Scientific Assessment Research Articles

The effect of Qi‐Shao‐Tong‐Mai‐An‐Shen herbal paste on coronary heart disease patients with depression and/or anxiety: Study protocol for a randomized controlled trial

AbstractCoronary heart disease (CHD) poses a significant threat to human life and well‐being. The presence of psycho‐cardiology diseases not only exacerbates the progression of CHD but also imposes a substantial financial burden. Consequently, there is a pressing need to prioritize the prevention and management of psycho‐cardiology conditions. Given the complex adverse effects associated with antidepressants, it is imperative to investigate alternative, safer, and more efficacious early interventions for psycho‐cardiology diseases. The trial will randomly divide 99 patients who meet the inclusion criteria into two groups in a ratio of 1:2. Both groups will be administered standard western medicine treatment for CHD. The Qi‐Shao‐Tong‐Mai‐An‐Shen (QSTMAS) group will be treated with an additional 30 mL QSTMAS herbal paste orally twice daily for up to 12 weeks. The primary endpoints are the changes of Generalized Anxiety Disorder‐7 and Patient Health Questionnaire‐9 scores after the intervention for 12 weeks. The secondary endpoints include the scores of Traditional Chinese medicine syndromes, 6‐min walking test, Insomnia severity index sleep scale, laboratory tests, and other examinations of both groups after the intervention for 12 weeks. The QSTMAS herbal paste exhibits potential and promise as a treatment modality for mild‐to‐moderate psychological disorders within the department of cardiology. The implementation of a rigorous trial design will facilitate an objective and scientific assessment of the clinical effectiveness and safety of combining QSTMAS herbal paste with standard western medicine for CHD patients with depression and/or anxiety. Trial Registration: China Clinical Trial Registry, ChiCTR2200065179. Registered 31 October 2022.

Risk assessment of high-speed railway CTC system based on improved game theory and cloud model

PurposeIn order to solve the problem of inaccurate calculation of index weights, subjectivity and uncertainty of index assessment in the risk assessment process, this study aims to propose a scientific and reasonable centralized traffic control (CTC) system risk assessment method.Design/methodology/approachFirst, system-theoretic process analysis (STPA) is used to conduct risk analysis on the CTC system and constructs risk assessment indexes based on this analysis. Then, to enhance the accuracy of weight calculation, the fuzzy analytical hierarchy process (FAHP), fuzzy decision-making trial and evaluation laboratory (FDEMATEL) and entropy weight method are employed to calculate the subjective weight, relative weight and objective weight of each index. These three types of weights are combined using game theory to obtain the combined weight for each index. To reduce subjectivity and uncertainty in the assessment process, the backward cloud generator method is utilized to obtain the numerical character (NC) of the cloud model for each index. The NCs of the indexes are then weighted to derive the comprehensive cloud for risk assessment of the CTC system. This cloud model is used to obtain the CTC system's comprehensive risk assessment. The model's similarity measurement method gauges the likeness between the comprehensive risk assessment cloud and the risk standard cloud. Finally, this process yields the risk assessment results for the CTC system.FindingsThe cloud model can handle the subjectivity and fuzziness in the risk assessment process well. The cloud model-based risk assessment method was applied to the CTC system risk assessment of a railway group and achieved good results.Originality/valueThis study provides a cloud model-based method for risk assessment of CTC systems, which accurately calculates the weight of risk indexes and uses cloud models to reduce uncertainty and subjectivity in the assessment, achieving effective risk assessment of CTC systems. It can provide a reference and theoretical basis for risk management of the CTC system.

Genie: the first open-source ISO/IEC encoder for genomic data

For the last two decades, the amount of genomic data produced by scientific and medical applications has been growing at a rapid pace. To enable software solutions that analyze, process, and transmit these data in an efficient and interoperable way, ISO and IEC released the first version of the compression standard MPEG-G in 2019. However, non-proprietary implementations of the standard are not openly available so far, limiting fair scientific assessment of the standard and, therefore, hindering its broad adoption. In this paper, we present Genie, to the best of our knowledge the first open-source encoder that compresses genomic data according to the MPEG-G standard. We demonstrate that Genie reaches state-of-the-art compression ratios while offering interoperability with any other standard-compliant decoder independent from its manufacturer. Finally, the ISO/IEC ecosystem ensures the long-term sustainability and decodability of the compressed data through the ISO/IEC-supported reference decoder.

