Search Results (328)

Manufacturing in modern industrial sectors involves the machining of components where the undeformed chip thickness inevitably decreases to values comparable to the tool edge radius. Under such conditions, the ploughing effect between the workpiece and the tool becomes dominant, followed by the noticeable formation of a stagnation zone. This paper presents research focused on the analysis of the cutting process for small cross-sections of the removed layers, based on cutting force components. This study investigated the machining of two titanium alloy grades—Ti Grade 5 (Ti-6Al-4V) and Ti Grade 2—with the main focus on process stability. A material separation model was analyzed to demonstrate the mechanism of material flow within the cross-section of the machined layer. It was found that the material has a limited ability to flow sideways at the boundary of the chip thickness, thus determining the probable size of the stagnation zone in front of the cutting edge. Orthogonal cutting experiments enabled the determination of the minimum chip thickness coefficient for constant temperature conditions, independent of the tool edge radius, as $h_{min0}=$0.313. In oblique cutting tests, the sensitivity of thin-layer machining was demonstrated for the determined values of minimum undeformed chip thickness. By applying the 0–1 test for chaos, the measurement time (parameter $T·dt$) was determined for both titanium alloys to determine the range of observable chaotic behavior. The analyses confirmed that Ti Grade 2 enters chaotic dynamics much more rapidly than Ti Grade 5 and displays local cutting instabilities independent of the uncut chip thickness. Full article

The growing popularity of Personal Light Electric Vehicles (PLEVs), such as e-scooters, has revolutionized urban mobility by offering compact, cost-effective, and environmentally friendly transportation solutions. However, safety concerns, including inadequate infrastructure, poor protective measures, and high accident rates, remain critical challenges. This paper presents the design and development of an innovative self-balancing microvehicle under the H2020 LEONARDO project, which aims to address these challenges through advanced engineering and user-centric design. The vehicle combines features of monowheels and e-scooters, integrating cutting-edge technologies to enhance safety, stability, and usability. The design adheres to European regulations, including Germany’s eKFV standards, and incorporates user preferences identified through representative online surveys of 1500 PLEV users. These preferences include improved handling on uneven surfaces, enhanced signaling capabilities, and reduced instability during maneuvers. The prototype features a lightweight composite structure reinforced with carbon fibers, a high-torque motorized front wheel, and multiple speed modes tailored to different conditions, such as travel in pedestrian areas, use by novice riders, and advanced users. Braking tests demonstrate deceleration values of up to 3.5 m/s², comparable to PLEV market standards and exceeding regulatory minimums, while smooth acceleration ramps ensure rider stability and safety. Additional features, such as identification plates and weight-dependent motor control, enhance compliance with local traffic rules and prevent misuse. The vehicle’s design also addresses common safety concerns, such as curb navigation and signaling, by incorporating large-diameter wheels, increased ground clearance, and electrically operated direction indicators. Future upgrades include the addition of a second rear wheel for enhanced stability, skateboard-like rear axle modifications for improved maneuverability, and hybrid supercapacitors to minimize fire risks and extend battery life. With its focus on safety, regulatory compliance, and rider-friendly innovations, this microvehicle represents a significant advancement in promoting safe and sustainable urban mobility. Full article

