Search Results (63,874)

The hydrogeochemical properties and evolution of groundwater in the Essaouira syncline basin in northwestern Morocco were investigated in this study, with a total of 447 samples during different campaigns (April 2017, May 2018, March 2019, and July 2020). These samples were analyzed for major ions and stable and radioactive water isotopes (δ²H, δ¹⁸O, and ³H). With decreasing rainfall from climate change in Morocco, it is crucial to assess the sustainability of groundwater reserves. This shortage leads to the degradation of water and soil quality. To ensure sustainable water management and preserve the environment in the study area, it is necessary to assess groundwater quality for drinking and irrigation, take precautions, and establish management plans. This study assessed groundwater quality using two water quality index methods (WQI and IWQI). Several natural processes control groundwater mineralization, including the dissolution of evaporite and carbonate minerals, cation exchange phenomena, evaporation, and seawater intrusion. According to the results obtained using the WQI method, all groundwater samples in the study area are generally of poor quality and must be treated before being used for domestic purposes. Based on the results obtained by the IWQI method, the samples are suitable for use as irrigation water, especially for plants resistant to high salinity concentrations. Stable isotope measurements (δ²H and δ¹⁸O) indicate that Atlantic precipitation continuously recharges the recharge areas of the Essaouira Basin. Thus, the low values of tritium (³H) in groundwater mean that the freshwater in the Essaouira Basin is ancient. Full article

Background: This study presents a comprehensive analysis of cholesteatoma of the middle ear, focusing on its clinical presentation, diagnostic imaging, and treatment outcomes. Cholesteatomas are defined by the keratinized squamous epithelium within the middle ear, leading to significant bone erosion, often affecting the ossicular chain and surrounding structures. Methods: The study explores various mechanisms involved in cholesteatoma progression, including enzymatic lysis, inflammatory responses, and neurotrophic disturbances. The study conducted a retrospective clinical and statistical review of 580 patients over a 20-year period (2003–2023), highlighting the role of advanced imaging, including computed tomography (CT) and diffusion-weighted magnetic resonance imaging (DWI), in preoperative planning and postoperative follow-up. Results: Findings revealed that early detection and intervention are crucial in preventing severe complications such as intracranial infection and hearing loss. Surgical treatment primarily involved tympanoplasty and mastoidectomy, with a recurrence rate of 1.55% within two years. The study underscores the importance of integrating imaging advancements into clinical decision-making to enhance patient outcomes and suggests further investigation into molecular mechanisms underlying cholesteatoma progression and recurrence. Histopathological and microbiological analysis was performed to identify pathological patterns and microbial agents. Conclusions: The study highlights the importance of early diagnosis and intervention to prevent complications such as intracranial infections and permanent hearing loss, while also emphasizing the role of advanced imaging techniques in the management and long-term monitoring of cholesteatoma patients. Full article

As the socio-economic landscape expands and tourism flourishes, the traditional earthen dwellings of Tuyugou Village, Turpan, Xinjiang, face significant challenges, including low energy efficiency and suboptimal living comfort, necessitating data-driven and scientifically robust renovation strategies. Existing renovation methods, however, often lack empirical support and rely heavily on the subjective judgments of architects, thus hindering the effective preservation and transmission of cultural heritage. This research addresses the renovation of these traditional dwellings by employing the AHP method to systematically evaluate user requirements, with input from diverse stakeholders, including homeowners, tourists, experts, and government authorities. The study then applies the QFD method to construct the House of Quality, translating user needs into specific design attributes; this is followed by a comprehensive quantitative analysis for optimization. A novel multi-objective optimization model (MOP) is introduced, with materials as the central focus, addressing key aspects of engineering, culture, and energy conservation. The NSGA-II algorithm is utilized to generate optimal Pareto solutions, which are then further refined using the entropy-weighted VIKOR method. Among the ten pre-selected renovation solutions, the sixth design plan was identified as the optimal choice, excelling in cost control, cultural integration, and energy performance. Specifically, it achieved a unit construction cost of RMB 340.566/m², a cultural adaptability score of 1.5364, and an energy cost of RMB 352.793/kWh, thereby demonstrating an effective balance between traditional architectural elements and modern requirements. The objective decision making enabled by the VIKOR method successfully balances cultural preservation with contemporary needs, enhancing both living standards and tourism appeal. This study offers innovative and empirically grounded renovation strategies for traditional dwellings in arid and semi-arid climates, providing a framework that effectively balances cultural preservation and modernization. Full article

