional tableau of discourse contradictions in which truth is relative, and legitimacy is constantly deferred. The play turns into a meta-discursive critique of Western power dynamics, challenging the manner in which the knowledge is created, distributed, and twisted in the name of liberation and humanitarianism. Further, the article examines both dramaturgical and aesthetic techniques that lend truthfulness to Holmes’ concept of the verbatim approach as it dislocates the truth in relation to war and victimhood. The results help us comprehend the role of modern theatre in the reconstruction of the cultural memory and morality in the post-war era. The article concludes that Fallujah is a vivid example of postmodern theatrical resistance, an ethical and artistic response to commodity violence and the obliteration of lived suffering. Full article

Background: Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer and is generally associated with an excellent prognosis. Historically, treatment strategies were uniform and frequently aggressive, including total thyroidectomy and routine radioiodine ablation, even in low-risk cases. Current Perspective: Over the past decade, the management of PTC has shifted toward a de-escalation paradigm. This transition is driven by high evidence showing that the majority of PTCs follow an indolent course, with low recurrence and mortality rates. As a result, there is increasing emphasis on tailoring the extent of surgery and adjuvant therapy to individual patient risk profiles. Active surveillance, hemithyroidectomy, and selective use of radioiodine now represent valid alternatives to traditional radical approaches, particularly for low-risk tumors. Clinical Implications: The goal of this evolution is to balance oncologic safety with quality of life, reducing overtreatment and minimizing long-term complications such as hypoparathyroidism or recurrent laryngeal nerve injury. Personalized treatment decisions are now guided by tumor biology, molecular markers, and refined risk stratification systems. Conclusions: This article will review the current evidence supporting this shift, highlight the challenges of implementation in clinical practice, and discuss future trends in the management of papillary thyroid carcinoma. Full article

Deep learning has revolutionized medical image segmentation; however, the clinical deployment of state-of-the-art models is severely impeded by their quadratic computational complexity and substantial resource demands, particularly in multisensor and multimodal imaging scenarios. In response, the field is undergoing a paradigm shift towards efficiency, characterized by the rise of linear-complexity architectures and the optimization of foundation models. This paper presents a comprehensive survey of efficient medical image segmentation methodologies, systematically reviewing the evolution from heavy, accuracy-driven models to lightweight, deployment-ready paradigms. In particular, we highlight the growing importance of efficient segmentation in multisensor medical imaging, where heterogeneous data sources such as CT, MRI, ultrasound, and infrared imaging introduce additional challenges in scalability and computational cost. We propose a novel taxonomy that categorizes these advancements into four distinct streams: (1) Mamba and State Space Models, which leverage selective scanning mechanisms to achieve global receptive fields with linear complexity; (2) Efficient Adaptation of Foundation Models, focusing on parameter-efficient fine-tuning and knowledge distillation to tailor the Segment Anything Model (SAM) for medical domains; (3) Advanced Lightweight Architectures, covering the resurgence of large-kernel CNNs and the emergence of Kolmogorov–Arnold Networks (KANs); and (4) Data-Efficient Strategies, including semi-supervised and federated learning to address annotation scarcity. Furthermore, we conduct a rigorous comparative analysis of representative algorithms on mainstream benchmarks, providing a granular evaluation of the trade-offs between segmentation accuracy and computational overhead. The survey also discusses key challenges in multisensor and multimodal settings, including modality heterogeneity, data fusion complexity, and resource constraints. Finally, we identify critical challenges and outline future research directions, serving as a roadmap for the development of next-generation efficient and scalable medical image analysis systems. Full article

Smart contracts raise persistent challenges regarding compliance with traditional contract formalities, including writing, signature, notarization, and in certain transactions, registration. These issues are particularly significant in high-value and public-facing transactions such as real estate, where formalities determine legal validity, evidentiary sufficiency and publicity effects. While existing scholarly work has examined these challenges from either doctrinal or technological perspectives, limited attention has been given to how the functional roles of formalities interact with blockchain architecture, practitioner perceptions and institutional legal frameworks. This study addresses this gap through a mixed-methods approach combining doctrinal legal analysis with qualitative socio-legal research based on 27 semi-structured interviews with legal professionals including attorneys, judges, and academic scholars. The analysis is grounded in a civil law framework, with particular reference to the Jordanian legal system, while references to the European Union’s eIDAS Regulation are used illustratively to demonstrate regulatory approaches to digital authentication. The findings demonstrate that blockchain-based systems can effectively support the evidentiary and attribution functions of contractual formalities through cryptographic verification, consensus mechanisms, and automated execution. However, they do not independently satisfy formalities that perform cautionary, constitutive, protective or public order function, namely notarization and registration, which remain dependent on institutional validation and legal recognition. The analysis further shows that practitioner concerns reflect not only doctrinal constraints but also institutional roles and varying levels of technical familiarity. To address these limitations, the study proposes a function-based analytical framework for evaluating smart contract formalities and identifies two complementary pathways for legal adaptation: (i) institutional integration, including registry-linkage systems and hybrid contracts; and (ii) technological adaptation, including digital authentication frameworks and legal oracles that connect on-chain execution to off-chain legal conditions. The study concludes that smart contract formalities’ challenges arise not solely from technological limitations, but from the interaction between legal doctrine, institutional structures, and system design. It advances a functional framework for aligning automation with the evidentiary, protective, and publicity functions of contractual formalities. Full article