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Search Results (828)

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Keywords = flexible collaboration

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22 pages, 2666 KiB  
Article
Comparative Proteomic Analysis of Flammulina filiformis Reveals Substrate-Specific Enzymatic Strategies for Lignocellulose Degradation
by Weihang Li, Jiandong Han, Hongyan Xie, Yi Sun, Feng Li, Zhiyuan Gong and Yajie Zou
Horticulturae 2025, 11(8), 912; https://doi.org/10.3390/horticulturae11080912 (registering DOI) - 4 Aug 2025
Abstract
Flammulina filiformis, one of the most delicious and commercially important mushrooms, demonstrates remarkable adaptability to diverse agricultural wastes. However, it is unclear how different substrates affect the degradation of lignocellulosic biomass and the production of lignocellulolytic enzymes in F. filiformis. In [...] Read more.
Flammulina filiformis, one of the most delicious and commercially important mushrooms, demonstrates remarkable adaptability to diverse agricultural wastes. However, it is unclear how different substrates affect the degradation of lignocellulosic biomass and the production of lignocellulolytic enzymes in F. filiformis. In this study, label-free comparative proteomic analysis of F. filiformis cultivated on sugarcane bagasse, cotton seed shells, corn cobs, and glucose substrates was conducted to identify degradation mechanism across various substrates. Label-free quantitative proteomics identified 1104 proteins. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis of protein expression differences were predominantly enriched in energy metabolism and carbohydrate metabolic pathways. Detailed characterization of carbohydrate-active enzymes among the identified proteins revealed glucanase (GH7, A0A067NSK0) as the key enzyme. F. filiformis secreted higher levels of cellulases and hemicellulases on sugarcane bagasse substrate. In the cotton seed shells substrate, multiple cellulases functioned collaboratively, while in the corn cobs substrate, glucanase predominated among the cellulases. These findings reveal the enzymatic strategies and metabolic flexibility of F. filiformis in lignocellulose utilization, providing novel insights for metabolic engineering applications in biotechnology. The study establishes a theoretical foundation for optimizing biomass conversion and developing innovative substrates using targeted enzyme systems. Full article
(This article belongs to the Special Issue Advances in Propagation and Cultivation of Mushroom)
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19 pages, 2280 KiB  
Article
A Swap-Integrated Procurement Model for Supply Chains: Coordinating with Long-Term Wholesale Contracts
by Min-Yeong Ryu and Pyung-Hoi Koo
Mathematics 2025, 13(15), 2495; https://doi.org/10.3390/math13152495 - 3 Aug 2025
Viewed by 109
Abstract
In today’s volatile supply chain environment, organizations require flexible and collaborative procurement strategies. Swap contracts, originally developed as financial instruments, have recently been adopted to address inventory imbalances—such as the 2021 COVID-19 vaccine swap between South Korea and Israel. Despite its increasing adoption [...] Read more.
In today’s volatile supply chain environment, organizations require flexible and collaborative procurement strategies. Swap contracts, originally developed as financial instruments, have recently been adopted to address inventory imbalances—such as the 2021 COVID-19 vaccine swap between South Korea and Israel. Despite its increasing adoption in the real world, theoretical studies on swap-based procurement remain limited. This study proposes an integrated model that combines buyer-to-buyer swap agreements with long-term wholesale contracts under demand uncertainty. The model quantifies the expected swap quantity between parties and embeds it into the profit function to derive optimal order quantities. Numerical experiments are conducted to compare the performance of the proposed strategy with that of a baseline wholesale contract. Sensitivity analyses are performed on key parameters, including demand asymmetry and swap prices. The numerical analysis indicates that the swap-integrated procurement strategy consistently outperforms procurement based on long-term wholesale contracts. Moreover, the results reveal that under the swap-integrated strategy, the optimal order quantity must be adjusted—either increased or decreased—depending on the demand scale of the counterpart and the specified swap price, deviating from the optimal quantity under traditional long-term contracts. These findings highlight the potential of swap-integrated procurement strategies as practical coordination mechanisms across both private and public sectors, offering strategic value in contexts such as vaccine distribution, fresh produce, and other critical products. Full article
(This article belongs to the Special Issue Theoretical and Applied Mathematics in Supply Chain Management)
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21 pages, 672 KiB  
Systematic Review
Assessing and Understanding Educators’ Experiences of Synchronous Hybrid Learning in Universities: A Systematic Review
by Hannah Clare Wood, Michael Detyna and Eleanor Jane Dommett
Educ. Sci. 2025, 15(8), 987; https://doi.org/10.3390/educsci15080987 (registering DOI) - 2 Aug 2025
Viewed by 254
Abstract
The rise in online learning, accelerated by the COVID-19 pandemic, has led to greater use of synchronous hybrid learning (SHL) in higher education. SHL allows simultaneous teaching of in-person and online learners through videoconferencing tools. Previous studies have identified various benefits (e.g., flexibility) [...] Read more.