In the context of the construction of new liberal arts, the integration and intersection of disciplines have become a new trend in the development of higher education. How to promote the teaching reform of big data technology and application courses in the new liberal arts construction scenario has become an important issue in enhancing students’ digital talent literacy and social adaptability. In this study, an extended probabilistic linguistic TODIM (an acronym in Portuguese for interactive multi-criteria decision making) with probabilistic linguistic entropy weight and Hamming distance is presented for teaching reform plan evaluation for the core course “big data technology and applications” in the digital economy major. Firstly, probabilistic linguistic entropy weight, based on the entropy of the additive linguistic term set, is applied to generate weight information. Secondly, parameter sensitivity analysis is carried out to prove the stabilization and effectiveness of the extended TODIM approach. Thirdly, this extended approach can integrate the psychological factors and cognitive behaviors of decision-makers for effectively responding to education management in the new liberal arts construction scenario. Finally, a case study on teaching reform plan evaluation is carried out, and a comparative analysis with different criteria weights and different methods is conducted to verify the extended approach. The results indicate that the extended approach can provide an effective technical tool for scientific decision-making, especially in the teaching reform plan evaluation scenario in order to promote high-quality development of education. Full article

Natural disasters have increasingly threatened human life, infrastructure, and ecosystems, exacerbated by climate change, urbanization, and deforestation. Effective disaster risk management is crucial to mitigate these impacts. Traditionally, Geographic Information Systems (GISs) have provided spatial data analysis capabilities, but the advent of Web-GIS applications has revolutionized this field. Web-GIS platforms enable real-time data access and facilitate enhanced stakeholder collaboration. This paper details the development of a Web-GIS application tailored for hydrogeological risk management in Cervo Valley, part of the NODES—Nord Ovest Digitale e Sostenibile project under Italy’s National Recovery and Resilience Plan (NRRP). The application integrates both static and dynamic geospatial data to create an interactive interface for evaluating and planning responses to hydrogeological hazards, specifically floods, landslides, and debris flow cones. By utilizing advanced Web-GIS capabilities, the project aims to refine the risk management practices and decision-making processes, thereby bolstering territorial resilience and addressing contemporary spatial challenges with enhanced precision and efficiency. Full article

Coverage path planning describes the process of finding an effective path robots can take to traverse a defined dynamic operating environment where there are static (fixed) and dynamic (mobile) obstacles that must be located and avoided in coverage path planning. However, most coverage path planning methods are limited in their ability to effectively manage the coordination of multiple robots operating in concert. In this paper, we propose a novel coverage path planning model (termed Multi-ST) which utilizes the spiral-spanning tree coverage algorithm with intelligent reasoning and knowledge-based methods to achieve optimal coverage, obstacle avoidance, and robot coordination. In experimental testing, we have evaluated the proposed model with a comparative analysis of alternative current approaches under the same conditions. The reported results show that the proposed model enables the avoidance of static and moving obstacles by multiple robots operating in concert in a dynamic operating environment. Moreover, the results demonstrate that the proposed model outperforms existing coverage path planning methods in terms of coverage quality, robustness, scalability, and efficiency. In this paper, the assumptions, limitations, and constraints applicable to this study are set out along with related challenges, open research questions, and proposed directions for future research. We posit that our proposed approach can provide an effective basis upon which multiple robots can operate in concert in a range of ‘real-world’ domains and systems where coverage path planning and the avoidance of static and dynamic obstacles encountered in completing tasks is a systemic requirement. Full article

The deformation of the No. 65 slope on the Shangsan Expressway poses a potential threat to road safety. In July 2021, the deformation rate of this slope accelerated significantly, leading to the implementation of reinforcement measures in 2022. To comprehensively analyze the historical deformation characteristics of the slope and evaluate the effectiveness of the reinforcement measures, this study employs Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technology to calculate and analyze the historical deformation characteristics of the slope and the adjacent hillside for two periods: from 10 January 2018 to 22 August 2021, and from 3 September 2021 to 22 December 2023. The SBAS-InSAR monitoring results were compared with in situ data from borehole inclinometers to verify the reliability of the calculations. The SBAS-InSAR results indicate that before reinforcement, the slope exhibited slow movement; however, after the implementation of the reinforcement measures, the displacement significantly decreased, demonstrating the success and effectiveness of the interventions. The consistency between the SBAS-InSAR results, borehole inclinometer data, and surface observations confirms the substantial potential of SBAS-InSAR technology for slope engineering monitoring. Full article