Background/Objectives: Metabolic dysfunction-associated steatotic liver disease (MASLD) represents a major global health challenge characterized by complex adipose–liver interactions mediated by adipokines and hepatokines. Despite rapid field evolution, a comprehensive understanding of research trends and translational advances remains fragmented. This study systematically maps the scientific landscape through bibliometric analysis, identifying emerging domains and future clinical translation directions. Methods: A comprehensive bibliometric analysis of 1002 publications from 2004 to 2025 was performed using thematic mapping, temporal trend evaluation, and network analysis. Analysis included geographical and institutional distributions, thematic cluster identification, and research paradigm evolution assessment, focusing specifically on adipokine–hepatokine signaling mechanisms and clinical implications. Results: The United States and China are at the forefront of research output, whereas European institutions significantly contribute to mechanistic discoveries. The thematic map analysis reveals the motor/basic themes residing at the heart of the field, such as insulin resistance, fatty liver, metabolic syndrome, steatosis, fetuin-A, and other related factors that drive innovation. Basic clusters include metabolic foundations (obesity, adipose tissue, FGF21) and adipokine-centered subjects (adiponectin, leptin, NASH). New themes focus on inflammation, oxidative stress, gut microbiota, lipid metabolism, and hepatic stellate cells. Niche areas show targeted fronts such as exercise therapies, pediatric/novel adipokines (chemerin, vaspin, omentin-1), and advanced molecular processes that focus on AMPK and endoplasmic-reticulum stress. Temporal analysis shows a shift from single liver studies to whole models that include the gut microbiota, mitochondrial dysfunction, and interactions between other metabolic systems. The network analysis identifies nine major clusters: cardiovascular–metabolic links, adipokine–inflammatory pathways, hepatokine control, and new therapeutic domains such as microbiome interventions and cellular stress responses. Conclusions: In summary, this study delineates current trends and emerging areas within the field and elucidates connections between mechanistic research and clinical translation to provide guidance for future research and development in this rapidly evolving area. Full article

This study presents AD-MRCNN, an advanced deep learning framework for automated atmospheric front detection that addresses two critical limitations in existing methods. First, current approaches directly input raw meteorological data without optimizing feature compatibility, potentially hindering model performance. Second, they typically only provide frontal category information without identifying individual frontal systems. Our solution integrates two key innovations: 1. An intelligent adapter module that performs adaptive feature fusion, automatically weighting and combining multi-source meteorological inputs (including temperature, wind fields, and humidity data) to maximize their synergistic effects while minimizing feature conflicts; the utilized network achieves an average improvement of over 4% across various metrics. 2. An enhanced instance segmentation network based on Mask R-CNN architecture that simultaneously achieves (1) precise frontal type classification (cold/warm/stationary/occluded), (2) accurate spatial localization, and (3) identification of distinct frontal systems. Comprehensive evaluation using ERA5 reanalysis data (2009–2018) demonstrates significant improvements, including an 85.1% F1-score, outperforming traditional methods (TFP: 63.1%) and deep learning approaches (Unet: 83.3%), and a 31% reduction in false alarms compared to semantic segmentation methods. The framework’s modular design allows for potential application to other meteorological feature detection tasks. Future work will focus on incorporating temporal dynamics for frontal evolution prediction. Full article

The focus of this paper is placed on Oscillating Water Column (OWC) systems. The primary aim is to analyze, through both mathematical modeling and numerical simulations, a single module (chamber) of an OWC plant which, in addition to energy production, offers the dual advantage of large-scale integration into port infrastructures or coastal defense structures such as breakwaters, etc. The core challenge lies in optimizing the geometry of the OWC chamber and its associated ducts. A trapezoidal cross-section is adopted, with various front wall inclinations ranging from $90°$ to $45°$. This geometric parameter significantly affects both the internal compression ratio and the hydrodynamic behavior of incoming and outgoing waves. Certain inclinations revealed increased turbulence and notable interference with waves reflected from the chamber bottom which determined an unexpected drop in efficiency. The optimal performance occurred at an inclination of approximately $55°$, yielding an efficiency of around 12.8%, because it represents the most advantageous and balanced compromise between counter-trend phenomena. A detailed analysis is carried out on several key parameters for the different configurations (e.g., internal and external wave elevations, crest phase shifts, pressures, hydraulic loads, efficiency, etc.) to reach the most in-depth analysis possible of the complex phenomena that come into play. Lastly, the study also discusses the additional structural and functional benefits of inclined walls over traditional parallelepiped-shaped chambers, both from a structural and construction point of view, and for the possible use for coastal defense. Full article

