Community Resilience Assessment and Identification of Barriers in the Context of Population Aging: A Case Study of Changchun City, China

As a susceptible demographic, elderly individuals are more prone to risks during sudden disasters. With the exacerbation of aging, new challenges arise for urban disaster reduction and prevention. To address this, the key is to establish a community-scale resilience assessment framework based on the aging background and to summarize factors that influence the resilience level of communities. This approach is a crucial step towards seeking urban disaster prevention and reduction from the bottom up, and serves as an important link to enhance the capacity of urban disaster reduction. This paper explores community resilience evaluation indicators under the background of aging, builds a community resilience evaluation index system based on the Pressure–State–Response, uses the entropy weight method to weigh the indicators, and carries out a resilience evaluation of 507 communities in the main urban area of Changchun. The empirical results indicate significant spatial differentiation of community resilience in the main urban area of Changchun. Moreover, the regional development is unbalanced, showing a spatial distribution pattern of weakness in the middle and strength in the periphery. The ring road network highlights the difference between the new and old urban areas. The high contribution indexes of community resilience in the main urban area of Changchun were concentrated on disaster relief materials input, community self-rescue ability, and disaster cognition ability. Finally, strategies to improve community resilience are proposed from the perspectives of stress, state, and response, emphasizing community residents' participation, conducting disaster prevention and reduction training, and improving community response-ability.

Safety Risks of Primary and Secondary Schools in China: A Systematic Analysis Using AHP–EWM Method

Owing to the frequent accidents in primary and secondary schools (PSS) in China in the past decades, a systematic analysis of indicators influencing safety risks in PSS is critical to identifying preventive measures. A two-hierarchy structure of indicators was identified by analyzing various cases, intensive interviews, and related previous literature. A combination of the analytic hierarchy process and the entropy weight method was developed to synthetically assess the primary and secondary risk indicators through a case study of Ma Shan School in China. The results are as follows: (1) the primary risk indicators, namely, natural disasters, public health, facility safety, accidental injury, public security, school bullying, and individual health constitute the evaluation framework of the safety risks in PSS. (2) Public health risks and accidental injury risks are the most critical factors that should be prioritized. In addition to providing academic implications, several managerial implications are proposed for these stakeholders to reduce the safety risks in PSS.

An Evaluation of the Petroleum Investment Environment in African Oil-Producing Countries Based on Combination Weighting and Uncertainty Measure Theory

Recognizing that the evaluation of the overseas petroleum investment environment is affected by many uncertain factors and that there are problems with current evaluation methods, this paper proposes a mathematical evaluation model of an overseas oil resources investment environment, based on a combination of the weighting and uncertainty measure theory. Combining international investment environment theory with the characteristics of the petroleum industry, this paper establishes an evaluation index system for the overseas petroleum investment environment and the linear uncertainty measure function of each index. Using the subjective weight obtained using an analytic hierarchy process together with the objective weight obtained using the entropy weight method, the optimal weight of each evaluation index was obtained using minimum relative information entropy. A multi-index evaluation matrix of the top 12 oil-producing countries in Africa was calculated. Finally, the credible degree recognition criterion was used to judge the order and level of the oil investment environment. This model provides an effective method for the evaluation of the overseas petroleum investment environment. The results show that Nigeria and Angola have the best investment climate, followed by Algeria, Egypt, and Libya. In general, Africa is an important strategic partner of China and is rich in oil resources. Although Africa’s oil industry is fraught with complex challenges and headwinds, challenges also present opportunities.

A Fuzzy Multi-Criteria Method for Sustainable Ferry Operator Selection: A Case Study

This study is motivated by the Zhuhai municipal government, which needs to select a sustainable ferry operator. Previous research has ignored the evaluation and selection of ferry operators. In addition, since ferry operator evaluation involves conflicting qualitative and quantitative criteria, and there may be uncertainty and ambiguity in the evaluation of criteria by experts, a fuzzy multi-criteria decision-making (MCDM) approach is required to address this challenge. To this end, this paper proposes an integrated MCDM framework model to evaluate and select the best ferry operator. First, a ferry operator evaluation index system with 15 sub-criteria is constructed according to literature and expert opinions;then the fuzzy analytic hierarchy process (FAHP) is used to determine the subjective weight of the criteria, and the entropy weight (EW) method is used to calculate the objective weight of the criteria. We use the linear weighting method to obtain the comprehensive weights of the criteria;finally, the fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) method is adapted to determine the best ranking of the alternatives. This paper takes the Wanshan Islands in Zhuhai as a real case study to verify the proposed FAHP-EW-FTOPSIS method. The results show that the proposed method can be effectively applied to the evaluation and selection of ferry operators. Sensitivity analysis of criteria weights demonstrates the effectiveness and robustness of the proposed framework model. Key findings based on the research provide management insights that can benefit relevant stakeholders. This is the first paper to study the evaluation and selection of ferry operators. Hence, the evaluation index system and integrated framework model proposed in this paper can make important contributions to the evaluation of ferry operators.