Life cycle asset allocation is a crucial aspect of financial planning, especially for pension funds. Traditional methods often face challenges in computational efficiency and applicability to different market conditions. This study aimed to innovatively transplant an algorithm from reinforcement learning that enhances the efficiency and accuracy of life cycle asset allocation. We synergized tabular methods with Monte Carlo simulations to solve the pension problem. This algorithm was designed to correspond states in reinforcement learning to key variables in the pension model: wealth, labor income, consumption level, and proportion of risky assets. Additionally, we used cleaned and modeled survey data from Chinese consumers to validate the model’s optimal decision-making in the Chinese market. Furthermore, we optimized the algorithm using parallel computing to significantly reduce computation time. The proposed algorithm demonstrated superior efficiency compared to the traditional value iteration method. Serial execution of our algorithm took 29.88 min, while parallel execution reduced this to 1.42 min, compared to the 41.15 min required by the value iteration method. These innovations suggest significant potential for improving pension fund management strategies, particularly in the context of the Chinese market. Full article

With the rapid development of space exploration technology, the detection of extraterrestrial bodies has become increasingly important. Among these, path planning and target recognition and positioning technologies are particularly critical for applications in intelligent agents with low computational power operating in complex environments. This paper presents a novel approach to path planning on low-resolution lunar surface maps by introducing an improved A* algorithm with an adaptive heuristic function. This innovation enhances robustness in environments with limited map accuracy and enables paths that maintain maximum distance from obstacles. Additionally, we innovatively propose the Dynamic Environment Target Identification and Localization (DETIL) algorithm, which identifies unknown obstacles and employs spatiotemporal clustering to locate points of interest. Our main contributions provide valuable references for the aerospace industry, particularly in lunar exploration missions. The simulation results demonstrate that the improved A* algorithm reduces the maximum elevation difference by 55% and the maximum cumulative elevation difference by 68% compared to the traditional A* algorithm. Furthermore, the DETIL algorithm’s obstacle identification component successfully recognizes all the obstacles along the path, and its spatiotemporal clustering improves the average number of target discoveries by 152% over the conventional DBSCAN clustering approach. Full article

Bridge infrastructure provides an important effect on contemporary transportation networks, and its upkeep is significant for ensuring public safety and reducing economic impacts. Nevertheless, the aging and degradation of bridge structures present considerable challenges for asset managers, who must navigate the necessity of maintenance against constrained financial resources. Conventional maintenance approaches typically emphasize reactive repairs, which can result in elevated lifecycle expenses and risk structural integrity. This paper introduces an innovative framework aimed at optimizing bridge maintenance expenditures while maintaining structural safety. The proposed methodology incorporates a reliability-based deterioration model, an intervention effect model, a financial model, and an optimization model empowered by an Improved Electric Fish Optimization (IEFO) algorithm. The framework is demonstrated through a case study of a reinforced bridge framework designed according to the standards of Canadian highway bridge design. The findings illustrate that the proposed methodology can substantially lower lifecycle costs by investigating the most economical maintenance strategies, including minor repairs that can postpone the necessity for expensive major interventions. The optimal scenario identified by the IEFO algorithm yielded lower equivalent uniform annual costs in comparison with the traditional scenario focused solely on major repairs. This research advances the field of data-driven maintenance planning for bridge infrastructure, empowering asset managers to make well-informed decisions that effectively balance cost and safety considerations. Full article

The urgent need to mitigate climate change and reduce reliance on fossil fuels has driven the global shift towards renewable energy sources (RESs). However, the intermittent nature of RESs poses significant challenges to the widespread adoption of Zero-Carbon Smart Grids (ZCSGs). This study proposes a synergistic framework to address this hurdle. It utilizes energy storage systems (ESSs) by comparing Vanadium redox flow batteries (VRFBs) and Lithium ion batteries (LIBs) to identify the most suitable option for ZCSGs, with precise models enabling robust performance evaluation. Moreover, an accurate demand-side management (DSM) strategy considering power elasticity to manage discrepancies between electricity load, RES generation, and ESS availability is introduced for estimating fair, dynamic tariffs. An advanced load and weather-forecasting strategy is introduced for improving grid planning and management. An advanced optimization algorithm enhances grid stability and efficiency. Simulations demonstrate significant reductions in carbon footprint, peak power demand, and reliance on fossil fuels. The study finds that VRFBs outperform LIBs in cost and security, and dynamic tariffs based on accurate DSM significantly reduce energy costs. This work explores the challenges and opportunities of this integrated approach, offering policy recommendations and future research directions for truly optimized ZCSG implementation. Full article

