Search Results (3,893)

Fractional differential equations have emerged as a prominent focus of modern scientific research due to their advantages in describing the complexity and nonlinear behavior of many physical phenomena. In particular, when considering problems with initial-boundary value conditions, the solution of nonlinear fractional differential equations becomes particularly important. This paper aims to explore the fractional soliton solutions for the three-component fractional nonlinear Schrödinger (TFNLS) equation under the zero background. According to the Lax pair and fractional recursion operator, we obtain fractional nonlinear equations with Riesz fractional derivatives, which ensure the integrability of these equations. In particular, by the completeness relation of squared eigenfunctions, we derive the explicit form of the TFNLS equation. Subsequently, in the reflectionless case, we construct the fractional N-soliton solutions via the Riemann–Hilbert (RH) method. The analysis results indicate that as the order of the Riesz fractional derivative increases, the widths of both one-soliton and two-soliton solutions gradually decrease. However, the absolute values of wave velocity, phase velocity, and group velocity of one component of the vector soliton exhibit an increasing trend, and show power-law relationships with the amplitude. Full article

Multi-source information fusion is a key challenge in uncertainty reasoning. Dempster–Shafer evidence theory (D-S evidence theory) offers a flexible framework for representing and fusing uncertain information. However, the classical Dempster’s combination rules may yield counter-intuitive results when faced with highly conflicting evidence. To overcome this limitation, we introduce a cluster-level information fusion framework, which shifts the focus from pairwise evidence comparisons to a more holistic cluster-based perspective. A key contribution is a novel cluster–cluster divergence measure that jointly captures the strength of belief assignments and structural differences between clusters. Guided by this measure, a reward-driven evidence assignment rule dynamically allocates new evidence to enhance inter-cluster separability while preserving intra-cluster coherence. Building upon the resulting structure, we propose a two-stage information fusion algorithm that assigns credibility weights at the cluster level. The effectiveness of the framework is validated through a range of benchmark pattern classification tasks, in which the proposed method not only improves classification accuracy compared with D-S evidence theory methods but also provides a more interpretable, cluster-oriented perspective for handling evidential conflict. Full article

Background: Electroencephalographic (EEG) neurofeedback training is gaining traction as a non-pharmacological treatment option for Parkinson’s disease (PD). This paper reports the first pre-registered, integrated systematic review and meta-analysis of studies examining the effects of EEG neurofeedback on cortical activity and motor function in people with PD. Method: We searched Cochrane Databases, PubMed, Embase, Scopus, Web of Science, PsycInfo, grey literature repositories, and trial registers for EEG neurofeedback studies in people with PD. We included randomized controlled trials, single-group experiments, and case studies. We assessed risk of bias using the Cochrane Risk of Bias 2 and Risk of Bias in Non-Randomized Studies tools, and we used the Grading of Recommendations, Assessment, Development and Evaluations tool to assess certainty in the evidence and resultant interpretations. Random-effects meta-analyses were performed. Results: A total of 11 studies (143 participants; Hoehn and Yahr I–IV) met the criteria for inclusion. A first meta-analysis revealed that EEG activity is modified in the prescribed way by neurofeedback interventions. The effect size is large (SMD = 1.30, 95% CI = 0.50–2.10, p = 0.001). Certainty in the estimate is high. Despite successful cortical modulation, a subsequent meta-analysis revealed inconclusive effects of EEG neurofeedback on motor symptomology. The effect size is small (SMD = 0.10, 95% CI = −1.03–1.23, p = 0.86). Certainty in the estimates is low. Narrative evidence revealed that interventions are well-received and may yield specific benefits not detected by general symptomology reports. Conclusion: EEG neurofeedback successfully modulates cortical activity in people with PD, but downstream impacts on motor function remain unclear. The neuromodulatory potential of EEG neurofeedback in people with PD is encouraging. Additional well-powered and high-quality research into the effects of EEG neurofeedback in PD is warranted. Full article

