Search Results (212)

By analyzing new findings from the literature on immunometabolism during the transition period, as well as classical concepts, we aim to propose a new approach to the inflammation paradigm in cows transitioning from gestation to lactation. The purpose of this review, based on data from scientific articles and reviews, is to characterize the immunometabolism of the transition period, highlighting the main characteristics of the inflammatory response in dairy cows and listing the mechanisms that govern inflammatory tone and coordinate the resolution of inflammation, with a view of new paradigms and analysis of non-classical pathways. We also seek to analyze inflammation and the role of mitochondria and the endoplasmic reticulum in the genesis of diseases, proposing approaches for modulating inflammatory tone. This review analyzes the classical theoretical approach using mechanistic views anchored in knowledge produced in other species and based on new evidence from the bovine field, determining new paradigms. This study highlights the constant inflammatory condition during the transition period and its effect on metabolism and demonstrates the role of dysregulation of inflammation resolution as a central factor in the genesis of diseases. Purinergic and cholinergic anti-inflammatory pathways have been little explored in cattle, but it is believed that the role of these pathways in maintaining homeostasis represents a great opportunity for understanding and modulating the phenomenon of inflammation in dairy cows. Dysregulation of the stress axis shows elucidative potential regarding the dysregulation of inflammatory resolution, with mitochondrial health and endoplasmic reticulum stress being dividing factors between homeorhetic and pathological states. Modulating inflammation and establishing inflammatory resolution presents challenges with classic anti-inflammatory drugs due to the paradoxical role of prostaglandin E2 in inflammation and resolution. Phytoactives offer new possibilities for modulating inflammation without disrupting inflammatory resolution and ensuring antioxidant effects, associated with strategies for formulating less inflammatory diets. Full article

The advancement of floating offshore wind energy demands innovative and robust mooring and shared infrastructure solutions to enable scalable, cost-effective deployment of future wind farms. This review provides a comprehensive overview of shared mooring systems for floating offshore wind applications, with a focus on system configurations, environmental load considerations, modelling methods and mooring cost estimations. Existing concepts of shared mooring and shared anchoring are summarized and discussed. Drawing on insights from numerical studies, industrial practices, and academic research, the paper identifies key technical challenges and gaps in current design methodologies, validation requirements, and regulatory frameworks. Recommendations are proposed to guide future research aimed at improving system reliability, optimizing mooring layouts, and lowering the levelized cost of energy for large-scale floating wind projects. Full article

The way in which Aquaporin-4 (AQP4) is localized on the astrocytes’ surface—i.e., with AQP4 channels predominantly located on the endfeet of astrocytes near the blood vessels—represents an important structural element for maintaining brain fluid homeostasis. In addition to this structural function, AQP4 polarity also facilitates glymphatic transport, the maintenance of the blood–brain barrier (BBB) functions, ion buffering, and neurotransmitter removal, and helps regulate neurovascular communications. The growing body of literature suggests that the loss of AQP4 polarity—a loss in the organization of AQP4 channels to the perivascular membrane—is associated with increased vascular, inflammatory, and metabolic disturbances in the context of many neurological diseases. As a result, this review attempts to synthesize both experimental and clinical studies to highlight that AQP4 depolarization often occurs in conjunction with early signs of neurodegeneration and neuroinflammation; however, we are aware that the loss of AQP4 polarity is only one factor in a complex pathophysiological environment. This review examines the molecular structure responsible for maintaining the polarity of AQP4—such as dystrophin–syntrophin complexes, orthogonal particle arrays, lipid microdomains, trafficking pathways, and transcriptional regulators—and describes how the vulnerability of these systems to various types of vascular stress, inflammatory signals, energy deficits, and mechanical injury can lead to a loss of AQP4 polarity. Furthermore, we will explore how a loss of AQP4 polarity can lead to the disruption of perivascular fluid movement, changes in blood–brain barrier morphology, enhanced neuroimmune activity, changes in ionic and metabolic balance, and disruptions in the global neural network synchronization. Importantly, we recognize that each of these disruptions will likely occur in concert with other disease-specific mechanisms. Alterations in AQP4 polarity have been observed in a variety of neurological disorders including Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, traumatic brain injury, and glioma; however, we also observe that the same alterations in fluid regulation occur across all of these different diseases, but that no single upstream event accounts for the alteration in polarity. Ultimately, we will outline emerging therapeutic avenues to restore perivascular fluid transport, and will include molecular-based therapeutic agents designed to modify the anchoring of AQP4, methods designed to modulate the state of astrocytes, biomaterials-based drug delivery systems, and therapeutic methods that leverage dynamic modulation of the neurovascular interface. Future advances in multi-omic profiling, spatial proteomics, glymphatic imaging, and artificial intelligence will allow for earlier identification of AQP4 polarity disturbances and potentially allow for the development of more personalized treatment plans. Ultimately, by linking these concepts together, this review aims to frame AQP4 polarity as a modifiable aspect of the “fluidic connectome”, and highlight its importance in maintaining overall brain health across disease states. Full article

