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Complex geological conditions, coupled with urban expansion, resource consumption, and rapid economic development, make the ecological environment of Chongqing's central urban area more vulnerable. To enhance the carrying capacity of resources and the environment in this region, it is significant to scientifically assess the trend of ecological risk changes in Chongqing. The article developed an ecological risk assessment index system for Chongqing, utilizing the "pressure-state-response" framework. The entropy weight method (EWM) is employed to assign weights to each variable, subsequently establishing a grey weighted clustering evaluation model (GWCEM). We evaluated the ecological risks of nine central urban areas in Chongqing from 2005 to 2021 and projected the ecological risk levels and changes from 2022 to 2025. Our research indicates that the comprehensive ranking of influencing factors of ecological risk in Chongqing follows this order: response factor > pressure factor > state factor. Throughout the study period, we observed a decrease in the ecological risk values of Ba'nan, Shapingba, Jiulongpo, Nan'an and Yubei Districts by more than 50%. These decline rates are accelerating and regional differences in ecological risk levels are diminishing. From 2022 to 2025, except Shapingba, Jiangbei, Yuzhong, and Nan'an District which consistently maintained a "low-risk" level, the ecological risk levels of all other areas continue to decrease, aligning with a "low-risk" classification by 2025. Based on the results of ecological risk assessment and ecological risk level prediction, corresponding recommendations are proposed for ecological environment protection and ecological risk management in the central urban area of Chongqing.

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At night, clear pavement markings are essential for driver safety. Currently, markings visibility evaluation relies on the retroreflectivity, but the impact of line width is unclear. To quantify the impact of line width on visibility and to refine visibility evaluation methods, a driver visual detection experiment was designed using both qualitative and quantitative approaches. Twenty-four drivers of small vehicles were randomly recruited to participate in visual detection tests of a total of 54 white pavement markings (comprising 6 widths and 9 retroreflectivity levels) under the illumination of high beams, following the principle of using the "emergence point" as the critical state for assessing pavement marking visibility. This study indicated that widening pavement markings significantly enhances their visibility, particularly for markings with low retroreflectivity. A visibility evaluation model was established to quantify the impact of width and retroreflectivity on the visual distance of markings. The model confirms that widening markings can improve visibility, thereby reducing the required level of retroreflectivity. The research methodology and findings provide technical support for managers to more accurately assess nighttime safety visibility during pavement marking operation and maintenance.

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Introduction: This study aims to develop a comprehensive evaluation model for urban tourism competitiveness in China. Given China's transition into a mature tourist destination, there is a pressing need for a framework that can assess the effectiveness of its urban tourism strategies. The model presented in this study is designed to provide a holistic understanding of the factors influencing urban tourism competitiveness in the Chinese context. Methods: The methodology employed in this study combines both qualitative and quantitative approaches. A modified version of Porter's Diamond Model serves as the primary framework, augmented by the IMD World Competitiveness Center: International Institute for Management Development (IMD) framework to incorporate social governance and environmental dimensions. To derive comprehensive scores for sustainable development, a linear weighted evaluation method was used, incorporating the coefficient of variation entropy weight method. This approach allows for a quantitative assessment of urban tourism competitiveness from 2008 to 2019. Results: The key findings of the study reveal significant challenges within the current urban tourism landscape in China. These challenges include homogeneous competition, a lack of strategic management, and insufficient service quality. Furthermore, the study identifies the need for greater emphasis on sustainable tourism development, balancing economic benefits with the preservation of cultural and natural assets. Discussion: Based on the findings, the study proposes several solutions to address the identified challenges. These solutions include creating boutique inland tourism routes, developing unique urban tourism brands, and enhancing regional cooperation and management practices. Additionally, the study emphasizes the importance of integrating community development and services into the evaluation model to foster sustainable tourism development. The proposed solutions offer actionable insights for policymakers and planners seeking to improve the competitiveness and sustainability of urban tourism in China.

