Underground station passenger flow is large, the number of parcels carried by passengers is large and varied, and the parcels carried have an impact on the fire hazard and evacuation of the station. In order to determine the weights of the passenger luggage risk and environmental factor index system in the fire risk evaluation of underground stations in a more realistic way, an optimized and improved hierarchical analysis method for determining the judgement matrix is proposed, which improves the traditional nine-scaled method and adopts the three-scaled method for the four major categories of luggage, namely, handbags, rucksacks, portable power tools and trolley cases. The advantage of this method is that there is no need for consistency judgement in determining packages with a wide range of types and uncertain contents, thus simplifying the calculation. Meanwhile, the reasonableness and reliability of the method is verified by combining it with an actual metro station fire risk assessment system.
Assessment of water resources carrying capacity (WRCC) is of great significance for understanding the status of regional water resources, promoting the coordinated development of water resources with environmental, social and economic development, and promoting sustainable development. This study focuses on the Longdong Loess Plateau region and utilized panel data spanning from 2010 to 2020, established a three-dimensional evaluation index system encompassing water resources, economic, and ecological dimensions, uses the entropy-weighted TOPSIS model coupled with global spatial autocorrelation analysis (Global Moran’s I) and the hot spot analysis (Getis-Ord Gi* index) method to comprehensively evaluate the spatial distribution of the WRCC in the study region. It can provide scientific basis and theoretical support for decision-making on sustainable development strategies in the Longdong Loess Plateau region and other regions of the world.From 2010 to 2020, the overall WRCC of the Longdong Loess Plateau area show some fluctuations but maintained overall growth. The WRCC in each county and district predominantly fell within level III (normal) and level IV (good). The spatial distribution of the WRCC in each county and district is featured by clustering pattern, with neighboring counties displaying similar values, resulting in a spatial distribution pattern characterized by high carrying capacity in the south and low carrying capacity in the north. Based on these findings, our study puts forth several recommendations for enhancing the WRCC in the Longdong Loess Plateau area.
Eco-friendly digital marketing strategies are crucial for Jordanian companies that want to meet environmental standards. This covers eco-friendly pricing, goods, and online cooperation. In contrast, customer concern and action are not connected, requiring true green marketing tactics. Jordan’s “Go Green” programme and the EU-EBRD’s Green Financing Facility show that sustainability boosts digital marketing. Eco-friendly branding goes beyond sustainable goods and strategic collaborations to support green causes. Consumer awareness is rising globally, especially in Asia-Pacific. Eco-friendly methods are being used to improve sustainability, employee wellbeing, and operational effectiveness. Email, social media, content, influencers, and SEO are effective digital marketing methods that increase customer involvement and reduce environmental impact. The environmental efforts of Patagonia, IKEA, Tesla, and Google are notable in Jordan. Jordanian economic modernization relies on sectoral strategies that integrate sustainability and diversity. The government is making headway in green projects, notably in energy, to meet Agenda 2030 and the Sustainable Development Goals. Environmentally responsible firms use content development, social media, and influencer marketing to create real stories and engage communities. Content marketing requires understanding the target audience, creating instructional resources, and effective distribution. Influencer marketing boosts brand awareness and engagement. Jordan suffers from resource limitations and the need for ongoing education, yet urbanisation and cultural growth are promising. Investments and government projects in green initiatives are enabling this change. Jordanians are increasingly buying eco-friendly items, which affects brand loyalty. Eco-friendly branding boosts customer views and brand awareness in Jordan, emphasising the significance of environmental responsibility in business.
This research delves into the urgent requirement for innovative agricultural methodologies amid growing concerns over sustainable development and food security. By employing machine learning strategies, particularly focusing on non-parametric learning algorithms, we explore the assessment of soil suitability for agricultural use under conditions of drought stress. Through the detailed examination of varied datasets, which include parameters like soil toxicity, terrain characteristics, and quality scores, our study offers new insights into the complexities of predicting soil suitability for crops. Our findings underline the effectiveness of various machine learning models, with the decision tree approach standing out for its accuracy, despite the need for comprehensive data gathering. Moreover, the research emphasizes the promise of merging machine learning techniques with conventional practices in soil science, paving the way for novel contributions to agricultural studies and practical implementations.
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