Search Results (142)

Amid the dual imperatives of global trade expansion and low-carbon transition, intelligent maritime shipping has emerged as a central driver for the innovation of international logistics systems, now entering a critical window period for the deep integration of Internet technologies and automated port infrastructure. While existing research predominantly focuses on isolated applications of intelligent technologies, systematic evaluations of the synergistic effects of technological integration on maritime ecosystems, policy compatibility, and contributions to global carbon emission governance remain under-explored. Leveraging bibliometric analysis, this study systematically examines 488 publications from the Web of Science (WoS) Core Collection (2000–2024), yielding three pivotal findings: firstly, China dominates the research landscape, with a 38.5% contribution share, where Artificial Intelligence (AI), the Internet of Things (IoT), and port automation constitute the technological pillars. However, critical gaps persist in cross-system protocol standardization and climate-adaptive modeling, accounting for only 2.7% and 4.2% of the literature, respectively. Secondly, international collaboration networks exhibit pronounced “Islamization”, characterized by an inter-team collaboration rate of 17.3%, while the misalignment between rapid technological iteration and existing maritime regulations exacerbates industry risks. Thirdly, a dual-track pathway integrating Cyber–Physical System (CPS)-based digital twin ports and open-source vertical domain-specific large language models is proposed. Empirical evidence demonstrates its efficacy in reducing cargo-handling energy consumption by 15% and decision-making latency by 40%. This research proposes a novel tripartite framework, encompassing technological, institutional, and data sovereignty dimensions, to resolve critical challenges in integrating multi-source maritime data and managing cross-border governance. The model provides academically validated and industry-compatible strategies for advancing sustainable maritime intelligence. Subsequent investigations should expand data sources to include regional repositories and integrate interdisciplinary approaches, ensuring the adaptability of both technical systems and international policy coordination mechanisms across diverse maritime ecosystems. Full article

Although the accumulated knowledge repository of the Corporate Responsibility (CR) literature continues to expand, organizational- and institutional-level studies dominate the field. This article addresses this gap by introducing a driver-based approach to CR through the moral mapping of CR policies and theory-building case studies in the textile sector. Considering the CR notion’s diverse stakeholder involvement and cross-disciplinary nature, process tracing of diverse actors from the Industrial Revolution is conducted. A reconstituted Kantian method is employed to assess the moral responsibility of individual agents. Employing this technique, the study categorizes diverse policies and strategies based on decision-makers and the most probable ethical thought processes, or “maxims”, at the time of the decision-making. The findings identify gaps in conventional CR practices, giving rise to CSR-washed actions and irresponsible corporate behavior. To tackle these challenges, we introduce the Corporate Local Responsibility (COLOR) model. This model is based on moral mapping by integrating them into its four pillars to minimize the ethical dilemmas of various actors by engaging broader stakeholders and local communities in the decision-making process. Full article

Background/Objectives: 3D printing has become an invaluable tool in medicine, enabling the creation of precise anatomical models for surgical planning and medical education. This study presents a comprehensive protocol for converting DICOM files into three-dimensional models and their subsequent transformation into GCODE files ready for 3D printing. Methods: We employed the open-source software “3D Slicer” for the initial conversion of the DICOM files, capitalising on its robust capabilities in segmentation and medical image processing. An optimised workflow was developed for the precise and efficient conversion of medical images into STL models, ensuring high fidelity in anatomical structures. The protocol was validated through three case studies, achieving elevated structural fidelity based on deviation analysis between the STL models and the original DICOM data. Furthermore, the segmentation process preserved morphological accuracy within a narrow deviation range, ensuring the reliable replication of anatomical features for medical applications. Our protocol provides an effective and accessible approach to generating 3D anatomical models with enhanced accuracy and reproducibility. In later stages, we utilised the “Ultimaker Cura” software to generate customised GCODE files tailored to the specifications of the 3D printer. Results: Our protocol offers an effective, accessible, and more accurate solution for creating 3D anatomical models from DICOM images. Furthermore, the versatility of this approach allows for its adaptation to various 3D printers and materials, expanding its utility in the medical and scientific community. Conclusions: This study presents a robust and reproducible approach for converting medical data into physical three-dimensional objects, paving the way for a wide range of applications in personalised medicine and advanced clinical practice. The selection of sample datasets from the 3D Slicer repository ensures standardisation and reproducibility, allowing for independent validation of the proposed workflow without ethical or logistical constraints related to patient data access. However, we acknowledge that future work could expand upon this by incorporating real patient datasets and benchmarking the protocol against alternative segmentation methods and software packages to further assess performance across different clinical scenarios. Essentially, this protocol can be particularly characterised by its commitment to open-source software and low-cost solutions, making advanced 3D modelling accessible to a wider audience. By leveraging open-access tools such as “3D Slicer” and “Ultimaker Cura”, we democratise the creation of anatomical models, ensuring that institutions with limited resources can also benefit from this technology, promoting innovation and inclusivity in medical sciences and education. Full article