Study on the Spatiotemporal Evolution and Driving Factors of Ecological Security in Stages Based on the DPSIRM-SBM Model: A Case Study of the Yangtze River Economic Belt.

Scientific assessment of urban ecological security (ES) is an important prerequisite to realize regional sustainable development. Previous studies lack the consideration of quality and poor systematic correlation, which could not reflect the internal dynamic relationship. On the basis of considering the time lag, this study divided the research process into the natural operation stage and the management feedback stage based on the driving forces, pressures, state, impacts, responses, management (DPSIRM) framework model and DEA theory, so as to effectively overcome the above shortcomings. Finally, we analyzed the spatio-temporal characteristics and influencing factors of the ES level of 108 cities in the Yangtze River Economic Belt (YREB) during 2005-2019. The results showed that: (a) both two stages showed a slow and fluctuating upward trend in time series, and the level of urban ES in the management feedback stage was significantly higher than that in the natural operation stage; (b) with the passage of time, the spatial distribution of ES in the natural operation stage gradually developed towards the middle and downstream of the YREB, while the management feedback stage mainly evolved from the midstream to the edge area; (c) the level of urban ES presented a different degree of spatial agglomeration phenomenon, and showed an increasing trend over time; and (d) the key influencing factors gradually changed from pressure to response during 2005-2019. This research aims to provide an innovative perspective for the measurement of urban ES, and provide scientific reference for improving urban ecological sustainable development.

Thank You to Our 2023 Reviewers

AbstractOn behalf of the journal, AGU, and the scientific community, we, the editors of Earth's Future, are delighted to publish the names of the 817 peer reviewers who provided 1,242 reviews for our journal in 2023 (italicized names have contributed three or more reviews). Your diligent efforts to provide timely comments on our submissions have significantly improved the manuscripts and elevated the scientific rigor of future research. As a unique transdisciplinary journal, Earth's Future delves into the state of the planet and its inhabitants, sustainable and resilient societies, the science of the Anthropocene, and predictions of our shared future through research articles, reviews, and commentaries. In the face of observed and anticipated global environmental and climatic changes, the need for high‐quality scientific theories, assessments, and projections about the future of our planet has never been more pressing. To safeguard research integrity in this crucial area, we rely on our reviewers' expertise and selfless cooperation. We extend our heartfelt thanks to each of the individuals listed below for their contributions to our journal and the broader scientific discourse. Your dedication is immensely appreciated.

Landscape ecological risk evaluation and prediction under a wetland conservation scenario in the Sanjiang Plain based on land use/cover change

Landscape ecological risk is the term used to describe potential negative effects of the relationship between environmental processes and landscape structure as a result of both natural and human interactions. The scientific assessment of past and prediction future ecological risks to landscapes is the basis for achieving sustainable regional development. In this study, we built an ecological risk measurement system characterized by variability in landscape composition to reflect the components of landscape ecological risk. In particular, the CA-Markov model was used to simulate the spatial pattern of land use in the Sanjiang Plain, China, under a wetland protection scenario. The evolution of the spatiotemporal land use trend in the study area was then analyzed for past (2011–2021) and future (2021–2036) periods. The results identified that construction land, farmland, water, and grassland areas exhibited an increasing trend from 2011 to 2021, while forest and wetland areas decreased each year. From 2021 to 2036, the grassland areas exhibited a downward trend, while the other land use types maintained the same previous trend, and all land use types experienced a slowdown in the degree of change. The major landscape ecological risk levels in the research region changed from medium-risk and low-risk levels (2011–2021) to low-risk and lower-risk levels (2021–2036). An evident decrease in risk is observed for farmland and construction land in the mid-region of the research district and forests in the south. In contrast, high-risk and higher-risk levels regions were smaller and distributed in the Songhua River basin in the northeast of the research region, wetland nature reserves, and the Xingkai Lake area, with an overall reduction of 59%. Based on the results, we propose several risk prevention and control management strategies. This research acts as a basis for determining Sanjiang Plain's future rational distribution of land resources and provides an example for the reduction of ecological risks in similar regions.