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Reasonably allocating medical resources can effsectively optimize the utilization efficiency of such resources. This paper took Taiyuan City as an example and established a model to evaluate the rationality of medical resource spatial allocation, incorporating two key dimensions: the spatial layout and the supply and demand of medical resources. In terms of the spatial layout, three indexes were included: Firstly, the service coverage rates of different levels of medical institutions, based on residents' medical orientations, were calculated using network analysis methods. Secondly, the Huff-2SFCA method was improved to calculate the accessibility of medical resources for four different modes of transportation. Then, the Health Resource Agglomeration Degree (HRAD) and Population Agglomeration Degree (PAD) were used to quantify the equity of medical resources. In terms of the supply and demand of medical resources, one index was included: the supply-demand ratio of medical resources during sudden public health events, which was calculated using the number of beds per thousand people as an indicator. These four indexes were weighted using the entropy weight method to obtain the rationality grade of medical resource spatial allocation in Taiyuan City. The study found that the rationality evaluation level of medical resource allocation in the central urban area of Taiyuan City followed a "concentrically decreasing" pattern. The rating ranged from "very reasonable" to "less reasonable", with the area of each level expanding gradually. The areas rated within the top two categories only accounted for 19.92% of the study area, while the area rated as "less reasonable" occupied 38.73% of the total area. These results indicate that the model accounted for residents' travel for various medical orientations and the availability of resources during public health emergencies. It considered both the spatial layout and supply and demand of medical resources, offering recommendations for the precise allocation of urban medical resources.

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The transmission environment of underwater wireless sensor networks is open, and important transmission data can be easily intercepted, interfered with, and tampered with by malicious nodes. Malicious nodes can be mixed in the network and are difficult to distinguish, especially in time-varying underwater environments. To address this issue, this article proposes a GAN-based trusted routing algorithm (GTR). GTR defines the trust feature attributes and trust evaluation matrix of underwater network nodes, constructs the trust evaluation model based on a generative adversarial network (GAN), and achieves malicious node detection by establishing a trust feature profile of a trusted node, which improves the detection performance for malicious nodes in underwater networks under unlabeled and imbalanced training data conditions. GTR combines the trust evaluation algorithm with the adaptive routing algorithm based on Q-Learning to provide an optimal trusted data forwarding route for underwater network applications, improving the security, reliability, and efficiency of data forwarding in underwater networks. GTR relies on the trust feature profile of trusted nodes to distinguish malicious nodes and can adaptively select the forwarding route based on the status of trusted candidate next-hop nodes, which enables GTR to better cope with the changing underwater transmission environment and more accurately detect malicious nodes, especially unknown malicious node intrusions, compared to baseline algorithms. Simulation experiments showed that, compared to baseline algorithms, GTR can provide a better malicious node detection performance and data forwarding performance. Under the condition of 15% malicious nodes and 10% unknown malicious nodes mixed in, the detection rate of malicious nodes by the underwater network configured with GTR increased by 5.4%, the error detection rate decreased by 36.4%, the packet delivery rate increased by 11.0%, the energy tax decreased by 11.4%, and the network throughput increased by 20.4%.

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Cuscuta chinensis have a significant regulatory effect on plant growth, but the response mechanism of functional traits to the parasitism of C. chinensis and the trade-off relationship between traits and hyperspectral characteristics are not clear. We investigated the functional trait response and hyperspectral characteristics of Euonymus japonicus, the most common urban hedge plant in China, to the parasitism of C. chinensis. The results showed that the parasitism of C. chinensis led to the difference of leaf functional traits: the leaf thickness, stomatal density, and leaf dry matter content were significantly increased, whereas the leaf area, leaf weight, specific leaf area, chlorophyll content index, and leaf tissue density were significantly decreased. Notably, the parasitism of C. chinensis changed the spatial distribution pattern of stomata and promoted the stomata to be evenly distributed. Furthermore, the spectral reflectance of leaves treated with the parasitism of C. chinensis tended to increase. The parasitism of C. chinensis led to the "blue shift" of hyperspectral reflectance of leaves. There was a significant correlation between spectral parameters and leaf functional traits, and leaf biomass accounted for 83% of the variation in reflectance of the water stress band. In general, the parasitism of C. chinensis determines the strategic way of plant utilization of resources and affects the change of plant strategy by affecting the difference of traits. Urban plants were more inclined to invest resources in nutrient storage capacity at the expense of resources investment in photosynthetic capacity and defense mechanism. The plant ecological strategy changed from resource acquisition to resource conservation. This finding comes up with a new strategy that urban tree species can modify the plasticity of functional traits for survival and growth under the interference of parasitic plants.