Background: The COVID-19 pandemic highlighted SARS-CoV-2 variants with increased transmissibility and immune evasion. In Ethiopia, where cases surged, the understanding of the virus’s dynamics was limited. This study analyzed SARS-CoV-2 variants during the fifth wave, crucial for guiding vaccines, therapeutics, diagnostics, and understanding disease severity. Method: From June to August 2022, 150 SARS-CoV-2-positive samples were randomly selected from the Ethiopian Public Health Institute repository. Sixty-three high-quality genome sequences were analyzed. Results: Of the 63 sequences, 70% were from males and 30% from females, with a median age of 34. Omicron dominated (97%, 61/63), primarily clade 22A (64%, 40/63), followed by 22B (18%, 11/63) and 21K (14%, 9/63). Delta accounted for 3.2% (2/63). Omicron was identified in all (25) vaccinated study participants. Ethiopian sequences showed limited evolutionary divergence and lower genetic diversity compared to global sequences. Conclusion: Omicron was the predominant variant during Ethiopia’s fifth wave, indicating recent community transmission. Despite minor genetic diversity differences, ongoing surveillance remains critical for tracking variants and informing public health interventions. Full article

Preliminary activities of searching and selecting relevant articles are crucial in scientific research to determine the state of the art (SOTA) and enhance overall outcomes. While there are automatic tools for keyword extraction, these algorithms are often computationally expensive, storage-intensive, and reliant on institutional subscriptions for metadata retrieval. Most importantly, they still require manual selection of literature. This paper introduces a framework that automates keyword searching in article abstracts to help select relevant literature for the SOTA by identifying key terms matching that we, hereafter, call source words. A case study in the food and beverage industry is provided to demonstrate the algorithm’s application. In the study, five relevant knowledge areas were defined to guide literature selection. The database from scientific repositories was categorized using six classification rules based on impact factor (IF), Open Access (OA) status, and JCR journal ranking. This classification revealed the knowledge area with the highest presence and highlighted the effectiveness of the selection rules in identifying articles for the SOTA. The approach included a panel of experts who confirmed the algorithm’s effectiveness in identifying source words in high-quality articles. The algorithm’s performance was evaluated using the $F_1$ Score, which reached 0.83 after filtering out non-relevant articles. This result validates the algorithm’s ability to extract significant source words and demonstrates its usefulness in building the SOTA by focusing on the most scientifically impactful articles. Full article

The expansion of operation technology (OT) use and its tight integration with classical information and communication technologies have led not only to additional and improved possibilities in monitoring physical/manufacturing processes and the emergency of Industry 4.0 but also to a number of new threats, both related to the security of processed data and the safety of people, affected by physical processes and controlled by OT. Understanding potential threats has caused an increased demand for scientific research in the field, which is still relatively new and lacks established terminology. In this review paper, we aim to identify emerging trends and technologies in OT incident response, attack detection, applications of machine and deep learning for attack recognition, and security of OT protocols. An examination of research patterns from the Web of Science repository is performed to comprehend the panorama of publications and the present state of research in the area of OT security. The analysis shows a notable rise in publications concerning OT security, reflecting an increasing research interest. Proceeding articles and research articles were the predominant types of publications that were analyzed. The analysis further emphasizes the collaborative connections between researchers, academic institutions, and nations. Additionally, co-occurrence and citation analyses are carried out to offer an understanding of the associations between various keywords and/or research subjects. The study is finalized by suggesting future research directions on OT security. The uniqueness of this review lies in its focus on OT rather than the more commonly explored SCADA/ICS topics, attempting to cover a wider range of research topics instead of concentrating on a narrow area/method. Full article