THE IMPACT OF THE SHADOW ECONOMY ON THE REDUCTION OF TAX REVENUES TO THE STATE BUDGET

The aim of the study was to assess and analyse the shadowing of the national economy, as well as to determine the impact of its shadowing on the reduction of tax revenues to the state budget. The research employed general scientific, economic, and mathematical assessment methods, such as regression analysis, correlation analysis, interval forecasts, as well as econometric models of Lacko's household electricity approach, as well as modelling of the shadowing level using the multiple indicators-multiple-causes (MIMIC) model. The calculations and analysis gave grounds to determine the level of the shadow economy of Ukraine based on the state statistics of shadowing trends. There is currently an upward trend estimated to be 37.1% of GDP in 2022 compared with international data, which indicates a rapid growth of the shadow economy from 27% in 2019 to 44% in 2022. An alternative method of assessing the shadowing level was proposed in order to level the peculiarities of calculating the level of shadowing of the economy. According to the calculations, it was 43% in 2022. It was determined that the rapid growth of the shadow economy is an indicator of a reduction in tax revenues, especially in 2022 — by almost 8%. The correlation analysis proved that the increased shadowing level is an indicator of the reduction of tax revenues to the budget of Ukraine. The conducted analysis has certain limitations, therefore it is advisable to further test the hypothesis regarding the indicator of tax revenue reduction on a larger range of data and to apply an alternative method of assessing the shadowing level for developed economies, such as the countries of the European Union (EU).

Robust Intelligent Malware Detection Using Deep Learning

Abstract: In the modern era of technology, malicious software, or malware, holds a serious security hazard as computer users, businesses, and governments see an uptick in malware attacks. In attempts to identify unknown malware, current malware detection solutions use dynamic as well as static examination of malware signatures and behavior patterns, which takes time and is unsuccessful. Modern malware employs evasive strategies such as metamorphosis and polymorphism to rapidly alter its actions and produce a multitude of variants. Machine learning algorithms (MLAs) are being used more and more to do an efficient malware analysis because new malware is primarily versions of current malware. Extensive feature engineering, feature learning, and feature representation are needed for this. It is likely to fully eliminate the feature engineering stage by utilizing sophisticated MLAs like deep learning. Even though there have been a few fresh investigations in the field, the algorithms' performance is skewed by the training set. It is a prerequisite to reduce bias and figure out these techniques holistically in order to develop new, improved techniques for successful zero-day malware detection. This paper fills a vacuum in the literature by comparing and contrasting deep learning architectures with standard MLAs for malware detection, classification, and categorization using public and private datasets. The public and private dataset’s train and test splits, which were gathered during distinctly different periods, are not connected to one another in the experimental study. Furthermore, we provide a new method of image processing with ideal parameters for deep learning architectures and MLAs. In response to a thorough scientific assessment of these methodologies, deep learning architectures perform more efficiently than traditional MLAs. All in all, our work suggests a scalable and multimodal deep learning system for real-time malware detection through visual means. An improved technique for successful zero-day malware detection is the visualization and deep learning architectures for static, dynamic, and image processing based blended methods in a big data environment.

Using Scaffolding to Improve Grade 10 Students’ Argumentation Skills on Green Chemistry

This study aimed to assess the impact of scaffolding instruction on the argumentation skills of 10th-grade students regarding green chemistry. Conducted in May 2023 at a public high school in Jakarta, Indonesia, the study employed a quasi-experimental design involving 72 students from two intact classes. These classes were divided into experimental and control groups. Students in the experimental group were instructed using scaffold learning with the MHC-C operator, while those in the control group followed conventional methods. The evaluation utilized scientific concept and argumentation assessments to gauge students’ argumentation skills and the quality of their arguments. Independent and paired t-tests were employed to analyze differences and improvements in posttest scores between the two groups. The results of the t-test [t = 2.06; p = 0.043] revealed a disparity in posttest scores, with the experimental group demonstrating higher scores. Consequently, the data analysis suggests that the implementation of scaffolding instruction is more effective than conventional learning in enhancing students’ argumentation skills regarding green chemistry. 