The rise in online learning, accelerated by the COVID-19 pandemic, has led to greater use of synchronous hybrid learning (SHL) in higher education. SHL allows simultaneous teaching of in-person and online learners through videoconferencing tools. Previous studies have identified various benefits (e.g., flexibility) and challenges (e.g., student engagement) to SHL. Whilst systematic reviews have emerged on this topic, few studies have considered the experiences of staff. The aim of this review was threefold: (i) to better understand how staff experiences and perceptions are assessed, (ii) to understand staff experiences in terms of the benefits and challenges of SHL and (iii) to identify recommendations for effective teaching and learning using SHL. In line with the PRISMA guidance, we conducted a systematic review across four databases, identifying 14 studies for inclusion. Studies were conducted in nine different countries and covered a range of academic disciplines. Most studies adopted qualitative methods, with small sample sizes. Measures used were typically novel and unvalidated. Four themes were identified relating to (i) technology, (ii) redesigning teaching and learning, (iii) student engagement and (iv) staff workload. In terms of recommendations, ensuring adequate staff training and ongoing classroom support were considered essential. Additionally, active and collaborative learning were considered important to address issues with interactivity. Whilst these findings largely aligned with previous work, this review also identified limited reporting in research in this area, and future studies are needed to address this. Full article
(This article belongs to the Section Higher Education)
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17 pages, 524 KiB  
Article
Collaborative Practices in Mental Health Care: A Concept Analysis
by Eslia Pinheiro, Carlos Laranjeira, Camila Harmuch, José Mateus Bezerra Graça, Amira Mohammed Ali, Feten Fekih-Romdhane, Murat Yıldırım, Ana Kalliny Severo and Elisângela Franco
Healthcare 2025, 13(15), 1891; https://doi.org/10.3390/healthcare13151891 - 2 Aug 2025
Viewed by 96
Abstract
Background/Objectives: Collaboration in mental health care is essential for implementing a model oriented towards the psychosocial rehabilitation of people based on multifaceted interventions involving different actors and sectors of society to respond to demands. Despite the benefits presented by the scientific evidence, there [...] Read more.
Background/Objectives: Collaboration in mental health care is essential for implementing a model oriented towards the psychosocial rehabilitation of people based on multifaceted interventions involving different actors and sectors of society to respond to demands. Despite the benefits presented by the scientific evidence, there are still many barriers to collaborative care, and professionals continue to struggle in reorienting their conduct. The current situation demands organization and the framing of well-founded action plans to overcome challenges, which in turn requires a detailed understanding of collaborative practices in mental health care and their conceptual boundaries. A concept analysis was undertaken to propose a working definition of collaborative practices in mental health care (CPMHC). Methods: This paper used the Walker and Avant concept analysis method. This includes identifying the defining concept attributes, antecedents, consequences, and empirical referents. A literature search was carried out from November 2024 to February 2025 in three databases (Medline, CINAHL, and LILACS), considering studies published between 2010 and 2024. Results: The final sample of literature investigated consisted of 30 studies. The key attributes were effective communication, building bonds, co-responsibility for care, hierarchical flexibility, articulation between services, providers and community, monitoring and evaluating of care processes, and attention to the plurality of sociocultural contexts. Conclusions: This comprehensive analysis contributes to guiding future research and policy development of collaborative practices in mental health, considering the individual, relational, institutional, and social levels. Further research is possible to deepen the understanding of the production of collaborative practices in mental health in the face of the complexity of social relations and structural inequities. Full article
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25 pages, 953 KiB  
Article
Command Redefined: Neural-Adaptive Leadership in the Age of Autonomous Intelligence
by Raul Ionuț Riti, Claudiu Ioan Abrudan, Laura Bacali and Nicolae Bâlc
AI 2025, 6(8), 176; https://doi.org/10.3390/ai6080176 - 1 Aug 2025
Viewed by 154
Abstract
Artificial intelligence has taken a seat at the executive table and is threatening the fact that human beings are the only ones who should be in a position of power. This article gives conjectures on the future of leadership in which managers will [...] Read more.