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Human milk phospholipids (HMPLs) play an indispensable role in the neurodevelopment and growth of infants. In this study, a total of 37 phospholipid fatty acid (PLFA) species and 139 phospholipid molecular species were detected from human milk and other natural phospholipid sources (including 5 animal-derived species and 2 plant species). Moreover, a similarity evaluation model for HMPLs was established, including phospholipid classes, PLFAs, and phospholipid molecular species, to evaluate their natural substitutes. The closest scores for HMPL substitute in these three dimensions was 0.89, 0.72, and 0.77, which belonged to mare milk, goat milk, and camel milk, respectively. The highest comprehensive similarity score was obtained by camel milk at 0.75, while the lowest score was observed in soybean phospholipid (0.22). Therefore, these results not only monitored the stereochemical structure of HMPLs and their substitutes, but also further provided new insights for the development of infant formulae.

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BACKGROUND: Self-management of a chronic condition is a complex but increasingly important issue. However, a supportive attitude and behaviour among healthcare professionals is hampered by a lack of awareness, knowledge and motivation. In addition, the role of professionals in supporting self-management seems unclear. METHODS: A blended learning program for primary healthcare professionals was developed to strengthen self-management support in primary care. The program was piloted in community health centres and multidisciplinary medical practices in Flanders. Using the Kirkpatrick model, the impact on healthcare professionals' reaction, learning and behaviour regarding self-management support was evaluated. RESULTS: A total of 60 healthcare professionals registered for the educational program. Post-learning questionnaires and verbal feedback showed a positive response, with professionals highly appreciating the innovative blended learning approach. In terms of learning, participants showed a good understanding of self-management support, although nuances were observed in the application of acquired knowledge to practice scenarios. Finally, preliminary insights into behavioural change were explored, revealing a positive impact of the intervention on participants' supportive self-management behaviours in healthcare practice. CONCLUSIONS: Our study provides preliminary insights into the outcomes of a blended learning program designed to increase awareness and knowledge of self-management support among professionals. The program needs to be refined for general implementation in primary care.

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In order to augment the efficacy of the intelligent evaluation model for assessing the suitability of ice and snow tourism, this study refines the model by incorporating the Long Short-Term Memory (LSTM) network within the framework of the Internet of Things (IoT). The investigation commences with an elucidation of the application of IoT technology in environmental detection. After this, an analysis is conducted on the structure of LSTM and its merits in the realm of time series prediction. Ultimately, a novel model for appraising the suitability of ice and snow tourism is formulated. The efficacy of this model is substantiated through empirical experiments. The results of these experiments reveal that the refined model exhibits exceptional performance across diverse climatic conditions, encompassing mild, cold, humid, and arid climates. In regions characterized by mild climates, the predictive accuracy of the refined model progressively ascends from 88% in the initial quarter to 94% in the fourth quarter, surpassing the capabilities of conventional models. Consistently robust performance is demonstrated by the refined model throughout each quarter. In terms of operational efficiency, comparative analysis indicates that the refined model attains a moderate level, manifesting a 30-33 s runtime and maintaining a Central Processing Unit (CPU) usage rate between 40 and 43%. This observation implies that the refined model adeptly balances precision against resource consumption. Consequently, this study holds significance as a scholarly reference for the integration of IoT and LSTM networks in the domain of tourism evaluation.

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OBJECTIVE: The prognosis of stroke patients is greatly threatened by malnutrition. However, there is no model to predict the risk of malnutrition in hospitalized stroke patients. This study developed a predictive model for identifying high-risk malnutrition in stroke patients. METHODS: Stroke patients from two tertiary hospitals were selected as the objects. Binary logistic regression was used to build the model. The model's performance was evaluated using various metrics including the receiver operating characteristic curve, Hosmer-Lemeshow test, sensitivity, specificity, Youden index, clinical decision curve, and risk stratification. RESULTS: A total of 319 stroke patients were included in the study. Among them, 27% experienced malnutrition while in the hospital. The prediction model included all independent variables, including dysphagia, pneumonia, enteral nutrition, Barthel Index, upper arm circumference, and calf circumference (all p < 0.05). The AUC area in the modeling group was 0.885, while in the verification group, it was 0.797. The prediction model produces greater net clinical benefit when the risk threshold probability is between 0% and 80%, as revealed by the clinical decision curve. All p values of the Hosmer test were > 0.05. The optimal cutoff value for the model was 0.269, with a sensitivity of 0.849 and a specificity of 0.804. After risk stratification, the MRS scores and malnutrition incidences increased significantly with escalating risk levels (p < 0.05) in both modeling and validation groups. CONCLUSIONS: This study developed a prediction model for malnutrition in stroke patients. It has been proven that the model has good differentiation and calibration.