Continuous advancements in technology have made it possible to integrate clear aligner therapy (CAT) with orthognathic surgery. This case report presents a novel, individually-planned workflow, combining CAT with a surgery-first orthognathic approach (SFOA) in collaborating with engineers for an in-house production of surgical guides and customized titanium plates. The patient was evaluated subjectively, using the Oral Health-Related Quality of Life-14 (OHIP-14) questionnaire and Orthognathic Quality of Life questionnaire (OQLQ), and objectively with the Peer Assessment Rating (PAR) index. The patient displayed the planned occlusal relationship with no report of discomfort in the temporomandibular joint (TMJ) or post-surgical complications. The surgical and occlusal outcomes have remained consistent and stable after debonding. A decreased score was reported in both questionnaires and the PAR after treatment, thereby indicating improvements in both subjective and objective evaluations. This case report demonstrates that with proper individual planning, satisfactory subjective and objective outcomes can be achieved when combining SFOA with CAT. Full article

The process of industrial transformation, becoming the most important for building up sustainable cities, is in urgent need for studying alternative options for land use to ensure sustainable city development. Rapid urbanization requires new built-up design in strong correlation with urban spatial planning issues. The objective of this paper is to contribute for the studies of sustainable land use solutions through investigating the problems of the reorganization of depressed industrial areas. The research methodology is based on the multicriteria decision-making method to provide primarily social functions of depressed industrial areas, depending on environmental and economic aspects of their historical location in urban structure. Since the article highlights the concept of the 15-min city to build a polycentric urban spatial structure, the assessment of supply and demand matching of social facilities is based on the analysis of 15 min accessibility to the serviced within either industrial zone and the city on the whole. The GIS spatial analysis method supports the developed criteria set to evaluate main city functions. The research provides the methodology for defining the priority land use solution for a specific industrial area in a specific location. The proposed methodology suggests a procedure for evaluating the importance of the land use composition for the city community, considering environmental requirements and cost-effectiveness of the project. Three different industrial zones located in the same city are a case study to asses the reliability of the proposed methodology. The research conclusion provides implementing sustainable land-use solutions for improving urban environment quality as well as the quality of life for the population. Full article

The COVID-19 pandemic and similar public health emergencies have significantly impacted global travel patterns. Analyzing the recovery characteristics of subway station-level passenger flow during the pandemic recovery phase can offer unique insights into public transportation operations and guide practical planning efforts. This pioneering study constructs a station-level passenger flow recovery resilience (PFRR) index during the rapid recovery phase using subway AFC system swipe data. Additionally, it develops an analytical framework based on a multiscale geographically weighted regression (MGWR) model, the improved gray wolf optimization with Levy flight (LGWO), and light gradient boosting machine (LightGBM) regression to analyze passenger flow resilience on weekdays and weekends in relation to land use-related built environment types. Finally, SHAP attribution analysis is used to study the nonlinear relationships between built environment variables and PFRR index. The results show significant spatial heterogeneity in the impact of commercial, recreational, and residential land, as well as POI (points of interest) of leisure and shopping on PFRR. On weekdays, the most relevant built environment variables for PFRR are POI of enterprises and shopping numbers. In contrast, the contribution of built environment variables affecting PFRR of weekend is more balanced, reflecting the recovery of non-essential travel on weekends. Most land use-related built environment variables exhibit nonlinear associations with PFRR values. The proposed analytical framework shows significant performance advantages over other baseline models. This study provides unique insights into subway passenger flow characteristics and surrounding land use-related development layouts under the impact of public health emergencies. Full article

The warming slowdown observed between 1998 and 2012 has raised concerns in recent years. To examine the temporal and spatial variations in annual mean temperature (Tmp) as well as 12 extreme temperature indices (ETIs), and to assess the presence of a warming slowdown in North China (NC), we analyzed homogenized daily observational datasets from 79 meteorological stations spanning 1960 to 2020. Additionally, we investigated the influences of 78 atmospheric circulation indices (ACIs) on ETIs during the period of warming slowdown. To compare temperature changes, the study area was divided into three parts based on topographic conditions: Areas I, II, and III. The results revealed significant warming trends in Tmp and the 12 ETIs from 1960 to 2020. Comparing the time frames of 1960–1998, 2012–2020, and 1998–2012, both Tmp and the 12 ETIs displayed a cooling trend in the latter period, confirming the existence of a warming slowdown in NC. Notably, indices derived from daily maximum temperature exhibited higher cooling rates during 1998–2012, with winter contributing most significantly to the cooling trend among the four seasons. The most pronounced warming slowdown was observed in Area I, followed by Area III and Area II. Furthermore, our attribution analysis of ACIs concerning the temperature change indicated that the Asia Polar Vortex Area Index may have had the greatest influence on ETIs from 1960 to 2016. Moreover, the weakening of the Tibet Plateau Index Band and the Asian Latitudinal Circulation Index, and the strengthening of the Eurasian Latitudinal Circulation Index, were closely associated with ETIs during the warming slowdown period in NC. Through this research, we aim to deepen our understanding of climate change in NC and offer a valuable reference for the sustainable development of its natural ecology and social economy. Full article