Search Results (2,256)

A solar air heater (SAH) converts solar energy into heated air without causing environmental pollution. It features a low initial cost and easy maintenance due to its simple design. However, owing to air’s poor thermal conductivity, its thermal efficiency is relatively low compared to that of other solar systems. To improve its thermal performance, previous studies have aimed at either enlarging the heat transfer surface or increasing the convective heat transfer coefficient. In this study, a novel SAH with fins and sequentially placed obstacles on the fin surface—designed to achieve both surface extension through a finned channel and enhancement of the heat transfer coefficient via the obstacles—was investigated using computational fluid dynamics analysis. The results confirmed that the obstacles enhanced heat transfer performance by up to 2.602 times in the finned channel. However, the obstacles also caused a pressure loss. Therefore, the thermo-hydraulic performance was discussed, and it was concluded that the obstacles with a relative height of 0.12 and a relative pitch of 10 yielded the maximum THP values among the investigated conditions. Additionally, correlations for the Nusselt number and friction factor were derived and predicted the simulation values with good agreement. Full article

The promising development of hydrogen and fuel cell technologies has garnered increased attention in recent years, assuming a significant role in industrial applications and the decarbonisation of the shipping industry. Given that the shipping industry generates considerable greenhouse gas emissions, it is crucial and imperative to implement integrated solutions based on clean energy sources, thereby meeting the proposed climate objectives. This study presents the standard hydrogen production, storage, and transport methods and analysis technologies that use hydrogen fuel cells in marine and industrial applications. Technologies based on hydrogen fuel cells and hybrid systems will have an increased perspective of application in industry and maritime transport under the conditions of optimising technological models, developing the hydrogen industrial chain, and updating standards and regulations in the field. However, there are still many shortcomings. The paper’s main contribution is analysing the hydrogen industrial chain, presenting the progress and obstacles associated with the technologies used in industrial and marine applications based on hydrogen energy. Full article

Considering the complexity and variability inherent in maritime environments, path planning algorithms for navigation have consistently been a subject of intense research interest. Nonetheless, single-algorithm approaches often exhibit inherent limitations. Consequently, this study introduces a path planning algorithm for autonomous surface vessels (ASVs) that integrates an improved fast marching method (FMM) with the dynamic window approach (DWA) for underactuated ASVs. The enhanced FMM improves the overall optimality and safety of the determined path in comparison to the conventional approach. Concurrently, it effectively merges the local planning strengths of the DWA algorithm, addressing the safety re-planning needs of the global path when encountering dynamic obstacles, thus augmenting path tracking accuracy and navigational stability. The efficient hybrid algorithm yields notable improvements in the path planning success rate, obstacle avoidance efficacy, and path smoothness compared with the isolated employment of either FMM or DWA, demonstrating superiority and practical applicability in maritime scenarios. Through a comprehensive analysis of its control output, the proposed integrated algorithm accomplishes efficient obstacle avoidance via agile control of angular velocity while preserving navigational stability and achieves path optimization through consistent acceleration adjustments, thereby asserting its superiority and practical worth in challenging maritime environments. Full article

Background: Community-acquired pneumonia (CAP) is the leading cause of death in infants aged 1–59 months. Concurrent with this, there is a need to prescribe antibiotics wisely in Vietnam due to concerns with rising antimicrobial resistance (AMR). Consequently, an urgent need has arisen to treat patients according to agreed guidelines. The aim of this study was to investigate the current management of infants under five years old with CAP in Vietnam as well as identify possible obstacles to adhering to national guidelines. Methods: A mixed-method approach was used incorporating both quantitative and qualitative data analysis in a leading hospital in Vietnam, which influences others. Data from 108 pediatric patient records were collected and analyzed. Subsequently, in-depth interviews were conducted with pediatric doctors treating these patients to ascertain possible reasons for non-adherence to guidelines. Results: The mean age of children diagnosed with CAP was 27.94 ± 12.99 months, with 82.4% having non-severe CAP, and 41.7% of children had previously used antibiotics before hospitalization. The median length of hospital stay was 7 days. All children were prescribed antibiotics, 91.4% of children received these initially intravenously, with third-generation cephalosporins being the most (91.7%) commonly prescribed. Cefoperazone/sulbactam was the most frequently prescribed (48.2%) antibiotic. However, on 96.1% of occasions cefoperazone/sulbactam was given at higher doses than the label instructions. Overall, 73.3% of antibiotics prescribed were “Watch” antibiotics. In addition, the proportion of initial antibiotic regimens that were consistent with current national guidelines was only 4.63%. Conclusions: There were considerable concerns with low adherence rates to current guidelines alongside high rates of prescribing of injectable third-generation cephalosporins due to various internal and external barriers. Antimicrobial stewardship programs with updated national guidelines are urgently needed in Vietnamese hospitals to treat CAP in children as part of ongoing measures to reduce increasing AMR rates. Such activities should also help improve antibiotic use in the community following improved education of trainee ambulatory care physicians regarding appropriate management of children with CAP. Full article

