BACKGROUND: Ancient classic prescription play a crucial role in the preservation and advancement of traditional Chinese medicine (TCM) theories. They represent a significant milestone in the ongoing development and transmission of TCM knowledge and practices and are considered one of the breakthroughs in the development of TCM inheritance. In the process of developing ancient classic prescriptions, many problems may still arise in ensuring quality consistency between traditional methods and modern production processes, among which the extraction process poses major challenges. This paper introduces a practical approach extracting an ancient classic prescription using a modern extraction process. The technique is demonstrated through the study of the extraction process of Shenshou Taiyi powder (STP).
METHODS: This study focuses on optimising the STP extraction process to ensure consistency in the quality of the product obtained through ancient and modern processes using the standard relation and fuzzy analytic hierarchical process (FAHP) and criteria importance through intercriteria correlation (CRITIC) method integrated weights combined with the Box-Behnken response surface test. Using the contents of rosmarinic acid, isoimperatorin, puerarin, as well as the extract yield and fingerprint similarity as evaluation indexes of STP, the Box-Behnken response surface method was employed to examine the varying extraction parameters, including water addition ratio, extraction duration, and number of extractions. The weighted coefficients for each parameter were calculated by combining the benchmark correlation and FAHP-CRITIC method, deriving a comprehensive score.
RESULTS: The optimal extraction process for STP consisted of a two extractions, each using at a tenfold quantity of water, performed for one hour. Process verification across three separate batches yielded a comprehensive score of 94.7, with a relative standard deviation of 0.76%.
CONCLUSIONS: The application of the Box-Behnken response surface method combined with standard relation and FAHP-CRITIC approach proved to be stable and feasible for optimising the extraction process of STP.

Bioenergy generation from microalgae can significantly contribute to climate mitigation and renewable energy production. In this regard, several multi-criteria decision-making method were employed to prioritize appropriate microalgae culture system for bioenergy production. Entropy weight, Criteria Importance Through Intercriteria Correlation (CRITIC) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) were the employed MCDA method. Fourteen microalgae culture systems were selected as a case study, which contain teen monoculture and four dual-culture. Initially, through ans in-depth review of the literature and expert views, four categories total eight indicators were selected as the evaluation indices of the study, namely 1) Proliferation: Half growth cycle and Max growth rate,2) Biomass output: Bio-crude yield and Lipid yield, 3) Nutrient utilization: residual concentration of total Nitrogen and total Phosphorus, and, 4) Stability: coefficient of variation of Bio-crude yield and Lipid yield. The result indicated that \"Pediastrum sp. & Micractinium sp.\" was identified as the most bioenergy potential microalgae culture system, and the evaluation results of entropy weight method and CRITIC method are similar. It is pertinent to note that 1)the entropy weight method exhibits lower sample size requirements, 2) the critic method excels when dealing with larger sample sizes, and 3) the TOPSIS method necessitates the incorporation of appropriate weighting methods to ensure credible results. In the application stage, the key indicators related to cost can be further included in the evaluation indices.

UNASSIGNED: Through data collection and analysis, the method of evaluating the operation quality of large medical equipment in children\'s hospital is explored and suggestions on the use and configuration of large medical equipment is put forward.
UNASSIGNED: Collect the equipment operation data through the Internet of Things, and combine the hospital HIS, RIS, HRP and other information system data to establish the operation evaluation system of large medical equipment of children\'s hospital. CRITIC method is used to quantitatively evaluate single type of equipment and single equipment.
UNASSIGNED: Hospital big data platform realizes the longitudinal analysis of the operation data of a single large equipment and forms a visual chart, which is displayed on the PC and mobile terminals. Municipal platform can conduct horizontal analysis on the equipment operation data to realize the comprehensive quantitative evaluation of the operation level of large equipment of children\'s hospital and put forward suggestions for use and configuration.
UNASSIGNED: A large equipment operation evaluation system for children\'s hospital is established through data collection and analysis, and the fine management level of large medical equipment is improved.
UNASSIGNED: 探索通过数据采集及分析评价儿童专科医院大型医疗设备运行水平的方法，提出大型医疗设备使用及配置建议。.
UNASSIGNED: 通过物联网终端采集设备运行数据，结合医院HIS、RIS、HRP等系统数据，建立儿童专科医院大型医疗设备评价指标体系，运用CRITIC法对单类、单台设备数据进行量化评价。.
UNASSIGNED: 医院大数据平台实现了对单台大型设备运行数据纵向分析并形成可视化图表，通过PC端及移动端展示。申康市级平台数据分析，实现对儿童专科医院大型设备运行水平的综合量化评价及使用配置建议。.
UNASSIGNED: 通过数据采集及分析，实现儿童专科医院大型设备运行评价体系建设，提升大型设备管理水平。.