The proliferation of the Social Internet of Things (SIoT) necessitates robust and scalable trust management systems to ensure secure and reliable interactions among heterogeneous devices. However, existing trust management models often lack scalability for large SIoT environments. To address this, a lightweight trust evaluation model for SIoT, referred to as Micro-Moment (MMTE), is presented here. MMTE evaluates trust based on concise, context specific, repetitive, and high-frequency interactions, termed micro-moments among SIoT devices. The MMTE model is evaluated using the Lysis dataset, which is extracted from a real SIoT environment, and demonstrates superior resource efficiency compared to existing SIoT trust models with significantly lower CPU time, memory, and disk usage. MMTE’s linear complexity and simple design make it more resource efficient and scalable than other lightweight trust models, especially when processing large-scale data in heterogeneous SIoT networks. Moreover, MMTE accurately distinguishes 99.35% of malicious nodes in a simulated smart home environment. Furthermore, a numerical comparison clearly demonstrates that MMTE outperforms existing and recently published trust models in terms of classifying malicious and benign nodes. To enhance scalability, the concept of trust spheres is introduced, and devices with similar trust scores are grouped to streamline processing and storage demands. Sphere Anchors manage the trust spheres and efficiently distribute computational tasks and optimize storage through an adaptive storage strategy. The trust spheres also efficiently manage increasing network sizes, maintaining linear processing times as the traffic load increases, and also outperform existing models in terms of average propagation times. MMTE and trust spheres together provide a robust, scalable, and lightweight solution for trust management in SIoT networks. Full article

This paper presents a concept for a Learning Factory (LF) designed for interdisciplinary engineering education. Learning factories are experiential learning environments that bridge the gap between theory and practice while supporting the demands of digital transformation. The proposed LF concept was developed using an integrated approach that assessed stakeholder needs and reviewed institutional infrastructure and capacity. These inputs were triangulated into a concept consisting of five core thematic components: Lean processes as an educational anchor, Enterprise Resource Planning (ERP) systems, Internet of Things (IoT)-based integration, simulation, and physical prototyping. Validation workshops with Small- and Medium-sized Enterprise (SME) managers, academic experts, and students confirmed the perceived relevance of this structure and its potential. The resulting concept focuses on practice-orientated, team-based learning methods that are in line with the principles of Education 4.0. The design sets goals in four key dimensions: educational integration, technological readiness, industrial relevance with SME orientation and flexibility and scalability. These design principles and practical insights can be utilized for future academic implementations of learning factories. Full article

The performance of extractive summarization models is often limited by their dependence on human references that may contain inaccuracies or subjective biases. Existing methods typically rely solely on sentence-level supervision, which lacks explicit grounding in the actual semantic content of the source document, thus limiting their robustness. We propose SSF-KW, a novel multi-task learning framework that enhances robustness by jointly optimizing keyword extraction and sentence selection. Our approach is designed to explicitly anchor salience decisions in the document’s intrinsic semantic structure, reducing reliance on potentially noisy labels. To this end, the model employs a shared BERT encoder to represent sentences, and identifies keywords through part-of-speech tagging, semantic similarity analysis, and fine-grained keyword signals with sentence-level representations via a transformer-based fusion module. The entire framework is optimized with a combined loss function that balances both tasks. Comprehensive evaluations on CNN/DailyMail, XSum, and WikiHow demonstrate that SSF-KW consistently outperforms baselines ROUGE-1 scores of 43.27, 25.43, and 30.03, respectively. Ablation studies confirm the contribution of each component, with the word-level module proving especially critical for capturing key concepts in procedural texts like WikiHow. Full article