Multimodal multiobjective optimization problems, characterized by multiple solutions mapping to identical objective vectors, are ubiquitous in real-world applications. Despite their prevalence, most existing multimodal multiobjective evolutionary algorithms (MMOEAs) predominantly focus on identifying global Pareto sets, often overlooking the equally significant local Pareto sets. While some algorithms attempt to address local Pareto sets, their performance in the objective space remains suboptimal. The inherent challenge lies in the fact that a single strategy cannot effectively tackle problems with and without local Pareto fronts. This study proposes a novel approach that first detects the presence of local Pareto fronts using a neural network, thereby enabling adaptive adjustments to the algorithm’s selection strategy and search scope. Based on this detection mechanism, we design a microscale searching multimodal multiobjective evolutionary algorithm (MMOEA_MS). Through extensive experiments on twenty-two benchmark problems, MMOEA_MS demonstrates superior performance in identifying local Pareto fronts and outperforms existing algorithms in the objective space. This study highlights the effectiveness of MMOEA_MS in solving multimodal multiobjective optimization problems with diverse Pareto front characteristics, thereby addressing key limitations of current methodologies. Full article

The winch traction system for shipboard aircraft, when operating in a marine environment, is subjected to additional forces and moments due to the complex motion of the hull. These loads pose significant threats to the safety of the aircraft during the traction process. To address the safety issues under complex sea conditions, this paper adopts harmonic functions to describe the rolling, pitching, and heaving motions of the hull. A theoretical analytical model of the three-winch traction system, considering the intricate coupling motions of the ship, is established. Unlike previous studies that often simplify ship motion or focus on single-component modeling, this work develops a complete, whole-system dynamic model integrating the winch system, rope, aircraft structure, and ship interaction. The dynamic characteristics of the small-deck winch traction system are investigated, with particular focus on the influence of the rear winch position, driving trajectory, and ship motion on the system’s dynamics and safety. This research is innovative in systematically exploring the dynamic safety behavior of a three-winch traction system operating under small-deck conditions and complex sea states. The results show that as the distance between the two rear winches increases, the lateral force on the tire decreases. Additionally, as the aircraft’s turning angle increases, the front winch rope force also increases. Moreover, with higher sea condition levels and wind scales, the maximum lateral force on the tires increases, leading to a significant reduction in the stability and safety of the winch traction system. This is particularly critical when the sea condition level exceeds 3 and the wind scale exceeds 6, as it increases the risk of tire sideslip or off-ground events. This research has substantial value for enhancing the safety and stability of winch traction systems on small decks, and also provides a theoretical basis for traction path design, winch position optimization, and the extension of the service life of key system components, demonstrating strong engineering applicability. Full article

This paper investigates the acceptability of focused Objects with [+corrective, +exhaustive] features in Italian and French, considering the role of syntactic rigidity, Exhaustivity Markers (EMs), and argument structure. We conducted two parallel acceptability judgment experiments (one per language), testing focused Objects in three positions: (i) in situ, (ii) fronted (FF), and (iii) clefted (CC). Each sentence was also presented with and without an explicit EM, and the verb type was controlled across three categories: transitive, unergative, and unaccusative verbs. Results reveal key cross-linguistic differences: (i) FF is the least acceptable strategy in both languages, contradicting the assumption that Italian tolerates FF more than French; (ii) Italian speakers prefer in situ Focus with an explicit EM, whereas French speakers rate in situ and CC Focus equally acceptable, favoring implicit exhaustivity; (iii) verb type does not significantly impact Focus acceptability, except in French, where intervention effects may reduce FF acceptability in transitive/unergative contexts; (iv) CC remains a viable alternative to in situ Focus in French, possibly acting as a repair strategy. These findings suggest that, as far as [+corrective, +exhaustive] Focus is concerned, Italian does not appear to be less syntactically rigid than French. Full article