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With the tourism industry continuing to boom, the importance of tourism mascots in promoting and publicizing tourism destinations is becoming increasingly prominent. Three core dimensions, market trend, appearance design, and audience feedback, are numerically investigated for deeply iterating tourism mascot design. Further, a subjective and objective evaluation weighting model based on the hierarchical analysis method (AHP) and entropy weighting method is proposed, aiming to utilize the advantages of these methods and ensure the entireness and correctness of results. Taking the mascots of six famous tourist attractions in Xi'an as an example, the feasibility and effectiveness of the evaluation model are verified. Data analysis and modeling results confirm that the three core evaluation indexes of scalability, innovation, and recommendation should be focused on in the design of tourism mascots in the three dimensions of market trends, appearance design, and audience feedback. The evaluation index scores are 0.1235, 0.1170, and 0.1123, respectively, which further illustrates the priority of mascot design. The evaluation model constructed by the research provides decision-makers with a comprehensive evaluation tool from the perspective of tourist experience, and also effectively assists the optimization process of mascot design. In addition, the model has good versatility and adaptability in structural design and evaluation logic and can be widely used in the optimization and evaluation research of brand mascots.

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Advancements in information technology have facilitated the emergence of mHealth apps as crucial tools for health management and chronic disease prevention. This research work focuses on mHealth apps for the management of diabetes by patients on their own. Given that China has the highest number of diabetes patients in the world, with 141 million people and a prevalence rate of 12.8% (mentioned in the Global Overview of Diabetes), the development of a usability research methodology to assess and validate the user-friendliness of apps is necessary. This study describes a usability evaluation model that combines task analysis methods and eye movement data. A blood glucose recording application was designed to be evaluated. The evaluation was designed based on the model, and the feasibility of the model was demonstrated by comparing the usability of the blood glucose logging application before and after a prototype modification based on the improvement suggestions derived from the evaluation. Tests showed that an improvement plan based on error logs and post-task questionnaires for task analysis improves interaction usability by about 24%, in addition to an improvement plan based on eye movement data analysis for hotspot movement acceleration that improves information access usability by about 15%. The results demonstrate that this study presents a usability evaluation model for mHealth apps that enables the effective evaluation of the usability of mHealth apps.

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The paper discusses the concept of a proprietary decision-making model that allows for determining whether the planned development in areas not protected by flood embankments and at risk of flooding can be shaped in a safe manner. The model was used to evaluate the possibility of shaping the development in flood-risk areas on the example of one of the types of Oleder villages - a dispersed village located in the floodplains of the Warta River (western Poland). So far, there has been no comprehensive evaluation method supporting proper spatial planning for flood-risk areas. The use of multi-criteria analysis methods enabled to specify the key criteria of this evaluation, which form the basis of the decision-making support system. Additionally, the elaborated method enables to determine whether the localities under study can retain their current functional nature and if there is a potential for further spatial development based on the characteristics of an Oleder village. The presented methodology can be easily adapted to other cultural areas located in countries with different levels of development, traditions, landscape or climate.