Accurate prediction of food delivery time is crucial for enhancing operational efficiency and customer satisfaction in real-world logistics and intelligent dispatch systems. To address this challenge, this study proposes a novel symmetric optimization prediction framework, termed SymOpt-CNSVR. The framework is designed to leverage the strengths of both deep learning and statistical learning models in a complementary architecture. It employs a Convolutional Neural Network (CNN) to extract and assess the importance of multi-feature data. An Enhanced Superb Fairy-Wren Optimization Algorithm (ESFOA) is utilized to optimize the diverse hyperparameters of the CNN, forming an optimal adaptive feature extraction structure. The significant features identified by the CNN are then fed into a Support Vector Regression (SVR) model, whose hyperparameters are optimized using Bayesian optimization, for final prediction. This combination reduces the overall parameter search time and incorporates probabilistic reasoning. Extensive experimental evaluations demonstrate the superior performance of the proposed SymOpt-CNSVR model. It achieves outstanding results with an R² of 0.9269, MAE of 3.0582, RMSE of 4.1947, and MSLE of 0.1114, outperforming a range of benchmark and state-of-the-art models. Specifically, the MAE was reduced from 4.713 (KNN) and 5.2676 (BiLSTM) to 3.0582, and the RMSE decreased from 6.9073 (KNN) and 6.9194 (BiLSTM) to 4.1947. The results confirm the framework’s powerful capability and robustness in handling high-dimensional delivery time prediction tasks. Full article

Liposomes, nanoscale vesicles with distinct structural and functional properties, are widely utilized in drug delivery due to their biocompatibility and ability to encapsulate diverse therapeutic agents. Effective sterilization is essential to ensure the safety and efficacy of liposomal formulations in biomedical applications, yet its impact on liposome integrity and functionality remains inadequately studied. This work systematically evaluates the effects of three sterilization methods: autoclaving, UV radiation, and filtration—on liposomes composed of dipalmitoylphosphatidylcholine (DPPC) and distearoylphosphatidylcholine (DSPC), two phospholipids differing in lipid chain length. Sterilization altered liposome properties in a lipid chain length-dependent manner, affecting particle size, zeta potential, and phospholipid content. Filtration caused significant hydrocarbon loss, confirmed by Fourier-transform infrared spectroscopy (FTIR) and Raman spectroscopy, and led to a higher reduction in phospholipid content in DPPC liposomes compared to DSPC liposomes. Biological evaluations showed that autoclaved and UV-irradiated DPPC liposomes exhibited higher cytotoxic and lower stability than their DSPC counterparts. While autoclaving and UV irradiation resulted in minimal chemical alterations, both methods significantly influenced biological properties. Filtration, although less disruptive to biocompatibility, also reduced key liposomal integrity and efficacy. This study underscores the critical importance of post-sterilization evaluation to optimize liposomal formulations for clinical and biomedical use. Full article

Several approaches are currently being used by law enforcement to locate the remains of victims. Yet, traditional methods are invasive and time-consuming. Unmanned Aerial Vehicle (UAV)-based remote sensing has emerged as a potential tool to support the location of human remains and clandestine graves. While offering a non-invasive and low-cost alternative, UAV-based remote sensing needs to be tested and validated for forensic case work. To assess current knowledge, a systematic review of 19 peer-reviewed articles from four databases was conducted, focusing specifically on UAV-based remote sensing for human remains and clandestine grave location. The findings indicate that different sensors (colour, thermal, and multispectral cameras), were tested across a range of burial conditions and models (human and mammalian). While UAVs with imaging sensors can locate graves and decomposition-related anomalies, experimental designs from the reviewed studies lacked robustness in terms of replication and consistency across models. Trends also highlight the potential of automated detection of anomalies over manual inspection, potentially leading to improved predictive modelling. Overall, UAV-based remote sensing shows considerable promise for enhancing the efficiency of human remains and clandestine grave location, but methodological limitations must be addressed to ensure findings are relevant to real-world forensic cases. Full article