Estimation of Mariculture Carbon Sinks in China and Its Influencing Factors

The scientific assessment of mariculture carbon sinks is crucial to recognize its potential as a significant component of marine blue carbon in global climate change mitigation. Therefore, the objective of the research was to estimate the seaweed and shellfish mariculture carbon sink of different varieties in various sea areas. The paper emphasized the distinction between short-term carbon sequestration in seaweed and shellfish that can be removed and long-term carbon sequestration that is deposited. Methodologically, the evaluation was based on the carbon sequestration mechanism and systematic pathways in shellfish and seaweeds. Additionally, the carbon sequestration of shellfish and seaweed aquaculture over the last decade was evaluated by the carbon sink assessment model, and the reasons for the differences in the carbon sink capacity of mariculture in China’s coastal provinces were discussed by using the LMDI decomposition model. The results indicated the carbon sequestration of offshore seaweeds and shellfish mariculture in China was huge. From 2010 to 2020, offshore seaweed aquaculture in China amounted to 7.959 Mt C/a, while shellfish aquaculture contributed 33.542 Mt C/a to the carbon sinks. Sedimentary carbon sequestration by shellfish accounted for 51% of the total carbon sequestration in mariculture involving shellfish and seaweeds. Especially noteworthy is the sedimentary carbon sequestration by shellfish, which is an indispensable and crucial component of mariculture carbon sequestration estimation. It is concluded that improvements in farming efficiency exerted the greatest influence on the variations of the mariculture carbon sink, while adjustments in farming structure had a relatively minor impact in the case of little change in aquaculture yield. Enhancing farming efficiency emerges as a practical approach to bolstering the carbon sink potential of marine aquaculture fisheries in the future.

Anticipating Job Market Demands—A Deep Learning Approach to Determining the Future Readiness of Professional Skills

Anticipating the demand for professional job market skills needs to consider trends such as automation, offshoring, and the emerging Gig economy, as they significantly impact the future readiness of skills. This article draws on the scientific literature, expert assessments, and deep learning to estimate two indicators of high relevance for a skill’s future readiness: its automatability and offshorability. Based on gold standard data, we evaluate the performance of Support Vector Machines (SVMs), Transformers, Large Language Models (LLMs), and a deep learning ensemble classifier for propagating expert and literature assessments on these indicators of yet unseen skills. The presented approach uses short bipartite skill labels that contain a skill topic (e.g., “Java”) and a corresponding verb (e.g., “programming”) to describe the skill. Classifiers thus need to base their judgments solely on these two input terms. Comprehensive experiments on skewed and balanced datasets show that, in this low-token setting, classifiers benefit from pre-training and fine-tuning and that increased classifier complexity does not yield further improvements.

Life Cycle Assessment and Model Optimization for Sustainable Energy Cross-Border E-Commerce

INTRODUCTION: In an in-depth study of the application of sustainable energy in cross-border e-commerce, a comprehensive assessment and model optimization of its life cycle are conducted to promote the practical application of sustainable development in e-commerce. With the increasing global concern for renewable energy and environmental protection, e-commerce, as an international business model, has attracted much attention in terms of the environmental and social impacts of its sustainability.OBJECTIVES: The aim is to provide scientific assessment methods and effective model optimization strategies to promote the feasibility and sustainability of cross-border e-commerce for sustainable energy.METHODS: A comprehensive life cycle assessment (LCA) model was constructed using the system life cycle assessment (SLCA) methodology by collecting data from various aspects of sustainable energy cross-border e-commerce. The model considers the entire life cycle process from energy production, logistics, transportation, and product manufacturing to final consumption and integrates various factors such as resource utilization, environmental emissions, and social responsibility. Based on the assessment, a series of model optimization strategies are proposed, including suggestions for improving supply chain efficiency, promoting green energy applications, and strengthening social responsibility.RESULTS: This study achieved significant life cycle assessment and model optimization results. In terms of energy use, promoting the application of renewable energy significantly reduces carbon emissions; in terms of supply chain management, optimization leads to an overall efficiency improvement and a reduction in resource wastage; and in terms of social responsibility, the enterprise strengthens employee training and community involvement, which enhances its social image. These results show that sustainable energy cross-border e-commerce can better achieve sustainable development goals through systematic assessment and optimization.CONCLUSION: Life cycle assessment and model optimization provide scientific assessment methods and practical suggestions for sustainable energy cross-border e-commerce. In global sustainable development, the e-commerce industry should actively adopt sustainable energy and minimize its negative impacts on the environment and society by optimizing production and supply chain management. Future research can continue to expand the assessment model and deeply explore the potential of sustainable energy in e-commerce to provide more precise guidance for the industry's sustainable development.

