Search Results (55)

Background: The therapeutic potential of natural products in cognitive disabilities has drawn growing attention, yet a comprehensive analysis of trends and key contributors is lacking. This study provides a bibliometric overview highlighting growth patterns, themes, and future directions. Methods: A comprehensive Scopus search with multistep filtering was conducted by applying keywords related to natural products and cognitive disabilities to titles, abstracts, and keywords, initially retrieving 10,011 documents. Filters for original articles and English language reduced the results to 5688. Data extracted in October 2024 were analyzed using Excel and the R-package, yielding performance and citation indices. Differential proliferation was visualized using a Sankey diagram, while thematic maps highlighted key research themes, geographic trends, and subject clusters. Results: The field exhibited an annual growth rate of 12.36% from 1971 to 2024, with 2021 being the most productive year (497 articles). In recent decades, citation metrics have highlighted significant impacts. Thematic maps and Sankey diagrams revealed the research focus, geographic trends, and collaboration. Alzheimer’s disease dominates the field, alongside topics such as oxidative stress, neuroprotection, and molecular docking. Emerging trends include ferroptosis, UPLC-Q-TOF-MS, and network pharmacology, which have marked advancements in therapeutic and computational approaches. Conclusions: This analysis underscores the dynamic and interdisciplinary nature of this field, highlighting areas for future exploration, particularly underrepresented cognitive disorders and novel therapeutic approaches. Full article

This article presents an integrative review of the role of the 7S-Based Feeding framework (Healthy, Sustainable, Safe, Social, Sovereign, Solidary, and Satisfactory) and its relationship with the One Health approach and human development in Latin America. Through an analysis of 18 articles selected via the PRISMA methodology and coded using ATLAS.ti, thematic patterns and analytical gaps were identified using Sankey diagrams and qualitative content analysis. The results indicate that the dimensions most frequently addressed were Sustainable, Healthy, Safe, and Social. In contrast, the Sovereign and Solidarity-based dimensions were underrepresented, while the Satisfactory dimension was entirely absent. Only one-third of the articles explicitly applied the One Health framework. The study proposes a theoretical integration of these approaches to enhance the understanding of food systems as determinants of well-being. It concludes that incorporating the 7S-Based Feeding framework into public food policies could strengthen their impact on equity, health, and resilience in Latin American communities. Full article

Background/Objectives: The place where a person dies serves as an indicator of end-of-life care quality. This study aims to identify the congruence of place of death (POD) and the reasons behind decision-making among terminally ill cancer patients in East Asia. Methods: We conducted a prospective multicenter cohort study in palliative care units in Japan, Korea, and Taiwan. Data were collected by the responsible physicians during routine clinical practice. Sankey diagrams were applied to present changes in reasons for POD incongruence. Results: A total of 2638 participants from 37 palliative care units in the three countries were enrolled, and most of them died at PCUs (Japan: 95.7%, Korea: 94%, Taiwan: 82%, p < 0.05). The congruence rate of the preferred and actual POD among PCU inpatients ranged from 70% to 80%. Availability of end-of-life care is the most common reason for preferred and eventual PCU death (78.6%, 72.2%, and 52.1%, respectively, p < 0.05). However, 13–22% of patients admitted to PCUs still preferred to die at home, for which traditional culture (20.2%, 40.8%, and 82%, respectively, p < 0.05) or family influence (44.4%, 38.8%, and 51.7%, respectively, p > 0.05) are the main reasons. Cultural and environmental factors, such as influences from family members’ preferences in the three countries or the ownership of housing/housing settings in Japan, are the main challenges in achieving POD congruence. Conclusions: Culturally inclusive strategies in clinical practice and policy implementation for identifying the preferred POD, enhancing communication among stakeholders, and facilitating transitional support may improve the quality of goal-concordant care. Full article