As one of the three major urban agglomerations in China, the Beijing-Tianjin-Hebei Region has strong economic strength but its ecological fragility is very prominent. To pursue the comprehensive development of economy and ecology, it is very important to analyze the ecological environment in the Beijing-Tianjin-Hebei Region. Here, the Beijing-Tianjin-Hebei Region was selected as the research area, and 19 indicators were selected to construct an evolution system based on the PSRM model. The temporal and spatial evolution characteristics of ecological vulnerability in the Beijing-Tianjin-Hebei Region were explored by combining the order relation method, CRITIC method, Theil index, and hot spot analysis, and the influencing factors were calculated via geographic detector. The results showed that:① the ecological vulnerability first increased and then decreased in the Beijing-Tianjin-Hebei Region. The vulnerable areas showed a northeast-southwest trend, and the ecological environment in the northeast and southwest regions was better than that in the central and southern regions. The area of slight vulnerability in 2014 increased by 6803.01 km2 compared with that in 2009. The area of mild vulnerability decreased by 130.41 km2, and the area of moderate vulnerability decreased by 26537.31 km2 compared with that in 2009. The areas of severe and extremely vulnerable status increased by 19512.9 km2 and 351.81 km2, respectively, compared with those in 2009. The habitat situation in the Beijing-Tianjin-Hebei Region improved significantly from 2014 to 2019. Compared with that in 2014, the areas of mild, moderate, severe, and extremely vulnerable decreased by 2248.29 km2, 2220.21 km2, 7988.67 km2, and 55.98 km2, respectively. The light area increased by 12513.15 km2 compared with that in 2014. ② According to the calculation results of the Theil index, the spatial correlation degree of ecological vulnerability in the Beijing-Tianjin-Hebei Region exhibited a V-shaped fluctuation, and the spatial pattern of the cold and hot areas was predominantly consistent with that of the vulnerability. ③ Biological abundance, PM10, and the human disturbance index had a significant influence on the spatial differentiation of ecological vulnerability in the Beijing-Tianjin-Hebei Region. Based on the results of ecological vulnerability analysis, some suggestions on the ecological environment and sustainable development in the Beijing-Tianjin-Hebei Region were proposed.

Global forest area has declined over the past few years, forest quality has declined, and ecological and environmental events have increased with climate change and human activity. In the context of ecological civilization, forest health issues have received unprecedented attention. By improving forest health, forests can better perform their ecosystem service functions and promote green development. This study was carried out in the WuZhi Shan area of Hainan Tropical Rainforest National Park. We employed a decision tree algorithm, a machine learning technique, for our modeling due to its high accuracy and interpretability. The objective weighted method using criteria of importance through intercriteria correlation (CRITIC) was used to determine forest health classes based on survey and experimental data from 132 forest samples. The results showed that species diversity is the most important metric to measure forest health. An interpretable decision tree machine learning model was proposed to incorporate forest health indicators, providing up to 90% accuracy in the classification of forest health conditions. The model demonstrated a high degree of effectiveness, achieving an average precision of 90%, a recall of 67%, and an F1 score of 70.2% in predicting forest health. The interpretable decision tree classification results showed that breast height diameter is the most important variable in classifying the health status of both primary and secondary forests. This study highlights the importance of using interpretable machine learning methods for the decision-making process. Our work contributes to the scientific underpinnings of sustainable forest development and effective conservation planning.

Vegetation makes an outstanding contribution to the stability of ecosystems and to a certain extent reflects the state of the terrestrial ecosystem. Drought conditions greatly affect the growth and development process of vegetation due to its remarkable stochasticity and complexity. Due to the complex coupling mechanism between vegetation and drought, the research on vegetation drought risk is still limited. In this work, we focus on Northwest China and use the improved vegetation health index (VHI) and other multi-source data. We selected indicator factors based on both hazard and vulnerability, and adopt three weight determination methods, namely entropy method, critic method, and coefficient of variation method, to construct the corresponding index model, and also to establish a vegetation drought risk assessment model to quantitatively evaluate the drought risk of vegetation in northwest China. Results show that the percentage of each drought category remarkably changed during the period encompassing 1981-2020, and the vegetation drought shows deterioration in more areas of northwest China. The vegetation drought risks derived from the three weight determination methods were generally consistent, but differed for a particular vegetation type. The overall spatial distribution pattern of vegetation drought risk in Northwest China is higher in the west and lower in the east, and the vegetation in southern Qinghai and northwestern Xinjiang presents higher drought risk. This study may be used as a tool to provide quantitative basis for vegetation protection and vegetation drought management.