In the digital economy, sustainable development is based on digital technologies. However, information security issues arising from its use pose significant challenges to sustainable development. Assessing information security risks in the digital economy is crucial for sustainable development. This paper constructs an information security risk assessment indicator system for the digital economy based on information ecology theory. Using game theory to combine CRITIC weights and entropy weights, the information security risk values for the digital economy in 29 provinces of China from 2019 to 2021 are calculated. Quantitative analysis is conducted using Ward’s method and the obstacle degree model. The combined weighting results indicate that the information security risks of the digital economy are mostly influenced by information infrastructure. Additionally, the spatio–temporal evolution pattern shows that the risk values of provinces vary to different degrees over time, with a distribution pattern of southern regions > northern regions > northwestern regions. Furthermore, the clustering results indicate that information technology is the primary cause of risk gaps. Finally, the obstacle degree model indicates that digital criminal behavior is the greatest obstacle to information security in the digital economy. The research findings hold significant implications for addressing information security challenges in the global digital economy’s sustainable development process, particularly in terms of the replicability of the research methodology and the valuable case study of China. Full article

Sustainable aviation fuels (SAFs) are currently considered a key element in the decarbonization of the aviation sector, offering a feasible solution to reduce life cycle greenhouse gas emissions without requiring fundamental changes in aircraft or infrastructure. This article provides a comprehensive overview of the current state of SAFs, including their classification, production technologies, economic aspects, and environmental performance. The analysis covers both currently certified SAF pathways, such as HEFA and FT-SPK, and emerging technologies like alcohol-to-jet and power-to-liquid, assessing their technological maturity, feedstock availability, and scalability. Economic challenges related to high production costs, investment risks, and policy dependencies are discussed, alongside potential mechanisms to support market deployment. Furthermore, the article reviews SAFs’ emission performance, including CO₂ and non-CO₂ effects, based on existing life cycle assessment (LCA) studies, with an emphasis on variability caused by feedstock type and production method. The findings highlight that, while SAFs can significantly reduce aviation-related emissions compared to fossil jet fuels, the magnitude of benefits depends strongly on supply chain design and sustainability criteria. There are various certified pathways for SAF production, as well as new technologies that can further contribute to the development of the industry. Properly selected biomass sources and production technologies can reduce greenhouse gas emissions by more than 70% compared to conventional fuels. The implementation of SAFs faces obstacles related to cost, infrastructure, and regulations, which hinder its widespread adoption. The study concludes that although SAFs represent a promising pathway for aviation climate mitigation, substantial scaling efforts, regulatory support, and continued technological innovation are essential to achieve their full potential. Full article

Our study explored the accuracy of Fitbit recorded step count during the use of an assistive device (two-wheeled walker and standard cane) at various body positions (wrists, hips, and ankles). Participants (n = 11) ambulated an obstacle course (50 m total, including turns and a step up/down) a total of three times (two-wheeled walker, standard cane, and a deviceless control trial). Fitbit generated step counts (at the wrists, hips, and ankles) were then compared to the individual’s “actual” step count captured through video analysis. During the cane trial and the deviceless trial, all positions were significantly correlated (r = 0.764 to 0.984; p < 0.006) with the actual step count. However, increased variability (demonstrated by increased limits of agreement) was observed when the Fitbit was worn on the wrist (compared to the hips or ankles). During the walker trial, the step count was significantly correlated to the actual step count at the ankle and hip positions (r = 0.669 to 0.888; p < 0.017) with an average error of 1.5%, while it was not statistically correlated at the wrist with a 31.2% average error. Our study suggests that Fitbits are a good predictor of actual step count, with the caveat that the location of the Fitbit should be considered if an assistive device (e.g., two-wheeled rolling walker and single-point cane) is being used. Full article