The Netherlands has established climate-adaptive strategies shaped by its long history of water-related climate events, such as the floods in 1421 and 1953. UNESCO World Heritage (WH) properties in The Netherlands reflect centuries of human intervention and natural processes to adapt and mitigate climate challenges, including spatial design and hydraulic engineering. The Dutch Climate Research Initiative also highlights cultural heritage as an integral component in preparing for the 2026 National Climate Adaptation Strategy. This article aims to unveil climate-adaptive World Heritage management strategies (CAWHMSs), using WH properties in The Netherlands as a case study. It collects textual data from Statements of Outstanding Universal Value, State of Conservation Reports by the State Parties and management plans. Through qualitative coding and keywords aggregation of the documents, the visualised results of a Sankey diagram and two semantic networks confirmed two CAWHMSs: conservation and developing WH properties as collaborative knowledge hubs. Conservation supports regulating urban climate and sustainable water management. As collaborative knowledge hubs, multidisciplinary sectors explore opportunities to align WH properties with broader sustainable development initiatives. They also deepen younger generations’ awareness of cultural and natural significance relevant to mitigating climate threats. The results emphasise WH as a contributor to climate adaptation. Cross-sectoral stakeholders can advance holistic climate adaptation efforts using CAWHMSs. Full article

Background: Interstitial cystitis/bladder pain syndrome (IC/BPS) is a chronic condition characterized by persistent bladder-related pain and urinary symptoms, often refractory to conventional treatments. Sacral neuromodulation (SNM) has emerged as a promising therapeutic option for managing refractory IC/BPS. Methods: This retrospective study included 24 patients with IC/BPS treated with SNM between 2017 and 2022. Baseline and follow-up data were collected on pain, opioid use, urinary symptoms, and quality of life. Patients underwent a trial of tonic stimulation before permanent implantation. Continuous variables were reported as median (IQR) and categorical data as counts and percentages. Pre- and post-SNM differences were analyzed using the Wilcoxon rank-sum test. Kaplan–Meier analysis evaluated lead survival, and a Sankey diagram illustrated employment status transitions. Results: Patients had a median age of 54.5 years (IQR: 47–61), with 92% female. Subtypes included Type 1 IC/BPS (8.3%), Type 2 (45.8%), Type 3 (37.6%), and unknown type (8.3%). Median pain duration was 4.5 years (IQR: 3–7.3). SNM resulted in significant improvements in pain (NRS: baseline 8 [IQR: 8–9], last follow-up 3 [IQR: 2–4], p < 0.0001), opioid use (MME: baseline 20 [IQR: 10–40], last follow-up 0 [IQR: 0–10], p < 0.0001), urinary function (24-h voids: baseline 19 [IQR: 14.5–25.8], last follow-up 8 [IQR: 6–12], p < 0.0001), and quality of life (QOL) (EQ-5D-5L: baseline 0.50 [IQR: 0.36–0.56], last follow-up 0.83 [IQR: 0.76–0.89], p < 0.0001). Employment rates increased from 43.5% to 50%, and unemployment decreased from 8.7% to 4.2%. The median follow-up was 35 months (IQR: 28–53). Conclusions: SNM significantly improved pain, urinary symptoms, quality of life, and employment outcomes in patients with refractory IC/BPS. These findings highlight its efficacy as a minimally invasive and reversible option for managing this challenging condition. Full article

In this paper, we investigated the role of generative AI in education in academic publications extracted from Web of Science (3506 records; 2019–2024). The proposed methodology included three main streams: (1) Monthly analysis trends; top-ranking research areas, keywords and universities; frequency of keywords over time; a keyword co-occurrence map; collaboration networks; and a Sankey diagram illustrating the relationship between AI-related terms, publication years and research areas; (2) Sentiment analysis using a custom list of words, VADER and TextBlob; (3) Topic modeling using Latent Dirichlet Allocation (LDA). Terms such as “artificial intelligence” and “generative artificial intelligence” were predominant, but they diverged and evolved over time. By 2024, AI applications had branched into specialized fields, including education and educational research, computer science, engineering, psychology, medical informatics, healthcare sciences, general medicine and surgery. The sentiment analysis reveals a growing optimism in academic publications regarding generative AI in education, with a steady increase in positive sentiment from 2023 to 2024, while maintaining a predominantly neutral tone. Five main topics were derived from AI applications in education, based on an analysis of the most relevant terms extracted by LDA: (1) Gen-AI’s impact in education and research; (2) ChatGPT as a tool for university students and teachers; (3) Large language models (LLMs) and prompting in computing education; (4) Applications of ChatGPT in patient education; (5) ChatGPT’s performance in medical examinations. The research identified several emerging topics: discipline-specific application of LLMs, multimodal gen-AI, personalized learning, AI as a peer or tutor and cross-cultural and multilingual tools aimed at developing culturally relevant educational content and supporting the teaching of lesser-known languages. Further, gamification with generative AI involves designing interactive storytelling and adaptive educational games to enhance engagement and hybrid human–AI classrooms explore co-teaching dynamics, teacher–student relationships and the impact on classroom authority. Full article