The recent synergistic explosion of artificial intelligence and the world of machines, in a bid to make them smarter entities as a result of the fourth industrial revolution, has resulted in the concept of chatbots, which have evolved over the years and gained heightened attention for the sustainability of most human corporations. Organisations are increasingly utilising chatbots to enhance customer engagement through the process of agent-based autonomous sensing, interaction, and enhanced service delivery. The current state of the art in chatbot technology is such that the system lacks the ability to conduct text-sensing in a bid to acquire new information or learn from the external world autonomously. This has limited the current chatbot systems to being system-controlled interactive agents, hence, strongly limiting their functionalities and posing a question on the purported intelligence. In this research, an integrated framework that combines the functionalities and capabilities of a chatbot and machine learning was developed. The integrated system was designed to accept new text queries from the external world and import them into the knowledge base using the SQL (Structured Query Language) syntax and MySQL workbench (version 8.0.44). The search engine and decision-making cluster was built in the Python (version 3.12.7) coding environment with the learning process, solution adaptation, and inference, anchored using a reinforcement machine learning approach. This mode of chatbot operation, with an interactive capacity, is known as the mixed controlled system mode, with a viable human–machine system interaction. The smart chatbot was assessed for efficacy using performance metrics (response time, accuracy) and user experience (usability, satisfaction). The analysis further revealed that several self-governed chatbots deployed in most corporate organisations are system-controlled and significantly constrained, hence lacking the ability to adapt or filter queries beyond their predefined databases when users employ diverse phrasing or alternative terms in their interactions. Full article

To address the challenge of simulating shear failure in anchor bolts within FLAC3D, a shear failure criterion, F_s(i) ≥ F_smax(i), is proposed based on the PILE structural element. Through secondary development using the FISH programming language, a modified mechanical model of the PILE element is established and integrated into the FLAC3D-FISH framework. Comparative analyses are conducted on shear tests of bolt shafts and on anchor bolt support performance under coal–rock interface slip conditions, using both the original PILE model and the modified mechanical model. The results demonstrate that the shear load–displacement curve of the modified PILE model clearly reflects shear failure characteristics, satisfying a quantitative shear failure criterion. Upon failure, both the shear force and axial force of the structural element at the failure point drop abruptly to zero, enabling effective simulation of shear failure in anchor bolts within the FLAC3D environment. Using the modified model, the distribution of principal stress differences in the surrounding rock after roadway excavation is analyzed. Based on this, the concept of a stress-bearing ring in the surrounding rock is introduced. The reinforcing effects of bolt length, spacing, and ultimate load capacity on the stress-bearing ring in weak and fractured surrounding rock are investigated. The findings reveal that: (1) shear failure initiates in bolt shafts near the coal–rock interfaces, occurring earlier near the coal–floor interface than near the coal–roof interface; (2) the stress-bearing ring in weak and fractured surrounding rock shows a discontinuous and uneven distribution. However, with support improvements—such as increasing bolt length, reducing spacing, and enhancing failure load—the surrounding rock gradually forms a continuous stress-bearing ring with more uniform thickness and stress distribution, migrating inward toward the roadway surface. Full article

This study primarily investigates the mechanical performance of prestressed anchor foundations. Based on the assumptions of continuity, homogeneity, and isotropy of the anchor foundation and anchoring materials, a simplified elastic analysis model was developed. Using the superposition principle, the working stresses under vertical loads and bending moments were calculated, allowing for the determination of the maximum working stresses within the anchors and the foundation. Additionally, the distribution of bond strength of the prestressed tendons was analyzed, and the concept of effective anchorage length was introduced. The reliability of the model was validated through prototype testing, with the measured free segment strain values showing a high degree of consistency with theoretical calculations, with errors within 6.5%. Empirical data on ultimate bearing capacity and bond characteristics were also obtained. By integrating numerical calculations with experimental results, the performance of the anchoring system under extreme and specialized loading conditions was analyzed. The experimental results indicated that the failure modes of all anchor foundations were characterized by bond failure at the interface between the anchor and the surrounding rock mass. Based on the experimental data, a reasonable anchorage length satisfying design strength requirements was proposed. The findings provide a theoretical foundation and practical guidance for the design and application of prestressed anchor foundations in structures such as wind turbine towers. Full article