This research investigates the challenges and opportunities of flood-prone buyback land in the context of intensifying climate change and urban intensification, taking the suburbs of Brisbane City in Australia as a case study. While the floodable land buyback strategy has gained global interest, there has been limited focus on the future of this acquired land in cities. Approaching the design of flood-prone buyback land requires an understanding of the impacts and the specific manifestations of buyback land while embracing the increasing presence of water in these areas. Buyback land represents spaces to rethink the design of cities, going beyond flood resilience and addressing other climate change-related urban challenges. By combining adaptation and regenerative measures, design disciplines can contribute to generating site-specific buyback land strategies, establishing a stronger connection between these newly acquired lands, hydrological systems, urban intensification, and ecological balance to address the current and future needs of the city. The methodology involves a design-led investigation, combining analytical and speculative–exploratory methods, grounded on a site-specific approach, working at multidisciplinary and multi-scalar levels at city, suburb and site scale. This study identifies five typologies of buyback land: isolated, isolated clusters, block-clusters, park-fronted and water-fronted. Understanding these typologies should shape how we rethink buyback land in the context of climate change and urban intensification. When reconceptualized, the buyback land can redefine the flood-prone cities, by applying strategies that reimagine these areas through local climate adaptation, land repair, regeneration and resource recovery. Current and future buyback land offers opportunities for future design practices and policymakers to rethink the city’s long-term development in a changing climate. Full article

Obesity and its related comorbidities continue to be a primary public health concern, especially in the United States (US). Such comorbidities include the top two causes of death in the US: cardiovascular disease and cancer. Obesity is also associated with several other chronic conditions that affect millions of adults and children, including diabetes, kidney, and liver disease. Weight loss has long been considered the front-line treatment and prevention strategy for these conditions. Lifestyle approaches, including dietary modification and increasing physical activity, are typically recommended for individuals with obesity, although rates of achieving and maintaining clinically meaningful weight loss remain low. Understanding the root causes of minimal weight loss and weight regain has been a prime focus among many researchers over the past several decades. The present review addresses several advantages of prioritizing exercise as an obesity and chronic disease treatment. We discuss current challenges when exercise is the primary treatment strategy, including physiological parameters that may influence the efficacy of exercise in addition to behavioral and environmental factors that play a role in exercise adherence and adoption. We also explore strategies and principles that, although not commonly utilized in an obesity/chronic disease treatment setting, may be applied and adapted to fit this model. Full article

In Supervisory Control and Data Acquisition (SCADA) systems, central to industrial automation and control systems, the Front-end Processor (FEP) facilitates seamless communication between field control devices and central management systems. As the Industrial Internet of Things (IIoT) and Industry 4.0 centered on the smart factory paradigm gain traction, conventional FEPs are increasingly showing limitations in various aspects. To address these issues, Data Distribution Service, a real-time communication middleware, and Kubernetes, a container orchestration platform, have garnered attention. However, the effective integration of conventional SCADA protocols, such as DNP3.0, IEC 61850, and Modbus with DDS, remains a key challenge. Therefore, this article proposes a Kubernetes-based real-time FEP for the modernization of SCADA systems. The proposed FEP ensures interoperability through an efficient translation mechanism between traditional SCADA protocols—DNP3.0, IEC 61850, and Modbus—and the Data Distribution Service protocol. In addition, the performance evaluation shows that the FEP achieves high throughput and sub-millisecond latency, confirming its suitability for real-time industrial control applications. This approach overcomes the limitations of conventional FEPs and enables the realization of more flexible and scalable industrial control systems. However, further research is needed to validate the system under large-scale deployment scenarios and enhance security capabilities. Future work will focus on performance evaluation in realistic conditions and the integration of quantum-resistant security mechanisms to strengthen resilience in critical infrastructure environments. Full article

The Three-North Shelter Forest Program (TNSFP) is a large-scale ecological restoration project that has attracted worldwide attention. It covers 4.069 million km² across 13 provinces in northern China, including northwestern, north-central, and northeastern regions. Bibliometric analysis provides a structural overview of the research in this field and offers insights into key research fronts. We conducted a literature review of the Web of Science Core Collection (WoSCC) from 1990 to 2024 using HistCite for a comprehensive literature analysis and CiteSpace for visualizing research trends and co-citation networks. Based on the literature data from the WoSCC, we performed a bibliometric visualization review of the TNSFP. We observe a rising trend in research on the TNSFP, with the number of publications steadily increasing, especially after 2011. Remote Sensing emerged as the leading journal during the study period, accounting for 8.84% of the total publications. China is the leading contributor to research in this field, comprising 99.32% of the publications, with the Chinese Academy of Sciences (CAS) being the primary research institution, accounting for 36.05%. Research on the TNSFP is interdisciplinary, with Environmental Sciences serving as its primary focus. Ecological restoration and climate change are likely to be the main trends in future research. This study provides a comprehensive overview of the TNSFP’s research landscape, offering insights that can inform policy decisions, guide future research directions, and support on-the-ground conservation and afforestation strategies. Full article