This paper presents a Problem-Based Learning (PBL) electrochemistry course contextualized within a real-world problem of wastewater treatment, designed to enhance students’ subject matter knowledge. The sample was a group of chemistry and chemical engineering undergraduate students who were taking an electrochemical course. The research outlines various activities and analyzes five cases of team learning outcomes using Atlas.ti(TM) 22 software. The analysis identifies and describes eight categories of scientific knowledge and practices derived from student reports. The results are represented using a Sankey diagram to show the complexity of students’ thinking after solving their problem. The findings indicate significant progress in students’ conceptual understanding of electrochemistry, the development of complex thinking, and the recognition of its relevance in solving everyday problems. Full article

Academic publications from the Web of Science Core Collection on “e-business” and “artificial intelligence” (AI) are investigated to reveal the role of AI, extract latent themes and identify potential research topics. The proposed methodology includes relevant graphical representations (trends, co-occurrence networks, Sankey diagrams), sentiment analyses and latent topics identification. A renewed interest in these publications is evident post-2018, with a sharp increase in publications around 2020 that can be attributed to the COVID-19 pandemic. Chinese institutions dominate the collaboration network in e-business and AI. Keywords such as “business transformation”, “business value” and “e-business strategy” are prominent, contributing significantly to areas like “Operations Research & Management Science”. Additionally, the keyword “e-agribusiness” recently appears connected to “Environmental Sciences & Ecology”, indicating the application of e-business principles in sustainable practices. Although three sentiment analysis methods broadly agree on key trends, such as the rise in positive sentiment over time and the dominance of neutral sentiment, they differ in detail and focus. Custom analysis reveals more pronounced fluctuations, whereas VADER and TextBlob present steadier and more subdued patterns. Four well-balanced topics are identified with a coherence score of 0.66 using Latent Dirichlet Allocation, which is a probabilistic generative model designed to uncover hidden topics in large text corpora: Topic 1 (29.8%) highlights data-driven decision-making in e-business, focusing on AI, information sharing and technology-enabled business processes. Topic 2 (28.1%) explores AI and Machine Learning (ML) in web-based business, emphasizing customer service, innovation and workflow optimization. Topic 3 (23.6%) focuses on analytical methods for decision-making, using data modeling to enhance strategies, processes and sustainability. Topic 4 (18.5%) examines the semantic web, leveraging ontologies and knowledge systems to improve intelligent systems and web platforms. New pathways such as voice assistance, augmented reality and dynamic marketplaces could further enhance e-business strategies. Full article

Background/Objectives: This study uses Sankey diagrams to analyze treatment pathways in patients with peripheral artery disease (PAD), which is a vascular condition characterized by atherosclerotic occlusion of the arteries, particularly in the lower limbs, affecting up to 14% of the general population. This study focuses on the treatment pathways that lead to amputation versus those that do not, utilizing the STARR dataset and the All of Us dataset. Methods: The study utilized Sankey diagrams to visualize treatment pathways, highlighting the progression from initial treatments to outcomes. Odds ratio analysis was performed to quantify the association between treatment pathways and outcomes. Recognizing potential confounders, analyses were conducted by filtering patients with PAD into subgroups based on these coexisting conditions. Sankey diagrams were then generated for each sub-cohort to visualize treatment pathways. Results: Pathways including antiplatelet and lipid-lowering treatments accounted for 56% of non-amputation cases in the STARR data and 50% in the All of Us data. Amputation pathways frequently included revascularization procedures, representing 15% of amputations in the STARR data and 20% in the All of Us data. Confounder analysis revealed that most amputated PAD patients were over 50 years old and had one or more conditions, such as diabetes, hypertension, or hyperlipidemia. Conclusions: These visualizations provide insights into treatment pathways and their associations with outcomes in PAD patients, highlighting the potential impact of specific treatments on amputation and non-amputation cases. Future work should build on these findings by incorporating predictive models using machine learning techniques to further explore and quantify these relationships. Full article