This work suggests a new use for the Non-Monopolize Optimization (NO) method to improve the dynamic stability and robustness of PID and PIDA controllers in Automatic Voltage Regulator (AVR) systems when there are load disruptions. The NO algorithm is a new search method that does not use metaphors and only looks for one answer. It utilizes adaptive dimension modifications to strike a balance between exploration and exploitation. Its addition to AVR control makes parameter tweaking more efficient, without relying on random metaphors or population-based heuristics. MATLAB/Simulink R2025a runs full simulations to check how well the system works in both the time domain (step response, root locus) and the frequency domain (Bode plot). We compare the results to those of well-known optimizers like WOA, TLBO, ARO, GOA, and GA. The suggested NO-based PID and PIDA controllers always show less overshoot, faster rise and settling periods, and higher phase and gain margins, which proves that they are more stable and responsive. A robustness test with a load change of ±50% shows that NO-tuned controllers are even more reliable. The results show that using NO to tune different controllers could be a good choice for real-time AVR controller tuning in modern power systems because it is lightweight and works well. Full article

Urban heat islands are intensifying under the dual pressures of global climate change and rapid urbanization, posing serious challenges to ecological sustainability and human well-being. Among the factors influencing urban thermal environments, vegetation and green spaces play a critical role in mitigating heat accumulation through canopy cover, evapotranspiration, and ecological connectivity. In this study, a comparative analysis of Seoul and Busan—two representative metropolitan areas in South Korea—was conducted using land surface temperature (LST) data derived from Landsat 8 and a set of multi-source spatial indicators. The nonlinear effects and interactions among built environment, socio-economic, and ecological variables were quantified using the Extreme Gradient Boosting (XGBoost) model in conjunction with Shapley Additive Explanations (SHAP). Results demonstrate that vegetation, as indicated by the Normalized Difference Vegetation Index (NDVI), consistently exerts significant cooling effects, with a pronounced threshold effect observed when NDVI values exceed 0.6. Furthermore, synergistic interactions between NDVI and surface water availability, measured by the Normalized Difference Water Index (NDWI), substantially enhance ecological cooling capacity. In contrast, areas with high building and population densities, particularly those at lower elevations, are associated with increased LST. These findings underscore the essential role of green infrastructure in regulating urban thermal environments and provide empirical support for ecological conservation, urban greening strategies, and climate-resilient urban planning. Strengthening vegetation cover, enhancing ecological corridors, and integrating greening policies across spatial scales are vital for mitigating urban heat and improving climate resilience in rapidly urbanizing regions. Full article

Accurate calculation of embodied carbon emissions in buildings (ECE) is crucial to achieving global carbon neutrality. However, fragmented data, inconsistent regional standards, and low computational efficiency have long hindered existing methods. This study innovatively integrates large language models (LLMs) with retrieval-enhanced generation (RAG) technology to establish a new intelligent accounting paradigm for embodied carbon in buildings. Through a systematic evaluation of three basic models—Kimi, Doubao, and DeepSeek-R1—in a five-level progressive input scenario, the study quantitatively reveals the “information sensitivity” patterns of LLMs. To address the illusion errors of general models in professional scenarios, an innovative three-stage closed-loop architecture of “knowledge retrieval—calculation embedding—trustworthy generation” is proposed. By dynamically invoking domain knowledge bases and embedded computing modules, zero-error verification of benchmark data is achieved. The core contributions include the following: (1) It has been clarified that the basic large model has application potential in calculating the implicit carbon emissions of buildings, but the reliability of the results is limited. (2) The influence of data elements on calculation accuracy is revealed. (3) The application path for integrating RAG with large models has been pioneered, and the results show that the RAG technology can enhance the performance of large models in calculating the implicit carbon emissions of buildings by approximately 25%. (4) The significant efficiency improvement of RAG technology is verified. (5) A supporting theoretical and application system is established. Full article