The development of biodegradable polymers for both industrial and commercial uses is crucial nowadays due to the detrimental environmental effects of synthetic plastics. For a variety of uses, researchers have created numerous starch-based composites. The current study examines bioplastics made from maize and rice starch for packaging purposes. Several types of bioplastic samples are created using various ratios of gelatin, glycerol, citric acid, maize starch, and rice starch. People have discovered the value of plastics all around the world. It can be used for packaging, trash bags, liquid containers, throwaway quick service restaurant products, and other things. Regarding the negative aspect of plastics, their dumping after durability poses a serious risk to both people and wildlife. This prompted researchers to seek alternative natural resources that may be used to create flexible polymers that are recyclable, eco-friendly, and sustainable. It has been discovered that tuber and grain starches can be used to produce flexible biopolymers. The decision to choose the best among these choices is an MCDM problem because the carbohydrates from these suppliers have varying qualities. The Probabilistic Hesitant Fuzzy Set (PHFS)-based COmplex PRoportional ASsessment (COPRAS) method for solving uncertainty problems is utilized in this research study. To get the objective weights of the criteria in this case, we used the Critic method of weight determination. An example case of selecting the optimal hydrolyzes for biodegradable dynamic plastic synthesis was chosen to represent the applicability of the suggested approach. The findings demonstrate the feasibility of thermoplastic starches derived from rice and corn for packaging applications.

To determine the security status of urban water supplies, a comprehensive evaluation model of urban water supply security based on the VIKOR and TOPSIS models is proposed. The comprehensive evaluation value K is obtained as the evaluation result, and the larger K is, the higher the safety of the urban water supply. The results show that the security of the water supply in Tianjin increased from 0.2300 in 2015 to 0.8026 in 2018. Although it slightly decreased to 0.5439 in 2019, it was still at a high level and increased to 0.7508 in 2020. The urban water transmission and distribution status, the service level of the water supply industry, and the status of sewage treatment play positive roles in affecting the safety of the water supply in Tianjin, and the status of urban water sources and the urban water use status are the main factors that reduced the safety of the urban water supply. According to the results of an obstacle degree model and the actual conditions in the study area, it is suggested that Tianjin should continue to focus on the development of water resources and the utilization of unconventional water sources and actively promote the construction of a water-saving society.

At the early stage of a major public health emergency outbreak, there exists an imbalance between supply and demand in the distribution of emergency supplies. To improve the efficiency of emergency medical service equipment and relieve the treatment pressure of each medical treatment point, one of the most important factors is the emergency medical equipment logistics distribution. Based on the actual data of medical equipment demand during the epidemic and the characteristics of emergencies, this study proposed an evaluation index system for emergency medical equipment demand point urgency, based on the number of patients, the number of available inpatient beds, and other influencing factors as the index. An urban emergency medical equipment distribution model considering the urgency of demand, the distribution time window, and vehicle load was constructed with the constraints. Wuhan, Hubei Province, China, at the beginning of the outbreak was selected as a validation example, and the Criteria Importance Though Intercriteria Correlation (CRITIC) method and the genetic algorithm were used to simulate and validate the model with and without considering the demand urgency. The results show that under the public health emergencies, the distribution path designed to respond to different levels of urgency demand for medical equipment is the most efficient path and reduces the total distribution cost by 5%.

With the frequent occurrence of various emergency events, emergency decision making (EDM) has become an important research focus recently and many studies have been conducted to decrease the negative impact of emergencies. Normally, it is essential for decision makers to make satisfactory and reasonable emergency decisions in the shortest possible time as inappropriate decisions may result in enormous economic losses and serious social consequences. To ensure that an emergency response can be made efficiently, we propose a new EDM method by integrating regret theory and evaluation based on distance from average solution (EDAS) method within the 2-tuple spherical linguistic environment. First, the 2-tuple spherical linguistic term sets (TSLTSs) are employed by decision makers to express their uncertain and vague evaluation information on emergency alternatives. Then, an integrated EDM method based on regret theory and EDAS method is proposed to rank emergency alternatives and find out the optimal one. Besides, the criteria importance through inter-criteria correlation (CRITIC) method is used to determine criteria weights objectively in the EDM process. Finally, the proposed regret theory-EDAS method is applied to select the optimal response solution for a public health emergency in China. The superiority and practicality of the designed method are further justified through a comparative analysis with other EDM methods.