Artificial intelligence has taken a seat at the executive table and is threatening the fact that human beings are the only ones who should be in a position of power. This article gives conjectures on the future of leadership in which managers will collaborate with learning algorithms in the Neural Adaptive Artificial Intelligence Leadership Model, which is informed by the transformational literature on leadership and socio-technical systems, as well as the literature on algorithmic governance. We assessed the model with thirty in-depth interviews, system-level traces of behavior, and a verified survey, and we explored six hypotheses that relate to algorithmic delegation and ethical oversight, as well as human judgment versus machine insight in terms of agility and performance. We discovered that decisions are made quicker, change is more effective, and interaction is more vivid where agile practices and good digital understanding exist, and statistical tests propose that human flexibility and definite governance augment those benefits as well. It is single-industry research that contains self-reported measures, which causes research to be limited to other industries that contain more objective measures. Practitioners are provided with a practical playbook on how to make algorithmic jobs meaningful, introduce moral fail-safes, and build learning feedback to ensure people and machines are kept in line. Socially, the practice is capable of minimizing bias and establishing inclusion by visualizing accountability in the code and practice. Filling the gap between the theory of leadership and the reality of algorithms, the study provides a model of intelligent systems leading in organizations that can be reproduced. Full article
(This article belongs to the Section AI Systems: Theory and Applications)
18 pages, 6642 KiB  
Article
Flood Impact and Evacuation Behavior in Toyohashi City, Japan: A Case Study of the 2 June 2023 Heavy Rain Event
by Masaya Toyoda, Reo Minami, Ryoto Asakura and Shigeru Kato
Sustainability 2025, 17(15), 6999; https://doi.org/10.3390/su17156999 - 1 Aug 2025
Viewed by 156
Abstract
Recent years have seen frequent heavy rainfall events in Japan, often linked to Baiu fronts and typhoons. These events are exacerbated by global warming, leading to an increased frequency and intensity. As floods represent a serious threat to sustainable urban development and community [...] Read more.
Recent years have seen frequent heavy rainfall events in Japan, often linked to Baiu fronts and typhoons. These events are exacerbated by global warming, leading to an increased frequency and intensity. As floods represent a serious threat to sustainable urban development and community resilience, this study contributes to sustainability-focused risk reduction through integrated analysis. This study focuses on the 2 June 2023 heavy rain disaster in Toyohashi City, Japan, which caused extensive damage due to flooding from the Yagyu and Umeda Rivers. Using numerical models, this study accurately reproduces flooding patterns, revealing that high tides amplified the inundation area by 1.5 times at the Yagyu River. A resident questionnaire conducted in collaboration with Toyohashi City identifies key trends in evacuation behavior and disaster information usage. Traditional media such as TV remain dominant, but younger generations leverage electronic devices for disaster updates. These insights emphasize the need for targeted information dissemination and enhanced disaster preparedness strategies, including online materials and flexible training programs. The methods and findings presented in this study can inform local and regional governments in building adaptive disaster management policies, which contribute to a more sustainable society. Full article
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38 pages, 1465 KiB  
Article
Industry 4.0 and Collaborative Networks: A Goals- and Rules-Oriented Approach Using the 4EM Method
by Thales Botelho de Sousa, Fábio Müller Guerrini, Meire Ramalho de Oliveira and José Roberto Herrera Cantorani
Platforms 2025, 3(3), 14; https://doi.org/10.3390/platforms3030014 - 1 Aug 2025
Viewed by 223
Abstract
The rapid evolution of Industry 4.0 technologies has resulted in a scenario in which collaborative networks are essential to overcome the challenges related to their implementation. However, the frameworks to guide such collaborations remain underexplored. This study addresses this gap by proposing Business [...] Read more.