(1) Background: Since the 1990s, theses and dissertations—a key part of scientific communication—have evolved significantly with advances in information and communication technologies. (2) Methods: This study reviews 99 publications examining these changes, drawing insights from international conferences and empirical studies in the field. (3) Results: Historically, a major challenge in managing PhD theses has been the shift to electronic formats, resulting in the creation of electronic theses and dissertations (ETDs). This shift involves four main tasks: adopting new digital formats, updating institutional workflows between departments, graduate schools, and academic libraries, implementing updated bibliographic standards (such as metadata and identifiers), and utilizing new tools and channels for distribution. With open science becoming a widespread research policy across many countries and institutions, ensuring open access for ETDs is an added challenge—though a substantial portion of ETD content remains restricted to institutional or library networks. Today, ETD management is on the brink of a new era, with advancements in data-driven science and artificial intelligence. (4) Conclusions: The development of ETDs varies significantly across different countries, regions, and institutions due to technological, organizational, and legal differences. It is essential for academic libraries and other stakeholders to address the challenges identified while considering these variations. Full article

The scope of the research work described in this article involved identifying the effects of the COVID-19 pandemic on the urban public transport system in a medium-sized city and its adjacent metropolitan area, using as reference information the number of tickets effectively sold in order to determine the fluctuation in the volume of passengers on the different bus lines before, during and after the pandemic. At the methodological level, a combined approach was employed, involving, on the one hand, the collection of open access public data from institutional repositories and information provided by the government and, on the other hand, network analysis and graphical mapping using GIS tools. The results obtained at the micro level (individualised study of each urban bus line) reveal a significant decrease in the number of passengers during the pandemic, showing the effect of mobility restrictions and the fear of contagion. However, a gradual recovery in post-pandemic demand has been observed, highlighting a large variability in recovery patterns between different bus lines. Such a situation could be attributable to several factors, such as the socio-demographic characteristics of the areas served, the frequency of the service, connectivity with other modes of transport and users’ perception of the quality of the service. At the macro level (comparison between urban and interurban transport), lines with higher demand prior to the pandemic have shown greater resilience and faster recovery. However, urban transport has experienced a more uniform and accelerated recuperation than interurban transport, with significant percentage differences in the years analysed. This disparity could be explained by the greater dependence of inhabitants on urban transport for their daily trips, due to its greater frequency and geographical coverage. Interurban transport, on the other hand, shows a more fluctuating demand and a lower dependence of users. Finally, the lack of previous research focused on the impact of the pandemic in sparsely populated rural areas restricts the ability to establish a solid frame of reference and generalise the results of this study. The authors consider that more detailed future research, including a comparative analysis of different alternative transport modes in inter-urban settings and considering a broader set of socio-demographic variables of passengers, is needed to better understand mobility dynamics in these areas and their evolution in the context of the pandemic. Full article

Introduction: Public health disinformation is a significant problem as demonstrated by the recent scientific literature on the COVID-19 pandemic. However, further studies that analyse the presence of the disinformation mitigation strategies in public health initiatives within specific contexts and which contains a multidimensional approach (gender, social and environmental) are required. Evidence shows that disinformation, information overload, misinformation or fake news on health issues are also influenced by these issues. Objective: The inclusion of the health disinformation dimension within national public implemented by the governments of Argentina and Spain before, during and after the COVID-19 pandemic. Additionally, this paper incorporated a gender-based approach and social and environmental determinants in order to identify the limitations of these initiatives and offer certain recommendations. We conducted a descriptive, qualitative and quantitative study, as well as content analysis. We focused on documents from the websites of the national health ministries of Argentina and Spain, and digital repositories of regulations at the national level. Various strategies for systematic searches on government websites were designed and implemented. This included manual searches on Google. The first step involved a general analysis of all documents found by the searches, followed by a qualitative analysis of the documents that were related to health issues. Based on this work, a comprehensive and flexible framework of (pre-established and emerging) dimensions and categories of health disinformation and infodemics was generated. Results. The work was based on a total of 202 documents (both downloadable information and information included in websites); 117 for Argentina and 85 for Spain. Of the total, 60.9% were published during the COVID-19 pandemic. In the second stage of the analysis, 55 texts were selected for Argentina and 47 for Spain. In both countries, the central communications approach used was disinformation and/or infodemics (although definitions such as fake news were also used). They were mainly linked to the COVID-19 pandemic, but other emerging health problems were also detected to a lesser degree. However, disinformation (or a related concept) was prominently present in only 17 documents in Argentina and 3 documents in Spain. In terms of document type, working materials were foremost in Argentina (44.4%) and Spain (37.6%), with little presence of policy, regulatory and evaluation documents (only 5). Gender binary language was predominantly used in these texts. Vulnerable groups and social determinants were poorly included. Environmental determinants were mentioned in conjunction with health disinformation in only one paper on the use of plastics and its impact on human health in Argentina, and in another paper from the Global Summit on Climate and Health in Spain. Conclusions: Based on the document analysis, the inclusion of health disinformation within public actions in both countries before, during and after the COVID-19 pandemic, was detected. However, different limitations were observed: it was clear that the problem was strongly linked to the health emergency and did not extend much beyond that. Health disinformation was secondary and did not play a key role in public policy nor did it have greater institutional importance. Limitations were also detected in terms of gender perspectives, vulnerable groups and social and environmental determinants linked to health disinformation, displaying a reductionist approach. Based on these results, this paper makes certain policy recommendations. Full article

