Search Results (834)

The integration of vision and language processing into a cohesive system has already shown promise with the application of large language models (LLMs) in medical image analysis. Their capabilities encompass the generation of medical reports, disease classification, visual question answering, and segmentation, providing yet another approach to interpreting multimodal data. This survey aims to compile all known applications of LLMs in the medical image analysis field, spotlighting their promises alongside critical challenges and future avenues. We introduce the concept of X-stage tuning which serves as a framework for LLMs fine-tuning across multiple stages: zero stage, one stage, and multi-stage, wherein each stage corresponds to task complexity and available data. The survey describes issues like sparsity of data, hallucination in outputs, privacy issues, and the requirement for dynamic knowledge updating. Alongside these, we cover prospective features including integration of LLMs with decision support systems, multimodal learning, and federated learning for privacy-preserving model training. The goal of this work is to provide structured guidance to the targeted audience, demystifying the prospects of LLMs in medical image analysis. Full article

Stock price forecasting remains a persistent challenge in time series analysis due to complex inter-stock relationships and dynamic textual signals such as financial news. While Graph Neural Networks (GNNs) can model relational structures, they often struggle with capturing higher-order dependencies and are sensitive to noise. Moreover, sentiment signals are typically aggregated using fixed time windows, which may introduce temporal bias. To address these issues, we propose DASF-Net (Diffusion-Aware Sentiment Fusion Network), a multimodal framework that integrates structural and textual information for robust prediction. DASF-Net leverages diffusion processes over two complementary financial graphs—one based on industry relationships, the other on fundamental indicators—to learn richer stock representations. Simultaneously, sentiment embeddings extracted from financial news using FinBERT are aggregated over an empirically optimized window to preserve temporal relevance. These modalities are fused via a multi-head attention mechanism and passed to a temporal forecasting module. DASF-Net integrates daily stock prices and news sentiment, using a 3-day sentiment aggregation window, to forecast stock prices over daily horizons (1–3 days). Experiments on 12 large-cap S&P 500 stocks over four years demonstrate that DASF-Net outperforms competitive baselines, achieving up to 91.6% relative reduction in Mean Squared Error (MSE). Results highlight the effectiveness of combining graph diffusion and sentiment-aware features for improved financial forecasting. Full article

This study investigates the effects of salinity, temperature, and diet on the biological characteristics of the rotifer Brachionus plicatilis, an essential live feed in aquaculture. The results indicate that environmental factors have a significant influence on reproductive traits and survival. At a salinity of 5 ppt, B. plicatilis achieved the highest fecundity (25.50 ± 0.58 inds.), while the longest lifespan (273.00 ± 72.52 h) was observed at 35 ppt. The temperature had a strong influence on developmental rates, with the shortest juvenile period recorded at 35 °C (8.00 ± 0.00 h) and the longest lifespan at 20 °C (270.62 ± 30.38 h). The diet also played a critical role, with Chlorella vulgaris supporting maximum fecundity, whereas mixed diets prolonged lifespan to 290.50 ± 62.83 (h). These findings provide valuable insights into optimizing rotifer culture systems to improve aquaculture productivity and sustainability. Full article

Advanced three-dimensional extended reality (XR) technologies are highly suitable for cultural heritage research and education. XR tools enable the creation of realistic virtual or augmented reality applications for curating and disseminating information about cultural artifacts and sites. Developing XR applications for cultural heritage requires interdisciplinary collaboration involving strong teamwork and soft skills to manage user requirements, system specifications, and design cycles. Given the diverse end-users, achieving high precision, accuracy, and efficiency in information management and user experience is crucial. Human–computer interaction (HCI) design and evaluation methods are essential for ensuring usability and return on investment. This article presents ten case studies of cultural heritage software projects, illustrating the interdisciplinary work between computer science and HCI design. Students from institutions such as the State University of New York (USA), Glasgow School of Art (UK), University of Granada (Spain), University of Málaga (Spain), Duy Tan University (Vietnam), Imperial College London (UK), Research University Institute of Communication & Computer Systems (Greece), Technical University of Košice (Slovakia), and Indiana University (USA) contributed to creating, assessing, and improving the usability of these diverse cultural heritage applications. The results include a structured typology of CH XR application scenarios, detailed insights into design and evaluation practices across ten international use cases, and a development framework that supports interdisciplinary collaboration and stakeholder integration in phygital cultural heritage projects. Full article