Background/Objectives: Spinal Phenol IN Glycerol (SPING) block is a novel palliative pain treatment for the non-operative management of proximal femur fractures (PFFs) in older adults living with frailty. Effective pain management that aligns with patient preferences and minimizes opioid use is critical in this setting. This study evaluated the patient, safety, and process outcomes of SPING block in this population. Methods: A retrospective cohort study was conducted in a suburban teaching hospital from March 2021 to June 2024, which included sixty-eight older adults living with frailty that suffered from a PFF and received SPING block. Data were collected from the Electronic Patient Records. The patient living situation was visualized with a Sankey diagram. Changes in pain scores and opioid use were assessed using the Wilcoxon Signed Rank test. Results: The median patient age was 89 years (Interquartile range (IQR) 83–92). Most were severely or terminally ill (American Society of Anesthesiologists (ASA) ≥ 4, 72%) and had cognitive impairment or dementia (68%). SPING block was effective in 93% of patients, significantly reducing median pain scores (4 [IQR 3–5] to 0 [IQR 0–1], p < 0.001) and opioid use (15 mg/day [IQR 4–30] to 0 mg/day [IQR 0–0], p < 0.001). Within 24 h, 84% could sit upright and 44% could transfer between their bed and chair. The median time to discharge was one day (IQR 0–3), with a median survival of 13 days (IQR 7–44). Conclusions: This study supports SPING block as a viable option for older adults living with frailty suffering from a PFF who opt for non-operative management in a palliative setting. SPING block for PFFs in a palliative setting offers effective pain relief, reduces opioid use, and enables mobility for older adults living with frailty. Follow-up is essential to monitor efficacy and safety. Prospective studies are needed to confirm these findings. Full article

In the current work, authors reviewed the latest research results in landslide susceptibility mapping (LSM) using artificial intelligence (AI) methods. Based on an overall review of collected publications, the review was classified into four sections based on their complexity: single-model approaches, enhanced models with optimization, ensemble models, and hybrid models. Each category offers distinct advantages and is suited to specific geographic and data conditions, enabling the selection of an optimal model type based on the complexity and requirements of the mapping task. Among models, random forest (RF), support vector machine (SVM), convolutional neural network (CNN), and multilayer perception (MLP) are used as the baseline to compare any new model introduced to develop LSM. Moreover, compared to previous review works, the number of LSM conditioning factors used in AI models are significantly increased, up to 122 factors. Their relation to the AI models is illustrated using Sankey diagram, while a radar chart is used to further visualize the dataset size per reviewed work for comparative purposes. In the main part of the current review work, the main findings are summarized into a table form, where the reader can find the overall relations between landslide conditioning factors, landslide dataset size, applied AI models, and their accuracy on predicting LSM for selected geographical locations. In terms of the regions, Asia is leading in the application of AI models to generate LSM, and in such regions with dense populations falling into higher landslide risk categories, there are more ongoing research activities, using modern AI methods. This trend underscores the increased use of AI in disaster management, with implications for improving practical applications, such as early warning systems and informing policy decisions aimed at risk reduction in vulnerable areas. Full article

This literature review critically examines the potential of collective intelligence (CI) to enhance theories of deliberative democracy and participatory governance through academic discourse. We employed PRISMA guidelines for systematic article selection, complemented by a narrative approach for in-depth thematic analysis and supplemented by quantitative methodologies such as Sankey diagrams and keyness analysis. Reviewing 61 scholarly articles focusing on CI within the public sector, this study identifies theoretical insights that could significantly impact the field of democratic innovations and participatory governance. Our analysis reveals that CI methodologies can make governance more inclusive and dynamic by integrating advanced digital tools that foster broader and more effective citizen participation. We conclude that integrating CI with deliberative democracy and participatory governance theories holds substantial promise for developing more responsive and adaptive governance models. Future research should focus on measuring deliberative quality in real time, deploying CI tools to empower underrepresented groups and address specific governance challenges, and examining CI’s ethical and social implications, especially concerning privacy, security, and power dynamics in technology-driven public decision-making. Full article