Background: To implement recovery-oriented practice, it is important to have instruments capable of evaluating such practice. A number of different questionnaires have been developed in recent years which measure recovery orientation in mental health services. Objective: To identify and analyze patient-reported experience measures (PREMs) reported in the literature that are related to recovery-oriented practice in mental health services. Methodology: This study followed the Joanna Briggs Institute methodology for scoping reviews. Searches were carried out in the Web of Science, CINAHL, Medline (via Pubmed), and SCOPUS databases and in grey literature repositories (Google Scholar, Opengrey, Dart-Europe, Teseo). Papers on recovery services for adults suffering from mental disorders (MDs) were included. Those focusing on addiction and intellectual disability care services were excluded. Results: Sixteen papers met the inclusion criteria. The selected PREMs mainly identified recovery-oriented systems, treatment, community integration and support as the dimensions addressed most frequently in questionnaires. The average number of items included in the questionnaires was found to be 54. With regard to psychometric properties, 62% of the papers evaluated reliability (internal consistency) and 56% provided some kind of evidence of validity. Conclusions: This review aims to give an overview of the existing instruments in the literature and to highlight the characteristics of each one of them. Several different PREMs exist which evaluate recovery-oriented practice. No instrument currently exists which could be described as a benchmark tool, but there are quite a few with good psychometric properties capable of producing data that are useful when evaluating clinical services. Full article

In the Netherlands, the Open Government Act (Wet openbare overheid or Woo/Wob in Dutch) is in effect, with the primary objective of ensuring a more transparent government. In line with the legislation, a search engine named Woogle has been designed and developed to centralize documents published under the Open Government Act. The Estonian Public Information Act serves a similar purpose and requires all public institutions to publish information generated during official duties, fostering transparency and public oversight. Currently, Estonia’s document repositories are decentralized, and content search is not supported, which hinders people’s ability to efficiently locate information. This study aims to assess public information accessibility in Estonia and to apply Woogle’s design and techniques to Estonia’s document repositories, thereby evaluating its potential for broader European implementation. The methodology involved web scraping data and documents from 57 Estonian public institutions’ document repositories. The results indicate that Woogle’s design and techniques can be implemented in Estonia. From a technical perspective, the alignment of the fields was successful, while it was found that content-wise, the Estonian data present challenges due to inconsistencies and lack of comprehensive categorization. The findings suggest potential scalability across European countries, pointing to a broader applicability of the Woogle model for creating a corpus of Freedom of Information Act documents in Europe. The collected data are available as a dataset. Full article

Network management and troubleshooting require not only a grasp of advanced concepts but also the development of analytical and problem-solving skills. To bridge this gap, this paper introduces a novel network administration system, DRACSC (Spanish acronym for device for automatic recovery and configuration of communication systems), designed for the automatic configuration and disaster recovery of communication equipment. This system transcends the limitations of current hardware and software solutions by combining their advantages, boasting portability, automated functions, and a cloud-based repository as its main features. The DRACSC system, undergoing a comprehensive large-scale evaluation involving diverse user groups across multiple institutions, was tested with 89 users, including students and teachers at educational centers and ICT (Information and Communication Technology) professionals. The benefits of the system were evaluated through a training program based on simulated real-world ICT environments, focusing on both quantitative results on the reduction in time to complete user tasks, as well as qualitative results on the interface and usability of the system. Statistical analysis, including Welch’s t-test on opinion surveys, indicated a significant increase in knowledge and understanding, demonstrating the system’s potential to enhance education and practice. Moreover, the evaluation shed light on the user experience, with positive impacts observed for learning and teaching implications. As a result, the study has verified that the system has the potential to significantly influence network management practices, enhancing both learning and professional application through improved efficiency and usability. Full article