Uveal melanoma (UM) is the most common primary intraocular malignancy in adults, associated with a high tendency for metastasis to the liver. Proton beam therapy (PBT) is the preferred external radiotherapy treatment for primary UM of certain sizes and locations in the eye, due to its efficacy and good local tumour control, as well as its precision to spare surrounding ocular structures. PBT is an effective alternative to surgical enucleation and other non-precision-targeted radiotherapies. Despite this, the radiobiology of UM in response to PBT is still not fully understood. This enhanced knowledge would help to further optimise UM treatment and improve patient outcomes through reducing radiation dosage to ocular structures, treating larger tumours that would otherwise require enucleation, or even offering a treatment strategy for the otherwise fatal liver metastases. In this review, we explore current knowledge of the treatment of UM with PBT, evaluating the biological responses to the therapy. Molecular factors, such as tumour size, oxygen tension levels, DNA damage proficiency, and autophagy, are known to influence the cellular response to radiotherapy, and these will be discussed. Furthermore, we examine innovative strategies to enhance radiotherapy outcomes, such as combination therapies with DNA damage repair and autophagy modulators, as well as advancements in PBT planning and delivery. By integrating current research and emerging technologies, we aim to provide opportunities to improve the therapeutic effectiveness of PBT in UM management. Full article

Two critical research problems emerge in creative education quality management: the framework misalignment problem, where business-oriented performance metrics inadequately assess design creativity and innovation, and the sustainability integration gap, reflecting limited incorporation of environmental and social sustainability dimensions into excellence models. This review article addresses these problems by developing an initial framework that adapts the Baldrige framework for urban design, architecture, art, and design education with integrated sustainability principles. Drawing on literature review and theoretical synthesis, the article proposes a framework that introduces three key epistemological shifts: prioritizing process over product, supporting non-linear and reflective learning pathways, and recognizing tacit, embodied, and experiential knowledge as central to creative education. The framework incorporates the United Nations Sustainable Development Goals (SDGs) as core design challenges and introduces innovative evaluation tools, including portfolios with iterative review processes, community feedback loops, and SDG mapping rubrics. This research contributes to the educational quality management literature by offering a systematic framework that bridges business excellence models with creative education paradigms while positioning sustainability as a core educational objective rather than a peripheral concern. Full article

Background: Following vitamin D₃ oral administration, attained serum concentrations of its metabolite 25-hydroxyvitamin D₃ (25(OH)D₃) are variable among children. Methods: We developed physiologically based pharmacokinetic (PBPK) modelling using annually measured serum 25(OH)D₃ concentrations in 77 Cape Town schoolchildren aged 6–11 years who received weekly oral doses of 10,000 IU vitamin D₃ for 3 years during a clinical trial (Δ25(OH)D = 32.2 nmol/L, 95% CI: [−3.2, 65.8] nmol/L). Simulations were performed to test the model on 463 other participants in the same trial, and in a cohort of 1756 Mongolian schoolchildren aged 6–11 years who received weekly oral doses of 14,000 IU vitamin D₃ for 3 years in another trial. Results: The best model attributed most of the variability in post-supplementation 25(OH)D₃ concentrations to hepatic clearance and covariates including weight (ΔAIC = −21) and ZBMI (body mass index Z-score, ΔAIC = −34). For 463 other children from the Cape Town trial (Δ25(OH)D = 25.8 nmol/L, 95% CI: [8.3, 47.2] nmol/L), mean estimation error was 5.3 nmol/L, and 76.7% of observations were within the 95% prediction intervals. Our simulation supported the previous proposal that serum 25(OH)D₃ should exceed 50 nmol/L among 97.5% of European children at 24.4 μg/day vitamin D₃ dosing. At a higher weekly dose (14,000 IU), the Mongolian children demonstrated a higher average increase in serum 25(OH)D₃ (40.6 [−2.9, 88.9] nmol/L) but were overestimated by the model. Conclusion: We developed the first PBPK model to successfully predict the long-term serum 25(OH)D₃ increases in healthy schoolchildren in Cape Town who received orally administered vitamin D₃ and exhibited higher relative increases than Mongolian children. Full article