The rapid evolution of Industry 4.0 technologies has resulted in a scenario in which collaborative networks are essential to overcome the challenges related to their implementation. However, the frameworks to guide such collaborations remain underexplored. This study addresses this gap by proposing Business Rules and Goals Models to operationalize Industry 4.0 solutions through enterprise collaboration. Using the For Enterprise Modeling (4EM) method, the research integrates qualitative insights from expert opinions, including interviews with 12 professionals (academics, industry professionals, and consultants) from Brazilian manufacturing sectors. The Goals Model identifies five main objectives—competitiveness, efficiency, flexibility, interoperability, and real-time collaboration—while the Business Rules Model outlines 18 actionable recommendations, such as investing in digital infrastructure, upskilling employees, and standardizing information technology systems. The results reveal that cultural resistance, limited resources, and knowledge gaps are critical barriers, while interoperability and stakeholder integration emerge as enablers of digital transformation. The study concludes that successfully adopting Industry 4.0 requires technological investments, organizational alignment, structured governance, and collaborative ecosystems. These models provide a practical roadmap for companies navigating the complexities of Industry 4.0, emphasizing adaptability and cross-functional synergy. The research contributes to the literature on collaborative networks by connecting theoretical frameworks with actionable enterprise-level strategies. Full article
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28 pages, 7946 KiB  
Article
Service Composition Optimization Method for Sewing Machine Cases Based on an Improved Multi-Objective Artificial Hummingbird Algorithm
by Gan Shi, Shanhui Liu, Keqiang Shi, Langze Zhu, Zhenjie Gao and Jiayue Zhang
Processes 2025, 13(8), 2433; https://doi.org/10.3390/pr13082433 - 31 Jul 2025
Viewed by 135
Abstract
In response to the low efficiency of collaborative processing of sewing machine cases at the part level in network collaborative manufacturing, this paper proposes a sewing machine cases manufacturing service composition optimization method based on an improved multi-objective artificial hummingbird algorithm. The structure [...] Read more.
In response to the low efficiency of collaborative processing of sewing machine cases at the part level in network collaborative manufacturing, this paper proposes a sewing machine cases manufacturing service composition optimization method based on an improved multi-objective artificial hummingbird algorithm. The structure and production process of sewing machine cases are analyzed; a framework for service composition optimization in the sewing machine cases manufacturing service platform is established; the required manufacturing resource service composition is determined; and a dual-objective service composition optimization mathematical model that considers Quality of Service (QoS) indicators and flexibility indicators is constructed. Opposition-based learning strategies, roulette wheel selection strategies, and improved differential evolution strategies are embedded in the multi-objective artificial hummingbird algorithm, and the improved artificial hummingbird algorithm (ORAHA_DE) is used to solve the sewing machine cases manufacturing service composition optimization model. The experimental results show the effectiveness and superiority of this composition optimization method in solving the sewing machine cases manufacturing composition optimization problem while avoiding entrapment in a local optimum during the solution process, thereby achieving the composition optimization of sewing machine cases collaborative manufacturing services. Full article
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18 pages, 2894 KiB  
Article
Technology Roadmap Methodology and Tool Upgrades to Support Strategic Decision in Space Exploration
by Giuseppe Narducci, Roberta Fusaro and Nicole Viola
Aerospace 2025, 12(8), 682; https://doi.org/10.3390/aerospace12080682 - 30 Jul 2025
Viewed by 99
Abstract
Technological roadmaps are essential tools for managing and planning complex projects, especially in the rapidly evolving field of space exploration. Defined as dynamic schedules, they support strategic and long-term planning while coordinating current and future objectives with particular technology solutions. Currently, the available [...] Read more.