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The bivalent fear of evaluation (BFOE) model of social anxiety divides fear of evaluation into two distinct valences: fear of positive evaluation (FPE) and fear of negative evaluation (FNE). However, there is evidence that the two most widely utilized and psychometrically supported measures of FNE and FPE contain items which are ambiguous with regard to valence of evaluative fear. To formally address this, the BFOE Scale (BFOES) was developed, by merging items from measures of FNE and FPE into a single scale with an integrated response format. The present studies examined the psychometric profile of the BFOES across a large pooled archival dataset (N = 2216), which included approximately 10 % (n = 224) patients with social anxiety disorder (SAD). The factorial validity, internal consistency, and construct validity of the BFOES were examined. Additionally, item response theory analyses were employed for the purpose of merging items from self-report scales which utilized different Likert-type response formats. Results from both studies provided support for the psychometric profile of the BFOES. The implications of the BFOES for the assessment of social anxiety, and theoretical models of fear of evaluation and SAD, are discussed.

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In order to improve the level of mine ecological environment management and restoration, and to improve and enhance the overall environmental quality of mines. This study takes coal mine as the perspective, and constructs evaluation indexes in two steps, i.e., social network analysis method and relevant policy documents are combined to construct evaluation indexes. The indicator system contains 5 first-level indicators and 23 s-level indicators, and the triangular fuzzy number hierarchical analysis method is introduced to determine the comprehensive weight of each evaluation indicator, which overcomes the inadequacy of the objective empowerment method or the subjective empowerment method of single empowerment. The grey correlation analysis theory is used to establish a grey correlation evaluation model of mine ecological environment, which is applied to the evaluation of ecological environmental protection level of four coal mines in a province of China, making full use of the information of each index for quantitative evaluation, and finally obtaining the evaluated value of ecological environmental protection level of each coal mine. It is demonstrated that the evaluation model can make scientific and effective evaluation of the level of ecological environmental protection in mines. The study concludes that coal mines should pay attention to improving the comprehensive utilization rate of coal gangue in the next mine ecological environment management and restoration, and at the same time, reduce the ton of coal power consumption, ton of coal water consumption, and Increase in vegetation cover. This study provides a useful evaluation method for ecological environment management in mining areas, which is helpful to improve the quality of ecological management in mining areas.

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Ni-Mn@KL ozone catalyst was prepared for the efficient treatment of reverse osmosis membrane concentrates. The working conditions and reaction mechanism of the ozone-catalyzed oxidation by Ni-Mn@KL were systematically studied. Then, a comprehensive CRITIC weighting-coupling coordination evaluation model was established. Ni-Mn@KL was characterized by scanning electron microscopy, BET, X-ray diffraction, X-ray photoelectron spectroscopy, energy-dispersive spectrometry, and X-ray fluorescence spectrometry and found to have large specific surface area and homogeneous surface dispersion of striped particles. Under the optimum working conditions with an initial pH of 7.9 (raw water), a reaction height-to-diameter ratio of 10:1, an ozone-aeration intensity of 0.3 L/min, and a catalyst filling rate of 10%, the maximum COD removal rate was 60.5%. Free-radical quenching experiments showed that OH oxidation played a dominant role in the Ni-Mn@KL-catalyzed ozone-oxidation system, and the reaction system conformed to the second-order reaction kinetics law. Ni-Mn@KL catalysts were further confirmed to have good catalytic performance and mechanical performance after repeated utilization. PRACTITIONER POINTS: Ni-Mn@KL catalyst can achieve effective treatment of RO film concentrated liquid. High COD removal rate of RO membrane concentrated liquid was obtained at low cost. Ni-Mn@KL catalyst promotes ozone decomposition to produce ·OH and O2 -· oxidized organic matter. The Ni-Mn@KL catalyst can maintain good stability after repeated use. A CRITIC weight-coupling coordination model was established to evaluate the catalytic ozonation.

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OBJECTIVE: To identify the current research hotspots of global health training, and construct a global health talent training evaluation index system. METHODS: Publications pertaining to global health talent training evaluation were retrieved in China National Knowledge Infrastructure, Wanfang Database, and Web of Science Core Collection from 2003 to 2022, and keywords were extracted from eligible publications for co-occurrence and cluster analyses using the CiteSpace software. Based on keywords clustering results, a global health talent training evaluation index system was constructed using a context, input, process, and product (CIPP) evaluation model as a theoretical framework. RESULTS: A total of 692 Chinese publications and 1 264 English publications were included. Keyword co-occurrence and cluster analyses yielded 10 Chinese and 10 English keyword clusters, and the 10 Chinese keyword clusters included analytic hierarchy process, health diplomacy, personnel structure, crossdiscipline, educational assessment, global health discipline development, training needs, curriculum program, quality evaluation and logistics support, while the English keyword clusters included evidence-based practice, capacity building, global health, quality of life, machine learning, leadership, sub-Saharan Africa, health equity, global health security and global health diplomacy. Based on keyword clustering, a global health talent training evaluation index system was constructed with CIPP as the theoretical framework, which contained 4 primary indicators, 15 secondary indicators and 59 tertiary indicators, and the primary indicators included 4 dimensions of context evaluation, input evaluation, process evaluation and product evaluation. CONCLUSIONS: A global health talent training evaluation index system has been constructed, which provides an effective evaluation tool and quantitative evidence for future global health talent training.