This study presents a systematic bibliometric review of digital innovations in renewable energy-oriented power systems, with a focus on Blockchain, Artificial Intelligence (AI), the Internet of Things (IoT), and Data Analytics. The objective is to evaluate the research landscape, trends, and integration potential of these technologies within sustainable energy infrastructures. Peer-reviewed journal articles published between 2020 and 2025 were retrieved from Scopus using a structured search strategy. A total of 23,074 records were initially identified and filtered according to inclusion criteria based on relevance, peer-review status, and citation impact. No risk of bias assessment was applicable due to the nature of the study. The analysis employed bibliometric and keyword clustering techniques using VOSviewer and MATLAB to identify publication trends, citation patterns, and technology-specific application areas. AI emerged as the most studied domain, peaking with 1209 papers and 15,667 citations in 2024. IoT and Data Analytics followed in relevance, contributing to real-time system optimization and monitoring. Blockchain, while less frequent, is gaining traction in secure decentralized energy markets. Limitations include possible indexing delays affecting 2025 trends and the exclusion of gray literature. This study offers actionable insights for researchers and policymakers by identifying converging research fronts and recommending areas for regulatory, infrastructural, and collaborative focus. This review was not pre-registered. Funding was provided by the Universidad Politécnica Salesiana under project code 005-01-2025-02-07. Full article

The analysis of sand distribution in a marine–continental rift basin is of practical value for hydrocarbon prediction. The primary objective of this study is to investigate the correlation between Paleoproterozoic sand development and paleomorphology in the Nanpu sag, and to focus on identifying the key factors controlling sand deposition in the marine–continental rift basin. Correspondence between the development of the Paleoproterozoic sand in the Nanpu sag and the paleogeomorphology shows that the gully limited the deposition of the sand into the lake. The differentiation and aggregation of the sand in the lake basin were influenced by two kinds of slope break zones (the syn-sedimentary fracture tectonic slope break zone and the paleo-topographic flexural depositional slope break zone). Due to tectonic movements in the marine–continental rift basin, as well as provenance supply and weather during chasmic stages, the impact of valley and syndeposit slope break zone on sand development varies. In areas where allocation is better as valley–syndeposit slope break zone, basal slope and its vicinity usually are favorable for delta (braided channel) and fan delta sand development, which extend basinward through hydraulic transport. Meanwhile, under the influence of syntectonic and gravitational disequilibrium, gravity flow sand can be seen sporadically distributed in the deep end of fan fronts. This study is of great significance for oil and gas exploration in the Bohai Bay Basin region and contributes to a better understanding of depositional processes in similar marine–continental rift basins around the globe. Full article

The field of sustainable finance has grown rapidly in response to escalating climate and economic challenges, yet its intellectual landscape, especially the connectedness between green and traditional financial systems, remains underexplored. This paper aims to systematically map the evolution, thematic structure, and intellectual linkages of the sustainable finance literature with a specific focus on risk spillovers and connectedness across financial systems. This study employs a comprehensive bibliometric methodology to map 1261 Web of Science-indexed articles (1994–2024) on the connectedness of sustainable finance, using techniques such as citation analysis, bibliographic coupling, co-citation analysis, trend cartography, collaboration network, and keyword trend analysis. The study clarifies the field’s evolution and identifies its key themes, influential authors, institutions, and networks. The findings reveal an exponential surge in sustainable finance research after 2015, coinciding with policy milestones like the Paris Agreement and rising ESG investment interest. Notably, the review uncovers how research clusters have formed around topics such as green bond market spillovers, green technology innovation, and climate risk, highlighting both well-established areas and emerging fronts. The contribution lies in providing a roadmap for future research and policy: the study pinpoints knowledge gaps (e.g., systemic risk transmission between green and conventional assets) and suggests how policymakers and investors can leverage these insights to foster a resilient, sustainable financial system. Full article