Technological roadmaps are essential tools for managing and planning complex projects, especially in the rapidly evolving field of space exploration. Defined as dynamic schedules, they support strategic and long-term planning while coordinating current and future objectives with particular technology solutions. Currently, the available methodologies are mostly built on experts’ opinions and in just few cases, methodologies and tools have been developed to support the decision makers with a rational approach. In any case, all the available approaches are meant to draw “ideal” maturation plans. Therefore, it is deemed essential to develop an integrate new algorithms able to decision guidelines on “non-nominal” scenarios. In this context, Politecnico di Torino, in collaboration with the European Space Agency (ESA) and Thales Alenia Space–Italia, developed the Technology Roadmapping Strategy (TRIS), a multi-step process designed to create robust and data-driven roadmaps. However, one of the main concerns with its initial implementation was that TRIS did not account for time and budget estimates specific to the space exploration environment, nor was it capable of generating alternative development paths under constrained conditions. This paper discloses two main significant updates to TRIS methodology: (1) improved time and budget estimation to better reflect the specific challenges of space exploration scenarios and (2) the capability of generating alternative roadmaps, i.e., alternative technological maturation paths in resource-constrained scenarios, balancing financial and temporal limitations. The application of the developed routines to available case studies confirms the tool’s ability to provide consistent planning outputs across multiple scenarios without exceeding 20% deviation from expert-based judgements available as reference. The results demonstrate the potential of the enhanced methodology in supporting strategic decision making in early-phase mission planning, ensuring adaptability to changing conditions, optimized use of time and financial resources, as well as guaranteeing an improved flexibility of the tool. By integrating data-driven prioritization, uncertainty modeling, and resource-constrained planning, TRIS equips mission planners with reliable tools to navigate the complexities of space exploration projects. This methodology ensures that roadmaps remain adaptable to changing conditions and optimized for real-world challenges, supporting the sustainable advancement of space exploration initiatives. Full article
(This article belongs to the Section Astronautics & Space Science)
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26 pages, 6831 KiB  
Article
Human–Robot Interaction and Tracking System Based on Mixed Reality Disassembly Tasks
by Raúl Calderón-Sesmero, Adrián Lozano-Hernández, Fernando Frontela-Encinas, Guillermo Cabezas-López and Mireya De-Diego-Moro
Robotics 2025, 14(8), 106; https://doi.org/10.3390/robotics14080106 - 30 Jul 2025
Viewed by 177
Abstract
Disassembly is a crucial process in industrial operations, especially in tasks requiring high precision and strict safety standards when handling components with collaborative robots. However, traditional methods often rely on rigid and sequential task planning, which makes it difficult to adapt to unforeseen [...] Read more.
Disassembly is a crucial process in industrial operations, especially in tasks requiring high precision and strict safety standards when handling components with collaborative robots. However, traditional methods often rely on rigid and sequential task planning, which makes it difficult to adapt to unforeseen changes or dynamic environments. This rigidity not only limits flexibility but also leads to prolonged execution times, as operators must follow predefined steps that do not allow for real-time adjustments. Although techniques like teleoperation have attempted to address these limitations, they often hinder direct human–robot collaboration within the same workspace, reducing effectiveness in dynamic environments. In response to these challenges, this research introduces an advanced human–robot interaction (HRI) system leveraging a mixed-reality (MR) interface embedded in a head-mounted device (HMD). The system enables operators to issue real-time control commands using multimodal inputs, including voice, gestures, and gaze tracking. These inputs are synchronized and processed via the Robot Operating System (ROS2), enabling dynamic and flexible task execution. Additionally, the integration of deep learning algorithms ensures precise detection and validation of disassembly components, enhancing accuracy. Experimental evaluations demonstrate significant improvements, including reduced task completion times, enhanced operator experience, and compliance with strict adherence to safety standards. This scalable solution offers broad applicability for general-purpose disassembly tasks, making it well-suited for complex industrial scenarios. Full article
(This article belongs to the Special Issue Robot Teleoperation Integrating with Augmented Reality)
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20 pages, 1421 KiB  
Article
A Learning Design Framework for International Blended and Virtual Activities in Higher Education
by Ania Maria Hildebrandt, Alice Barana, Vasiliki Eirini Chatzea, Kelly Henao, Marina Marchisio Conte, Daniel Samoilovich, Nikolas Vidakis and Georgios Triantafyllidis
Trends High. Educ. 2025, 4(3), 40; https://doi.org/10.3390/higheredu4030040 - 29 Jul 2025
Viewed by 273
Abstract
Blended and virtual learning have become an integral part in international higher education, especially in the wake of the COVID-19 pandemic and the European Union’s Digital Education Action Plan. These modalities have enabled more inclusive, flexible, and sustainable forms of international collaboration, such [...] Read more.