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With the continuous development and application of online interactive activities and network transmission technology, online interactive behaviors such as online discussion meetings and online teaching have become indispensable in people's studies and work. However, the effectiveness of working with online discussions and feedback from participants on their conference performance has been a major concern, and this is the issue examined in this post. Based on the above issues, this paper designs an online discussion activity-level evaluation system based on voiceprint recognition technology. The application system developed in this project is divided into two parts; the first part is to segment the online discussion audio into multiple independent audio segments by audio segmentation technology and train the voiceprint recognition model to predict the speaker's identity in each separate audio component. In the second part, we propose a linear normalized online meeting activity-level calculation model based on the modified main indexes by traversing and counting each participant's speaking frequency and total speaking time as the main indexes for activity-level evaluation. To make the evaluation results more objective, reasonable, and distinguishable, the activity score of each participant is calculated, and each participant's activity-level in the discussion meeting is derived by combining the fuzzy membership function. To test the system's performance, we designed an experiment with 25 participants in an online discussion meeting, with two assistants manually recording the discussion and a host moderating the meeting. The results of the experiment showed that the system's evaluation results matched those recorded by the two assistants. The system can fulfill the task of distinguishing the level of activity of participants in online discussions.

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We aimed to obtain the optimal formula for human milk fat substitute (HMFS) through a combination of software and an evaluation model and further verify its practicability through an animal experiment. The results showed that a total of 33 fatty acid (FA) and 63 triglyceride (TAG) molecular species were detected in vegetable oils. Palmitic acid, oleic acid, linoleic acid, 18:1/16:0/18:1, 18:2/16:0/18:2, 18:1/18:1/18:1 and 18:1/18:2/18:1, were the main molecular species among the FAs and TAGs in the vegetable oils. Based on the HMFS evaluation model, the optimal mixed vegetable oil formula was blended with 21.3% palm oil, 2.8% linseed oil, 2.6% soybean oil, 29.9% rapeseed oil and 43.4% maize oil, with the highest score of 83.146. Moreover, there was no difference in the weight, blood routine indices or calcium and magnesium concentrations in the feces of the mice between the homemade mixed vegetable oil (HMVO) group and the commercial mixed vegetable oil (CMVO) group, while nervonic acid (C24:1) and octanoic acid (C8:0) were absorbed easily in the HMVO group. Therefore, these results demonstrate that the mixing of the different vegetable oils was feasible via a combination of computer software and an evaluation model and provided a new way to produce HMFS.

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The growing generation of construction and demolition waste (CDW) has emerged as a prominent challenge on global environmental agendas. However, the effectiveness of CDW management (CDWM) strategies varies among cities. Existing literature predominantly evaluates the effectiveness of CDWM at the project level, offering a localized perspective that fails to capture a city's comprehensive CDWM profile. This localized focus has certain limitations. To fill this gap in city-scale evaluations, this study introduces a novel model for assessing CDWM effectiveness at the municipal level. An empirical investigation was conducted across 11 cities within the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) to operationalize this model. The model defines five distinct levels of CDWM effectiveness. Findings indicate that Hong Kong consistently achieves the highest level (level I), while the majority of cities fall within levels III and IV. This pattern suggests that CDWM effectiveness in the GBA is moderately developed, with uneven progress in CDW management outcomes and supporting systems. Essentially, there is a lack of synchronous development of CDWM results and guarantee systems. The proposed evaluation model enriches existing CDWM research field and offers a framework that may inform future studies in other countries.

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