Background: Hypoxia and immune components significantly shape the tumor microenvironment and influence prognosis and immunotherapy response in gastric cancer (GC). This study aimed to develop hypoxia- and immune-related gene signatures for prognostic evaluation in GC. Methods: Transcriptomic data from TCGA-STAD were integrated with hypoxia- and immune-related genes from InnateDB and MSigDB. A prognostic gene signature was constructed using Cox regression analyses and validated on an independent GSE84437 cohort and single-cell RNA dataset. We further analyzed immune cell infiltration, molecular characteristics of different risk groups, and their association with immunotherapy response. Single-cell RNA-seq data from the TISCH database were used to explore gene expression patterns across cell types. Results: Five genes (TGFB3, INHA, SERPINE1, GPC3, SRPX) were identified. The risk score effectively stratified patients by prognosis, with the high-risk group showing lower overall survival and lower T-cell expression. The gene signature had an association with immune suppression, ARID1A mutation, EMT features, and poorer response to immunotherapy. Gene signature, especially SRPX was enriched in fibroblasts. Conclusions: We developed a robust hypoxia- and immune-related gene signature that predicts prognosis and may help guide immunotherapy strategies for GC patients. Full article

Vaginitis is a major health concern among women, with inadequate treatment potentially leading to reproductive complications. This study aimed to assess vaginitis prevalence, identify predominant pathogens, and evaluate associated risk factors among female patients at Da Nang Dermato-Venereology Hospital. A prospective study of 796 female patients undergoing physical examinations was conducted, with demographic, clinical, and microbiological data collected. Vaginitis was diagnosed in 180 (22.6%) of 796 female patients, predominantly caused by Candida spp. (66.1%) and bacterial pathogens (31.7%), with no Trichomonas vaginalis detected, and was most prevalent in women aged 20–30 years. Poor hygiene practices, including infrequent sanitary pad changes (OR = 5.01, p < 0.001) and routine vaginal douching (OR = 6.77, p < 0.001), were significantly associated with vaginitis. The Amsel criteria showed high specificity (99.1%) for bacterial vaginosis diagnosis. The absence of T. vaginalis suggests a potential shift in the epidemiology of vaginal infections. The Amsel criteria are a practical diagnostic tool in resource-limited settings. Our findings highlight the need for targeted hygiene education to reduce vaginitis prevalence in Vietnam. Full article

Layered double hydroxide Ti-Zn-CO₃ was synthesized by the co-precipitation method with a molar ratio of 2. The synthesized material was characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), thermal analysis (TGA/DTG), UV–vis diffuse reflection spectroscopy (DRS), and Scanning Electron Microscopy (SEM). The photocatalytic degradation of Trypan Blue (TB) and Naphthol Green B (NGB) dyes from aqueous solutions under UV irradiation was investigated. The effects of contact time, photocatalyst dose, dye concentration, solution pH, scavenger effect, and regeneration of catalyst were investigated. The kinetic study showed that the equilibrium was reached within 30 min and 40 min for TB and NGB dyes, respectively, with photodegradation efficiency of around 91% and 83% for TB and NGB dyes, respectively, for dye concentration of 25 mg∙L⁻¹, and the pseudo-first order showed good agreement with the reaction. The optimum photocatalyst dose is 20 mg (1 g∙L⁻¹) and 30 mg (1.5 g∙L⁻¹) for TB and NGB dyes, respectively, and the optimal pH of reaction was found to be 7 for both TB and NGB dyes. This study was established to highlight the photodegradation performance of the prepared catalyst Ti-Zn-CO₃ for the degradation of (TB and NGB) dyes chosen as pollutants, and the fact that it can be used many times, which has an economical effect. This mean that the prepared sample is a potential catalyst with good photocatalytic activity, stability, and reusability. Full article