As communication technologies continue to evolve, Reconfigurable Intelligent Surfaces (RISs) have become a crucial and highly potential technology for sixth-generation (6G) mobile communication systems. Their key competitive advantages lie in their cost-effectiveness, minimal power consumption, and simple deployment. To address the limitations of current communication paradigms, this study innovatively integrates RIS technology into vehicle-to-vehicle (V2V) communication systems. Current methodologies fail to comprehensively elucidate the transmission principles underlying RIS-assisted V2V fluid antenna system (FAS) communications. The current channel characteristic analysis techniques and modeling theories struggle to achieve a balance between computational accuracy and computational complexity. To overcome these problems, this study systematically constructed a multipath sub-channel model in RIS-assisted V2V communication. Combining detailed simulation with theoretical analysis, a reliable parametric channel statistical model was established. This progress successfully overcame the main obstacle of the traditional RIS channel modeling method, which was unable to coordinate accuracy and efficiency. Full article

Atrial fibrillation (AF) is a common cardiac arrhythmia linked to an increased risk of stroke, heart failure, and mortality, yet its diagnosis remains challenging due to its intermittent and often asymptomatic nature. Traditional methods, such as standard electrocardiography (ECG) and prolonged cardiac monitoring, have limitations in terms of cost, accessibility, and diagnostic yield. Artificial intelligence (AI), particularly machine learning (ML) and deep learning, has emerged as a promising tool for AF detection and prediction by analyzing ECG data with high accuracy. AI models can identify subtle patterns in ECG signals that may indicate AF, even when the arrhythmia is not actively present, improving early diagnosis and risk stratification. Additionally, AI-powered ECG analysis has been integrated into wearable and mobile health devices, expanding screening capabilities beyond clinical settings. While studies have demonstrated AI’s effectiveness, challenges such as data bias, model reliability across diverse populations, and regulatory considerations must be addressed before widespread clinical adoption. If these obstacles are overcome, AI has the potential to revolutionize AF management by enabling earlier detection, reducing the need for resource-intensive monitoring, and improving patient outcomes. Full article

This paper proposes a method for solving mazes, with a special focus on navigation using image processing. The objective of this study is to demonstrate that a robot can successfully navigate a maze using only two-wheel encoders, enabled by appropriate control strategies. This method significantly simplifies the structure of mobile robots, which typically suffer from increased energy consumption due to the need to carry onboard sensors and power supplies. Through experimental analysis, it was observed that although the encoder-only solution requires more advanced control knowledge, it can be more efficient than the alternative approach that combines encoders with a gyroscope. In order to develop an efficient maze-solving system, control theory techniques were integrated with image processing and neural networks in order to analyze images in which various obstacles were transformed into maze walls. This approach led to the training of a neural network designed to detect key points within the maze. Full article

Urban–rural integration (URI) plays a crucial role in advancing rural revitalization and the modernization of agriculture. Nevertheless, numerous nations encounter persistent obstacles, including inefficient resource mobility across urban–rural divides and uneven industrial distribution, while striving to foster such integration. Agricultural new quality productive forces (ANPFs) offer an innovation-led production framework fueled by advances in agricultural technology, allowing urban–rural integration (URI) through improved resource mobility between cities and rural regions. Utilizing panel data from 30 Chinese provinces (2013–2022), this study employs a two-way fixed effects model, mediation analysis model, threshold regression model, and the spatial Durbin model to investigate the transmission mechanism and spatial spillover effect of agricultural new quality productive forces (ANPFs) on urban–rural integration (URI). The findings show the following: (1) Agricultural new quality productive forces (ANPFs) significantly influence urban–rural integration (URI). (2) The influence is significantly stronger in western China than in the eastern and central regions. (3) Industrial restructuring and upgrading (IND) function as a mediating influence in this connection. (4) The role of informatization (INF) has a dual-threshold effect. (5) Geographically, while these forces promote local integration, they may impede progress in nearby regions. This study provides new empirical insights into the factors that influence urban–rural integration (URI) and proposes policy solutions to promote sustainable regional development. Full article