With the development of drone technology in recent years, many studies have discussed how to leverage drones equipped with sensors and cameras to conduct inspections under bridges. To address positioning challenges caused by the lack of GPS signals under the bridges, triangulation methods with on-site pre-installed Ultra-Wideband (UWB) sensors were used extensively to determine drone locations. However, the practical hurdles of deploying anchors under bridges are often overlooked, including variable terrain and potential electromagnetic interference from deploying a large number of UWB sensors. This study introduces a handover mechanism to address long-distance positioning challenges and an enhanced two-stage algorithm to enhance its suitability for bridge terrain with higher stability. By integrating these concepts, a practical bridge inspection system was devised, and realistic under-bridge experiments were conducted to validate the method’s efficacy in real-world settings. Full article

With the increase in contamination by microbial agents (bacteria, viruses, etc.) in the fields of agri-food, healthcare, and environment, it is necessary to detect and quantify these biological elements present in complex fluids in a short time with high selectivity, high sensitivity, and, if possible, moderate cost. Acoustic wave biosensors, based on immuno-detection, appear to meet a certain number of these criteria. In this context, we are developing a generic antibody-based biointerface that can detect a wide range of pathogenic bacterial agents using a specific bioreceptor. Based on the silane–oxide chemistry, the process is transferable to any kind of surface that can be either oxidized in surface or activated with O₂-plasma, for instance. For this proof of concept, we have chosen to develop our biointerface on titanium and lithium niobate surfaces. The development of the biointerface consists of grafting antibodies via a self-assembled monolayer (SAM) composed of an aminopropyltriethoxysilane (APTES) and a linker (phenylene diisothiocyanate, PDITC). Two functionalization routes were tested for grafting APTES: in anhydrous toluene followed by a heating step at 110 °C or in chloroform at room temperature. The results obtained on titanium show comparable grafting efficiency between these two routes, allowing us to consider the transposition of the route at room temperature on lithium niobate. The latest route was chosen for fragile materials that do not require the heating steps necessary when using toluene for grafting aminopropyltriethoxysilane. Different surface characterization techniques were used, such as IR spectroscopy (FTIR-ATR), X-ray photoelectron spectroscopy (XPS), and contact angle (WCA), to verify the successful grafting of each layer. Biodetection experiments in static conditions were also carried out to demonstrate the specificity of pathogenic detection, testing an ideal medium with solely bacteria, with no other food sampling nutrients. This paper demonstrates the successful elaboration of a biointerface using APTES as the first anchoring layer, with chloroform as a mild solvent. The process is easily transferable to any kind of fragile surface. Moreover, following anti-L. monocytogenes antibodies, our biointerface shows a specificity of capture in static mode (at a concentration of 10⁷ CFU/mL for an incubation time of 4 h at 37 °C) of up to 98% compared to a species negative control (E. coli) and up to 85% in terms of strain specificity (L. innocua). Full article

Background: Urban loneliness is rising worldwide and is a recognised public-health threat. Nature-Based Social Prescriptions (NBSPs), guided group activities in natural settings, are being piloted in six cities through the EU project RECETAS. However, in new contexts such as Marseille, its implementation is constrained by professionals’ limited knowledge of the concept. Objectives: (i) Exploring how professionals in Marseille (France) conceptualise NBSPs; (ii) Identifying perceived facilitators and barriers to implementing NBSPs among residents facing social isolation and loneliness. Methods: Twelve semi-structured interviews were conducted with health, social-care, and urban–environment professionals selected via network mapping and snowball sampling. Verbatim transcripts underwent inductive thematic analysis informed by Social Representation Theory, with double coding to enhance reliability. Results: Five analytic themes emerged: (1) a holistic health paradigm linking nature, community, and well-being; (2) stark ecological inequities with limited green-space access in deprived districts; (3) work challenges due to the urgent needs of individuals facing significant socio-economic challenges in demanding contexts; (4) a key tension between a perceived top-down process and a preference for participatory approaches; (5) drivers and obstacles: strong professional endorsement of NBSPs meets significant systemic and institutional constraints. Conclusions: Professionals endorse NBSPs as a promising approach against loneliness, provided programmes tackle structural inequities and adopt participatory governance. Results inform the Marseille RECETAS pilot and contribute to global discussions on environmentally anchored health promotion. Full article