Blended and virtual learning have become an integral part in international higher education, especially in the wake of the COVID-19 pandemic and the European Union’s Digital Education Action Plan. These modalities have enabled more inclusive, flexible, and sustainable forms of international collaboration, such as Collaborative Online International Learning (COIL) and Blended Intensive Programs (BIPs), reshaping the landscape of global academic mobility. This paper introduces the INVITE Learning Design Framework (LDF), developed to support higher education instructors in designing high-quality, internationalized blended and virtual learning experiences. The framework addresses the growing need for structured, theory-informed approaches to course design that foster student engagement, intercultural competence, and motivation in non-face-to-face settings. The INVITE LDF was developed through a rigorous scoping review of existing models and frameworks, complemented by needs-identification analysis and desk research. It integrates Self-Determination Theory, Active Learning principles, and the ADDIE instructional design model to provide a comprehensive, adaptable structure for course development. The framework was successfully implemented in a large-scale online training module for over 1000 educators across Europe. Results indicate that the INVITE LDF enhances educators’ ability to create engaging, inclusive, and pedagogically sound international learning environments. Its application supports institutional goals of internationalization by making global learning experiences more accessible and scalable. The findings suggest that the INVITE LDF can serve as a valuable tool for higher education institutions worldwide, offering a replicable model for fostering intercultural collaboration and innovation in digital education. This contributes to the broader transformation of international higher education, promoting equity, sustainability, and global citizenship through digital pedagogies. Full article
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16 pages, 274 KiB  
Article
Exploring an Intervention to Enhance Positive Mental Health in People with First-Episode Psychosis: A Qualitative Study from the Perspective of Mental Health Professionals
by Júlia Rolduà-Ros, Antonio Rafael Moreno-Poyato, Joana Catarina Ferreira Coelho, Catarina Nogueira, Carlos Alberto Cruz Sequeira, Sónia Teixeira, Judith Usall and Maria Teresa Lluch-Canut
Healthcare 2025, 13(15), 1834; https://doi.org/10.3390/healthcare13151834 - 28 Jul 2025
Viewed by 244
Abstract
Background/Objectives: This study explores the perspectives of mental health professionals on tailoring the Mentis Plus intervention to enhance positive mental health (PMH) in individuals experiencing First-Episode Psychosis (FEP). Although the Mentis Plus Program has been previously implemented in other contexts, it has not [...] Read more.
Background/Objectives: This study explores the perspectives of mental health professionals on tailoring the Mentis Plus intervention to enhance positive mental health (PMH) in individuals experiencing First-Episode Psychosis (FEP). Although the Mentis Plus Program has been previously implemented in other contexts, it has not yet been applied to FEP care. Therefore, this study aimed to adapt the intervention for future implementation through expert consultation. Methods: A qualitative exploratory-descriptive design was employed. Data were collected via three focus groups comprising multidisciplinary professionals experienced in FEP care. Qualitative content analysis was used to examine the data. Results: Participants viewed the tailored Mentis Plus intervention as a valuable, recovery-oriented tool. Key recommendations included a flexible, group-based format with eight weekly sessions. Suggested intervention components encompassed gratitude journaling, emotional regulation techniques, and collaborative problem-solving exercises. Group delivery was highlighted as essential for mitigating isolation and promoting peer support. Practical implementation strategies included phased session structures and routine emotional check-ins. Identified barriers to implementation included the need for specialized training, limited therapeutic spaces, and the heterogeneity of participant needs. Facilitators included a person-centered approach, institutional backing, and sufficient resources. Conclusions: The findings support the feasibility and clinical relevance of a tailored Mentis Plus FEP Program—Brief Version. Expert-informed insights provide a foundation for adapting mental health interventions to early-psychosis care and inform future research and implementation strategies. Full article
24 pages, 1530 KiB  
Article
A Lightweight Robust Training Method for Defending Model Poisoning Attacks in Federated Learning Assisted UAV Networks
by Lucheng Chen, Weiwei Zhai, Xiangfeng Bu, Ming Sun and Chenglin Zhu
Drones 2025, 9(8), 528; https://doi.org/10.3390/drones9080528 - 28 Jul 2025
Viewed by 386
Abstract
The integration of unmanned aerial vehicles (UAVs) into next-generation wireless networks greatly enhances the flexibility and efficiency of communication and distributed computation for ground mobile devices. Federated learning (FL) provides a privacy-preserving paradigm for device collaboration but remains highly vulnerable to poisoning attacks [...] Read more.