Introduction: Oral health problems are prevalent among people receiving palliative care, affecting their quality of life. However, little is known about dental practitioners’ perspectives in this setting. Thus, this study aimed to explore the perceptions of public dental practitioners regarding the provision of dental care for people who receive palliative care. Methods: An exploratory focus group with 21 public dental practitioners, with a mean of 8.24 years of experience, was conducted in a public oral health service in Sydney, Australia. The focus group was transcribed and analysed using thematic analysis. Results: Three themes were identified: (1) enhancing quality of life in palliative care through improved oral health; (2) navigating the systemic and practical challenges of palliative dental care; (3) competent, collaborative, and optimised: a palliative oral care model. Participants highlighted the importance of oral health to quality of life while receiving palliative care. Nevertheless, there were several systematic and practical challenges to delivering appropriate dental care, which included competing priorities among clients, disconnects and gaps in care coordination with palliative care providers, limited training, and adapting treatment planning during appointments. Participants highlighted the need for a new model of care in the future that improved dental practitioners’ competence through comprehensive palliative dental training, included protocols to facilitate interdisciplinary collaboration, and optimised dental treatment planning and appointment scheduling. Conclusions: Public dental practitioners in this study demonstrated positive attitudes, but systemic barriers and limited training restrict their care provision. A palliative oral health care model for this setting should include palliative dental training, foster interdisciplinary collaboration, and optimise dental treatment planning. Full article

This research investigates the influence of incorporating perlite aggregate and silica fume on the properties of cement mortar, with a focus on compressive strength, flexural strength, density, water absorption, and thermal conductivity. The results show that increasing the percentage of perlite (Pe) in the mixes causes a marked reduction in the compressive strength, reflecting the lightweight nature and low density of perlite. For mixes with Pe-20% through Pe-100%, the compressive strength decreased by up to 78% compared to the reference mix. However, the addition of silica fume (SF) in mixes with SF-20% to SF-100% partially offset this effect, limiting the strength losses to 18–71%, which indicates that silica fume contributes to strength enhancement over time. The flexural strength followed a similar trend, decreasing with a higher perlite content: reductions of up to 40% were observed for Pe mixtures, while SF mixes showed slightly smaller decreases, reaching 36%. The density also declined consistently with increasing perlite replacement, with a maximum reduction of 57% in mix Pe-100% due to the inherent porosity of perlite. The water absorption increased substantially in the same mix (Pe-100%), by 327% compared to the reference one, whereas the addition of silica fume (SF-100%) limited the increase to 181%, confirming its role in refining the pore structure. The thermal conductivity decreased with a higher perlite content, attributed to the formation of voids in the matrix. The lowest value was observed for Pe-100%, with an 82% reduction, while silica fume mixes also showed reductions of 37–81% relative to the reference mix. Based on a comprehensive evaluation of strength, density, water absorption, and thermal performance, mix SF-60% was identified as the optimal mixture, offering a balanced profile with a compressive strength of 4.4 MPa, thermal conductivity of 0.28 W/(m·K), and density of 1089 kg/m³. These performance levels make the developed mortars particularly suitable for non-load-bearing masonry units, lightweight blocks, and insulation panels, where reduced weight and enhanced thermal efficiency are essential. The study therefore provides practical guidance for the design of sustainable, lightweight mortars for energy-efficient construction applications. Full article

This exploratory study investigates how youths aged 18–25 perceive and prioritize elements of the Integrated Digital Storytelling for Social Media (IDSM) framework in cultural heritage tourism contexts, addressing critical gaps between theoretical frameworks and contemporary social media engagement requirements. Through purposive sampling at cultural heritage tourism sites in Bangkok, Thailand, questionnaires were distributed to 100 participants to examine their preferences for cultural tourism video content and validate framework elements. Cultural authenticity emerged as the paramount consideration among participants, while traditional storytelling elements demonstrated sustained relevance when adapted for social media contexts. Youth participants preferred authentic mobile phone recordings over professional production, with optimal video durations and caption-dependent storytelling for mobile consumption. TikTok emerged as the primary motivational platform despite moderate usage frequency patterns. This exploratory study contributes preliminary empirical assessment of an integrated framework specifically designed for social media applications in cultural heritage tourism contexts. The findings provide evidence-based guidelines to help practitioners develop platform-optimized content strategies that effectively engage youth audiences while maintaining cultural authenticity. Full article