Recent decades have witnessed an increased volume of studies investigating the spa tourism sector. There has, however, been an absence of studies evaluating the relationship between corporate social responsibility (CSR) and spa competitiveness, as well as the mediating effects of responsible innovation (RI) and corporate sustainability performance (CSP) on this relationship. This study developed a comprehensive conceptual framework that examined the impacts of CSR on spa competitiveness. Data were collected from 786 participants, who included spa managers and employees located in three main cities of Vietnam: Ha Noi, Da Nang, and Ho Chi Minh. The Partial Least-Squares Structural Equation Modelling (PLS-SEM) method was applied to provide statistical evidence to confirm the conceptual model and eight hypotheses. The findings indicated that CSR positively and indirectly affects spa competitiveness. The mediating roles of RI and CSP, which influence the relationship with spa competitiveness, were also confirmed. This research makes theoretical contributions to understanding the relationships between these internal factors and achieving competitiveness. Further, the study has practical implications for spa managers and policymakers implementing CSR programs and RI and reshaping CSP to obtain and maintain their competitiveness. Full article

The growing presence of hazardous organic pollutants in wastewater poses severe environmental and health risks, necessitating sustainable and efficient treatment solutions. Traditional remediation methods have limitations, highlighting the need for innovative approaches. A green synthesis method was developed to produce TiO₂-CeO₂ nanocomposites using Cleistocalyx operculatus leaf extract. The photocatalytic efficiency of the synthesized nanocomposites was evaluated under simulated sunlight by degrading Methylene Blue (MB) dye. Various compositions were tested to determine the optimal performance. The 0.1% TiO₂-CeO₂ nanocomposite achieved the highest degradation efficiency (95.06% in 150 min) with a reaction rate constant (k) of 18.5 × 10⁻² min⁻¹, outperforming commercial TiO₂ (P25, 74.85%, k ≈ 3.7 × 10⁻² min⁻¹). Additionally, the material maintained excellent stability over eight consecutive cycles with only a slight decrease in efficiency from 95.85% to 93.28%. The enhanced photocatalytic activity is attributed to the synergistic effects of CeO₂ incorporation, which enhances charge separation, extends visible light absorption, and promotes reactive oxygen species (ROS) generation. These findings highlight the potential of green-synthesized TiO₂-CeO₂ nanocomposites as a cost-effective and sustainable solution for wastewater treatment. Full article

Sexually transmitted infections (STIs) remain a global issue, causing health problems and financial burdens. This study aimed to provide an update on the invasive pathogens and analyze any associated factors in patients visiting Da Nang Dermato-Venereology Hospital who were diagnosed with genital tract infections in males and lower genital tract infections in females; 535 participants underwent clinical examinations and microbiological tests to identify the invasive microorganisms, before we analyzed previously gathered laboratory results and associated risk factors. The rate of infection was 37.6% amongst 535 participants. Treponema pallidum infection accounted for the highest rate of 21.3%, followed by HSV, standing at 6%. The prevalence of syphilis infection was highest in the 20–29 age group, standing at 51.7%. There was a positive correlation between age under 20 and infected conditions (OR = 3.78, 95% CI: 1.41–10.11, p = 0.008). Having multiple sexual partners was identified as a risk factor for infection, as those with three or more sexual partners showed a high correlation (OR = 3.19, 95% CI: 1.44–7.05, p = 0.004). The high syphilis prevalence among young adults and teenagers underscores the need for improved STI education and screening programs in Vietnam. Full article

This study evaluates and estimates the agronomic effectiveness of food waste-derived fertilizers by analyzing plant yield and the internal efficiency of nitrogen utilization (IENU) via statistical and machine learning models. A dataset of 448 cases from various food waste treatments gathered from our experiments and the existing literature was analyzed. Plant yield and IENU exhibited substantial variability, averaging 2268 ± 3099 kg/ha and 32.3 ± 92.5 kg N/ha, respectively. Ryegrass dominated (73.77%), followed by unspecified grass (10.76%), oats (4.87%), and lettuce (2.02%). Correlation analysis revealed that decomposition duration positively influenced plant yield and IENU (r = 0.42 and 0.44), while temperature and volatile solids had negative correlations. Machine learning models outperformed linear regression in predicting plant yield and IENU, especially after preprocessing to remove missing values and outliers. Random Forest and Cubist models showed strong generalization with high R² (0.79–0.83) for plant yield, while Cubist predicted IENU well in testing, with RMSE = 3.83 and R² = 0.78. These findings highlight machine learning’s ability to analyze complex datasets, improve agricultural decision-making, and optimize food waste utilization. Full article