The integration of unmanned aerial vehicles (UAVs) into next-generation wireless networks greatly enhances the flexibility and efficiency of communication and distributed computation for ground mobile devices. Federated learning (FL) provides a privacy-preserving paradigm for device collaboration but remains highly vulnerable to poisoning attacks and is further challenged by the resource constraints and heterogeneous data common to UAV-assisted systems. Existing robust aggregation and anomaly detection methods often degrade in efficiency and reliability under these realistic adversarial and non-IID settings. To bridge these gaps, we propose FedULite, a lightweight and robust federated learning framework specifically designed for UAV-assisted environments. FedULite features unsupervised local representation learning optimized for unlabeled, non-IID data. Moreover, FedULite leverages a robust, adaptive server-side aggregation strategy that uses cosine similarity-based update filtering and dimension-wise adaptive learning rates to neutralize sophisticated data and model poisoning attacks. Extensive experiments across diverse datasets and adversarial scenarios demonstrate that FedULite reduces the attack success rate (ASR) from over 90% in undefended scenarios to below 5%, while maintaining the main task accuracy loss within 2%. Moreover, it introduces negligible computational overhead compared to standard FedAvg, with approximately 7% additional training time. Full article
(This article belongs to the Special Issue IoT-Enabled UAV Networks for Secure Communication)
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33 pages, 1238 KiB  
Article
Crisis Response Modes in Collaborative Business Ecosystems: A Mathematical Framework from Plasticity to Antifragility
by Javaneh Ramezani, Luis Gomes and Paula Graça
Mathematics 2025, 13(15), 2421; https://doi.org/10.3390/math13152421 - 27 Jul 2025
Viewed by 387
Abstract
Collaborative business ecosystems (CBEs) are increasingly exposed to disruptive events (e.g., pandemics, supply chain breakdowns, cyberattacks) that challenge organizational adaptability and value creation. Traditional approaches to resilience and robustness often fail to capture the full range of systemic responses. This study introduces a [...] Read more.
Collaborative business ecosystems (CBEs) are increasingly exposed to disruptive events (e.g., pandemics, supply chain breakdowns, cyberattacks) that challenge organizational adaptability and value creation. Traditional approaches to resilience and robustness often fail to capture the full range of systemic responses. This study introduces a unified mathematical framework to evaluate four crisis response modes—plasticity, resilience, transformative resilience, and antifragility—within complex adaptive networks. Grounded in complex systems and collaborative network theory, our model formalizes both internal organizational capabilities (e.g., adaptability, learning, innovation, structural flexibility) and strategic interventions (e.g., optionality, buffering, information sharing, fault-injection protocols), linking them to pre- and post-crisis performance via dynamic adjustment functions. A composite performance score is defined across four dimensions (Innovation, Contribution, Prestige, and Responsiveness to Business Opportunities), using capability–strategy interaction matrices, weighted performance change functions, and structural transformation modifiers. The sensitivity analysis and scenario simulations enable a comparative evaluation of organizational configurations, strategy impacts, and phase-transition thresholds under crisis. This indicator-based formulation provides a quantitative bridge between resilience theory and practice, facilitating evidence-based crisis management in networked business environments. Full article
(This article belongs to the Special Issue Optimization Models for Supply Chain, Planning and Scheduling)
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20 pages, 2352 KiB  
Article
Three-Dimensional Physics-Based Channel Modeling for Fluid Antenna System-Assisted Air–Ground Communications by Reconfigurable Intelligent Surfaces
by Yuran Jiang and Xiao Chen
Electronics 2025, 14(15), 2990; https://doi.org/10.3390/electronics14152990 - 27 Jul 2025
Viewed by 205
Abstract
Reconfigurable intelligent surfaces (RISs), recognized as one of the most promising key technologies for sixth-generation (6G) mobile communications, are characterized by their minimal energy expenditure, cost-effectiveness, and straightforward implementation. In this study, we develop a novel communication channel model that integrates RIS-enabled base [...] Read more.
Reconfigurable intelligent surfaces (RISs), recognized as one of the most promising key technologies for sixth-generation (6G) mobile communications, are characterized by their minimal energy expenditure, cost-effectiveness, and straightforward implementation. In this study, we develop a novel communication channel model that integrates RIS-enabled base stations with unmanned ground vehicles. To enhance the system’s adaptability, we implement a fluid antenna system (FAS) at the unmanned ground vehicle (UGV) terminal. This innovative model demonstrates exceptional versatility across various wireless communication scenarios through the strategic adjustment of active ports. The inherent dynamic reconfigurability of the FAS provides superior flexibility and adaptability in air-to-ground communication environments. In the paper, we derive and study key performance characteristics like the autocorrelation function (ACF), validating the model’s effectiveness. The results demonstrate that the RIS-FAS collaborative scheme significantly enhances channel reliability while effectively addressing critical challenges in 6G networks, including signal blockage and spatial constraints in mobile terminals. Full article
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