Background: Patient safety is an important component of healthcare service quality, and there are numerous instruments in the literature that measure patient safety. This scoping reviewaims to map the instruments/scales for assessing patient safety in healthcare services. Method: This scoping review follows the JBI methodology. The protocol was registered on the Open Science Framework. Eligibility criteria were defined based on studies that include instruments or scales for assessing patient safety in healthcare services, in any language, and without temporal restrictions. It adhered to all scoping review checklist items [PRISMA-ScR], with searches in the Embase, Lilacs, MedLine, and Scopus databases, as well as the repository of the Brazilian Digital Library of Theses and Dissertations. Two independent reviewers performed selection and data extraction in July 2023. Results: Of the 4019 potential titles, 63 studies reported on a total of 47 instruments/scales and 71 dimensions for patient safety assessment. The most-described dimensions were teamwork, professional satisfaction, safety climate, communication, and working conditions. Conclusion: The diversity of instruments and dimensions for patient safety assessment characterizes the multidimensionality and scope of patient safety. However, it hinders benchmarking between institutions and healthcare units. Full article

Background/Objectives: High-grade gliomas are the most common primary malignant brain tumors in adults. These neoplasms remain predominantly incurable due to the genetic diversity within each tumor, leading to varied responses to specific drug therapies. With the advent of new targeted and immune therapies, which have demonstrated promising outcomes in clinical trials, there is a growing need for image-based techniques to enable early prediction of treatment response. This study aimed to evaluate the potential of radiomics and artificial intelligence implementation in predicting progression-free survival (PFS) in patients with highest-grade glioma (CNS WHO 4) undergoing a standard treatment plan. Methods: In this retrospective study, prediction models were developed in a cohort of 51 patients with pathologically confirmed highest-grade glioma (CNS WHO 4) from the authors’ institution and the repository of the Cancer Imaging Archive (TCIA). Only patients with confirmed recurrence after complete tumor resection with adjuvant radiotherapy and chemotherapy with temozolomide were included. For each patient, 109 radiomic features of the tumor were obtained from a preoperative magnetic resonance imaging (MRI) examination. Four clinical features were added manually—sex, weight, age at the time of diagnosis, and the lobe of the brain where the tumor was located. The data label was the time to recurrence, which was determined based on follow-up MRI scans. Artificial intelligence algorithms were built to predict PFS in the training set (n = 75%) and then validate it in the test set (n = 25%). The performance of each model in both the training and test datasets was assessed using mean absolute percentage error (MAPE). Results: In the test set, the random forest model showed the highest predictive performance with 1-MAPE = 92.27% and a C-index of 0.9544. The decision tree, gradient booster, and artificial neural network models showed slightly lower effectiveness with 1-MAPE of 88.31%, 80.21%, and 91.29%, respectively. Conclusions: Four of the six models built gave satisfactory results. These results show that artificial intelligence models combined with radiomic features could be useful for predicting the progression-free survival of high-grade glioma patients. This could be beneficial for risk stratification of patients, enhancing the potential for personalized treatment plans and improving overall survival. Further investigation is necessary with an expanded sample size and external multicenter validation. Full article

Urban historical heritage areas serve as vital repositories of urban culture and history, playing a crucial role in cultural inheritance and the promotion of urban development. The protection and development of these heritage areas are essential for preserving the cultural characteristics and architectural styles of cities. Despite the growing body of research, a comprehensive review of the dynamic evolution, research frontiers, and future trajectories in this field remains absent. To bridge this gap, this study draws on the Web of Science Core Collection database, selecting 828 papers published between 2000 and 2024 that focus on urban historical heritage conservation and development. By employing Python programming and network analysis tools, this study conducted a systematic analysis of research structures and trends over the past 25 years. The results indicate that countries such as China and Italy, along with their respective research institutions, are at the forefront of global research in this area. Furthermore, this study identified research hotspots, including historic districts, sustainable urban development, urban regeneration, risk assessment, 3D modeling, digital documentation, and cultural tourism. This research not only discusses the challenges faced in the field but also explores future development trends, providing new theoretical perspectives and practical guidance for subsequent studies. Full article