Background: The fibromyalgia syndrome (FMS) is classified as a functional somatic syndrome and is characterized primarily by chronic pain in multiple body regions and physical and/or mental fatigue. The German S3-guideline recommends a multimodal therapy for severe forms. Since research on non-pharmacologic complementary, naturopathic, and integrative therapy approaches shows positive and promising effects, integrative methods are firmly anchored in the S3 guideline. Objective/Methods: Aim of the present study was to investigate whether a multimodal integrative treatment program can be effective in reducing the primary symptoms of FMS (pain and fatigue) and improving psychological aspects such as quality of life (QoL), anxiety, depression, and perceived stress. Another aim of the study is to explore whether potential effects appear only in the short term (immediately after discharge) or persist long term (six months after discharge). The treatment concept is based on mind–body medicine and elements of classical European naturopathy (including fasting interventions) and focusses on stress reduction and lifestyle modification. Results: Of N = 134 originally included longstanding fibromyalgia patients (mean time since diagnosis 9.2 ± 8.5 years), 101 data sets could be analyzed. Results show a significant improvement in both short-term and long-term pain and fatigue intensity (about 12% improvement). Long-term reductions in pain intensity appear to be supported by medical fasting interventions. Regarding psychological aspects and quality of life, there are long-lasting reductions regarding anxiety, depression, perceived stress, and helplessness and a long-lasting increase in self-efficacy, quality of life and current working ability. Conclusions: The two-weeks inpatient stay therefore leads to significant improvements in all mentioned aspects. Therefore, the concept may be a promising component for integration into medical guidelines and thus in the care of FMS patients. Future research including randomized controlled trials is necessary to further evaluate the program. Full article

Burial location and concepts of belonging are deeply interconnected. This article explores the biblical narrative of Jacob’s death and burial in the final chapters of the book of Genesis, with a focus on this relationship. The analysis engages in dialogue with Osman Balkan’s recent research on Turkish Muslims in Europe, examining factors influencing burial decisions, including the choice between repatriation to countries of origin and local burial. Key themes relevant to the biblical narrative include tensions with the host society, its authorities, and customs, the complex interplay of factors in end-of-life decisions, and the role of burial location as a means of anchoring future generations. In particular, the concept of the dead as an ‘anchor’ provides a useful framework for understanding the contrasting burial wishes of Jacob and his son Joseph. Additionally, considering Joseph as an undertaker adds nuance to his struggle to balance loyalty to local Egyptian customs with his father’s request to be buried among his ancestors in Canaan. Full article

As the global digital transformation of agriculture accelerates, the widespread deployment of farming equipment has triggered an exponential surge in agricultural production data. Consequently, traditional cloud computing frameworks face critical challenges: communication latency in the field, the demand for low-power devices, and stringent real-time decision constraints. These bottlenecks collectively exacerbate bandwidth constraints, diminish response efficiency, and introduce data security vulnerabilities. In this context, edge computing offers a promising solution for smart agriculture. By provisioning computing resources to the network periphery and enabling localized processing at data sources adjacent to agricultural machinery, sensors, and crops, edge computing leverages low-latency responses, bandwidth optimization, and distributed computation capabilities. This paper provides a comprehensive survey of the research landscape in agricultural edge computing. We begin by defining its core concepts and highlighting its advantages over cloud computing. Subsequently, anchored in the “terminal sensing-edge intelligence-cloud coordination” architecture, we analyze technological evolution in edge sensing devices, lightweight intelligent algorithms, and cooperative communication mechanisms. Additionally, through precision farming, intelligent agricultural machinery control, and full-chain crop traceability, we demonstrate its efficacy in enhancing real-time agricultural decision-making. Finally, we identify adaptation challenges in complex environments and outline future directions for research and development in this field. Full article