This paper studies the implementation of a system consisting of an electrolyzer connected to a bioelectricity generator set that operates using vinasse biogas. Data on total ethanol production across all regions of Brazil were collected, and two ethanol plants in São Paulo state were selected for analysis (São Jose da Estiva and São Manoel). The feasibility of implementing this system at these facilities was evaluated using energy analysis for biohydrogen production. The process’s energy efficiency was assessed, allowing for the construction of a Sankey Diagram for both plants. Additionally, the costs of producing bioelectricity and biohydrogen via electrolysis using vinasse biogas from Brazil’s sugar/alcohol industry were determined, factoring in the payback period, equivalent utilization period, and annual interest rate. The study demonstrates the efficiency and cost-effectiveness of producing biohydrogen using vinasse biogas. The cost of producing bioelectricity at the two plants decreases significantly over the 25-year system implementation period, starting at around 0.09–0.08 USD/kWh in the first year and dropping to a minimum of 0.027–0.039 USD/kWh by the end of the period. The initial cost of producing biohydrogen ranges from 0.24 to 0.25 USD/kWh at São Jose da Estiva and from 0.30 to 0.32 USD/kWh at São Manoel in the first year. However, prices drop by nearly half in the second year, reaching 0.05 to 0.06 USD/kWh at São Jose da Estiva and 0.06 to 0.07 USD/kWh at São Manoel. The payback period for the biohydrogen and bioelectricity production system increases, with São Jose da Estiva generating income by 1st year for a 4% to 12% interest rate. For São Manoel, income is expected by the 1.5 year for a 4% to 12% interest rate. Both plants recover their investment within the first 2 years of operation. By the 10th year, São Jose da Estiva’s income is projected to be between 3,888,501.96 USD (4%) and 3,678,407.29 USD (12%), while São Manoel’s income is expected to range from 3,123,824.69 USD (4%) to 2,932,050.63 USD (12%), demonstrating that the system is viable for sugar and ethanol plants. Full article

Infrastructures enable economic growth and job creation and improve quality of life. Therefore, infrastructure should be resilient to natural hazards and other challenges. This paper presents a bibliometric and network analysis of 6596 articles, published between 1977 and 2024, extracted from the Scopus database by using “Infrastructure AND Resilience” as the keyword. VOSviewer and Biblioshiny are used to generate analyses such as the co-authorship, co-occurrences, bibliographic coupling, co-citation, and Sankey diagram. This paper also emphasizes principles of infrastructure resilience such as flexibility, adaptability, agility, robustness, survivability, redundancy, and so on. The outcomes of this research can be utilized by future researchers, policymakers, governments, and industrialists for resilient infrastructure. Full article

With so many studies today on the water quality of the sea, one can hardly comprehend the multitude of topics that arise all over the world. This study provides a few graphic syntheses related to the most frequent words (including their clustering and links), trend topics, the spatial distribution of the researched areas, and the thematic evolution of the research directions over the decades. The most frequent authors’ keywords have a 50% similitude between the ocean studies and the studies related to the Mediterranean Sea; these keywords are part of a causal chain that dominates the marine studies on water quality: nutrients → eutrophication → phytoplankton → chlorophyll → seagrass. The most frequent words in the titles and abstracts of the selected papers from the Web of Science are “concentration” and “species”; in the Mediterranean studies, “chlorophyll” and “temperature” are the most frequent. In close connection with water quality, Zostera marina (eelgrass) and Crassotrea virginica (eastern oyster) prevail at the global scale, while Posidonia oceanica (Neptune grass) is relevant in the Mediterranean space. Some of the most studied water bodies are the South China Sea, San Francisco Bay, Chesapeake Bay, and, in the Mediterranean Sea, the Adriatic, Ionian, Aegean, and Marmara seas. “Climate change” and “remote sensing” are trend topics that shape the current studies on water quality; the increasing sea surface temperature enhances algal blooms—these need to be monitored using satellite imagery for the sustainable evolution of human activities, including aquaculture. Full article