The building sector holds a significant position in the global energy consumption share, and its environmental impact continues to intensify, making the construction industry a key player in sustainable development. The application of life cycle assessment on buildings (LCA-B) is widely employed to evaluate building energy and environment performance, and thus is of great significance for ensuring the sustainability of the project. This work aims to provide a systematic overview of LCA-B development based on reviewed literature. A three-stage mixed research method is adopted in this study: Firstly, an overall analysis framework is constructed, and 327 papers related to building life cycle assessment published between 2009 and 2025 are screened out by using the bibliometric method; Then, through scientometrics analysis, the journal regions, sources, scholars, and keyword evolution are revealed and analyzed using VOSviewer tool, and the hotspots in the field of LCA-B (e.g., integration of building information modeling (BIM) in LCA-B, multi-dimensional framework of environment–society–culture) are preliminarily explored based on the selected highly cited papers. The research finds that: (1) the performance of low energy buildings is better than that of net zero energy buildings from the perspective of LCA; (2) software compatibility and data exchange are the main obstacles in the integration of BIM-LCA; (3) a multi-dimensional LCA framework covering the social or cultural aspects is expected for a comprehensive assessment of building performance. This study provides a systematic analysis and elaboration of review articles related to LCA-B and thereby provides researchers with in-depth insight into this field. Full article

Pedestrian flow simulations play a pivotal role in urban planning, transportation engineering, and disaster response by enabling the detailed analysis of crowd dynamics and walking behavior. While physical models such as the Social Force model and Boids have been widely used, they often struggle to replicate complex inter-agent interactions. On the other hand, reinforcement learning (RL) methods, although adaptive, suffer from limited interpretability due to their opaque policy structures. To address these limitations, this study proposes a pedestrian simulation framework based on the Anticipatory Classifier System 2 (ACS2), a rule-based evolutionary learning model capable of extracting explicit behavior rules through trial-and-error learning. The proposed model captures the interactions between agents and environmental features while preserving the interpretability of the acquired strategies. Simulation experiments demonstrate that the ACS2-based agents reproduce realistic pedestrian dynamics and achieve comparable adaptability to conventional reinforcement learning approaches such as tabular Q-learning. Moreover, the extracted behavior rules enable systematic analysis of movement patterns, including the effects of obstacles and crowd composition on flow efficiency and group alignment. The results suggest that the ACS2 provides a promising approach to constructing interpretable multi-agent simulations for real-world pedestrian environments. Full article

This study analyses aspects related to the electromobility transition. Emerging technologies have enabled the production and commercialisation of electric vehicles to reduce polluting emissions. However, significant obstacles are present in this global transition. The analysis identifies that public policies play a crucial role in the development of electromobility, and emphasises how new business models in electromobility are emerging to satisfy changing customer demands. Concerns related to raw materials extraction, battery disposal, and vehicle-to-grid (V2G) integration are also important to consider. The relationship between technologically advanced countries and raw material-producing nations must balance socioeconomic, historical, labour, and ecological factors. In order to have a standard reference, this study considers for the analysis the political, economic, social, technological, environmental, and legal factors (PESTLE). An analysis of future scenarios considering pessimistic and optimistic trends revealed that, compared with the actual trends, important actions must be taken to develop electromobility not only from the technological aspect. These results provide a comprehensive analysis of electromobility sustainability and its importance for multidisciplinary stakeholders related to the actual challenges towards electromobility, the electric network capabilities, and the importance of creating new jobs and products based on a circular and sustainable economy. Full article

As global urbanization accelerates amidst compounding risks, comprehensive urban resilience assessment has emerged as a pivotal issue in optimizing risk governance pathways. Grounded in the Pressure–State–Response (PSR) theoretical framework, this study constructs a multidimensional evaluation system for comprehensive urban resilience. Through the integration of a combined weighting method and the TOPSIS model, we systematically measure resilience levels across 13 prefecture-level cities in Jiangsu Province, with the obstacle degree model employed to identify critical resilience constraints. The findings reveal significant spatial heterogeneity in regional resilience patterns. High-resilience cities establish positive feedback mechanisms through economic foundations, innovation-driven strategies, and institutional coordination. Conversely, low-resilience cities face multidimensional constraints, including industrial structure imbalance, inadequate social security systems, and infrastructure deficiencies. The resilience disparity stems from the coupling effects of systemic multidimensional elements, with three core obstacles identified: energy consumption and population pressure in the Pressure dimension, medical resource scarcity and innovation deficit in the State dimension, and fiscal expenditure inefficiency in the Response dimension. The study proposes strategic interventions, including fiscal structure optimization, cross-regional resource coordination enhancement, and innovation–translation mechanism improvement, to facilitate urban systems’ transformation from passive resistance to proactive adaptation. This research provides novel perspectives for analyzing complex system resilience evolution and offers scientific grounds for urban agglomeration risk prevention and sustainable development. Full article