This study evaluates the predictive performance of advanced machine learning models, including DeepBoost, XGBoost, CatBoost, RF, and MLP, in estimating the Ω₂, Ω₄, and Ω₆ parameters based on a comprehensive set of input variables. Among the models, DeepBoost consistently demonstrated the best performance across the training and testing phases. For the Ω₂ prediction, DeepBoost achieved an R² of 0.974 and accuracy of 99.895% in the training phase, with corresponding values of 0.971 and 99.902% in the testing phase. In comparison, XGBoost ranked second with an R² of 0.929 and accuracy of 99.870% during testing. For Ω₄, DeepBoost achieved a training phase R² of 0.955 and accuracy of 99.846%, while the testing phase results included an R² of 0.945 and accuracy of 99.951%. Similar trends were observed for Ω₆, where DeepBoost obtained near-perfect training phase results (R² = 0.997, accuracy = 99.968%) and testing phase performance (R² = 0.994, accuracy = 99.946%). These findings are further supported by violin plots and correlation analyses, underscoring DeepBoost’s superior predictive reliability and generalization capabilities. This work highlights the importance of model selection in predictive tasks and demonstrates the potential of machine learning for capturing complex relationships in data. Full article

Post-harvest quality and longevity of cut flowers are critical factors influencing customer satisfaction and purchase decisions. Maintaining post-harvest quality and ensuring a long vase life (VL) present significant challenges to the floriculture industry due to the perishable nature of cut flowers. Recent studies have demonstrated the potential of melatonin (MT), a multifunctional biomolecule, to improve the post-harvest quality and longevity of floricultural products. This review highlights recent advances in the application of MT to improve the longevity and post-harvest quality of cut flowers. The physiological, biochemical, and molecular mechanisms underlying MT’s effects, along with various application methods, are discussed. Furthermore, current challenges and knowledge gaps are identified, and future research directions are proposed to explore MT’s potential in diverse flower species and its practical application in the cut flower industry. Full article

Synchronous colorectal cancer (SCRC) is characterized by the simultaneous occurrence of two or more primary colorectal malignancies, diagnosed either preoperatively, intraoperatively, or within six months postoperatively. The rare prevalence of SCRC makes it an uncommon scenario among colorectal malignancies. Since the majority of SCRC patients have been reported to have two concurrent malignancies, triple synchronous malignancies are extremely rare. We report the case of a 65-year-old male individual presenting with a history of abdominal pain, anemia, anorexia, and unintentional weight loss. He was diagnosed with synchronous colorectal cancer with three distinct tumors: two located in the splenic flexure and sigmoid colon, respectively, and another in the rectum that caused partial obstruction. This case highlights the importance of intraoperative evaluation and an appropriate choice of surgical intervention in colorectal cancer. The early identification and proper management of multiple colorectal cancers remain essential for better survival rates. Full article

The architectural legacy of the French colonial period forms a key part of Vietnam’s urban identity, especially in Hue. Yet, this heritage is rapidly declining: from over 240 structures in 2000, fewer than 100 remain today. This study introduces a heritage-based evaluation framework to assess and preserve French colonial buildings using Le Loi Street, Hue’s historic “Western quarter” as a pilot site. Fourteen colonial-era buildings were systematically assessed through field surveys and expert consultation. A total of 40 specialists participated in the criteria development process, and eight selected experts conducted detailed building evaluations. The final framework includes three main categories and nine specific criteria, based on a 100-point scale, incorporating architectural integrity, historical and cultural significance, contextual fit, and adaptive reuse potential. The results show that all the surveyed buildings qualify as Group A or B, warranting strict conservation or minimal renovation. The study emphasizes the value of localized, expert-informed approaches to heritage planning. The research provides a practical foundation for integrating historic architecture into context-sensitive urban conservation strategies in Hue and comparable Southeast Asian contexts. Full article