The Sustainability Evaluation of Masks Based on the Integrated Rank Sum Ratio and Entropy Weight Method

Due to the seriousness of COVID-19, masks are considered to be as a key and effective device to cut off the spread of viruses and are widely used by people, such as doctors and patients. Hundreds of millions of masks used worldwide in daily life will inevitably cause huge pollution and damage to the environment. However, existing research has not yet provided a method to simultaneously evaluate the economic, environmental, and social aspects of sustainable design of masks, which brings great barriers and challenges for designers to make sustainability decisions on masks and consumers’ behavioral decisions on mask purchases. Consequently, on the basis of principles of sustainability evaluation of masks, this work evaluates ten masks of different materials (including two newly designed masks) by using a novel hybrid of rank-sum ratio and entropy weight method. The results indicate that some disposable masks also show better sustainability than reusable masks, and in addition, the integrated rank-sum ratio and entropy weight method can effectively realize the sustainability evaluation of masks. The main contribution is to furnish an effective decision-making reference for sustainability evaluation of masks while greatly reducing the negative impacts of masks on the environment during the epidemic.

A Novel βSA Ensemble Model for Forecasting the Number of Confirmed COVID-19 Cases in the US

In December 2019, Severe Special Infectious Pneumonia (SARS-CoV-2)–the novel coronavirus (COVID-19)– appeared for the first time, breaking out in Wuhan, China, and the epidemic spread quickly to the world in a very short period time. According to WHO data, ten million people have been infected, and more than one million people have died;moreover, the economy has also been severely hit. In an outbreak of an epidemic, people are concerned about the final number of infections. Therefore, effectively predicting the number of confirmed cases in the future can provide a reference for decision-makers to make decisions and avoid the spread of deadly epidemics. In recent years, the α-Sutte indicator method is an excellent predictor in short-term forecasting;however, the α-Sutte indicator uses fixed static weights. In this study, by adding an error-based dynamic weighting method, a novel β-Sutte indicator is proposed. Combined with ARIMA as an ensemble model (βSA), the forecasting of the future COVID-19 daily cumulative number of cases and the number of new cases in the US are evaluated from the experiment. The experimental results show that the forecasting accuracy of βSA proposed in this study is better than other methods in forecasting with metrics MAPE and RMSE. It proves the feasibility of adding error-based dynamic weights in the β-Sutte indicator in the area of forecasting.

Potential coral implementation area for Indonesia Coral Reef Garden in Nusa Dua, Bali

The Indonesia Coral Reef Garden (ICRG) program is announced as a coral reef restoration program which can support the marine tourism sector since the Covid-19 pandemic hit Indonesia, particularly in Bali. A comprehensive survey and preliminary study are necessary to be conducted to decide a suitable point or to avoid a premature choice for the restoration location. Field survey in Nusa Dua, Bali was carried out on November-December 2020 to determine physical and chemical characteristics of seawater which appropriate for coral life. The bathymetry result at Nusa Dua, Bali varied from shallow to middle water depth. Area covered with coral, soft coral, coral and sand, sand, and seaweed on the seabed are found over study area. In the depth close to the seabed, the sea condition of temperature, salinity, pH, turbidity, and DO is 26.04 - 28.48 °C, 33.95 - 34.29 PSU, 7.933 - 7.982, 0.81 - 2.44 FTU, and 4.40 - 4.93 mg/L, respectively. Based on the conformity of water quality, the middle depth region has sufficient condition for coral growth. Simple Addition Weighting method is used for determining potential location. The potential coral implementation is located 3-5 km from Tanjung Benoa and in south of Nusa Dua around 1-3 km from coast.