Flood risk identification in high-density urban areas of Macau based on disaster scenario simulation

Currently, most of the world's economically developed and densely populated cities are built along coasts, and populations and industries tend to concentrate in coastal areas. However, with climate change, extreme weather events frequently occur in coastal areas. High-density urban spaces have changed the natural hydrological cycle, and the dense spatial layout, low-load municipal system planning, and inefficient management system of coastal cities have led to an increasing threat of flooding in these high-density urban areas, affecting their safety and sustainable development. In this context, the scientific and reasonable risk assessment of future flooding in coastal high-density urban areas has become an urgent problem and a key focus of urban disaster prevention and control efforts. In this paper, a flood identification tool is developed, a technical route for flood risk identification is established, identification scenarios under several disaster conditions are set, and classification criteria for flood risk identification are determined. An empirical study of high-density urban areas in Macau is carried out, the Infoworks Icm hydrological simulation software (Manufacturer: HR Wallingford (Shanghai) Co.,Ltd) is used to establish a flood hazard risk identification model for the Macau Peninsula, and flood hazard risk zones for the high-density urban areas in Macau are identified and delineated based on the simulation results.

Wildlife ecotoxicology of plant protection products: knowns and unknowns about the impacts of currently used pesticides on terrestrial vertebrate biodiversity.

Agricultural practices are a major cause of the current loss of biodiversity. Among postwar agricultural intensification practices, the use of plant protection products (PPPs) might be one of the prominent drivers of the loss of wildlife diversity in agroecosystems. A collective scientific assessment was performed upon the request of the French Ministries responsible for the Environment, for Agriculture and for Research to review the impacts of PPPs on biodiversity and ecosystem services based on the scientific literature. While the effects of legacy banned PPPs on ecosystems and the underlying mechanisms are well documented, the impacts of current use pesticides (CUPs) on biodiversity have rarely been reviewed. Here, we provide an overview of the available knowledge related to the impacts of PPPs, including biopesticides, on terrestrial vertebrates (i.e. herptiles, birds including raptors, bats and small and large mammals). We focused essentially on CUPs and on endpoints at the subindividual, individual, population and community levels, which ultimately linked with effects on biodiversity. We address both direct toxic effects and indirect effects related to ecological processes and review the existing knowledge about wildlife exposure to PPPs. The effects of PPPs on ecological functions and ecosystem services are discussed, as are the aggravating or mitigating factors. Finally, a synthesis of knowns and unknowns is provided, and we identify priorities to fill gaps in knowledge and perspectives for research and wildlife conservation.

Common questions and misconceptions about protein supplementation: what does the scientific evidence really show?

Protein supplementation often refers to increasing the intake of this particular macronutrient through dietary supplements in the form of powders, ready-to-drink shakes, and bars. The primary purpose of protein supplementation is to augment dietary protein intake, aiding individuals in meeting their protein requirements, especially when it may be challenging to do so through regular food (i.e. chicken, beef, fish, pork, etc.) sources alone. A large body of evidence shows that protein has an important role in exercising and sedentary individuals. A PubMed search of "protein and exercise performance" reveals thousands of publications. Despite the considerable volume of evidence, it is somewhat surprising that several persistent questions and misconceptions about protein exist. The following are addressed: 1) Is protein harmful to your kidneys? 2) Does consuming "excess" protein increase fat mass? 3) Can dietary protein have a harmful effect on bone health? 4) Can vegans and vegetarians consume enough protein to support training adaptations? 5) Is cheese or peanut butter a good protein source? 6) Does consuming meat (i.e., animal protein) cause unfavorable health outcomes? 7) Do you need protein if you are not physically active? 8) Do you need to consume protein ≤ 1 hour following resistance training sessions to create an anabolic environment in skeletal muscle? 9) Do endurance athletes need additional protein? 10) Does one need protein supplements to meet the daily requirements of exercise-trained individuals? 11) Is there a limit to how much protein one can consume in a single meal? To address these questions, we have conducted a thorough scientific assessment of the literature concerning protein supplementation.

Research on Establishment and Application of Evaluation System of Urban Energy Strategy Development Indicators under the Perspective of Carbon Neutrality

A scientific, comprehensive and integrated assessment of urban energy development is of great significance for the establishment of a clean, low-carbon and efficient urban modern energy system. From the perspective of carbon neutrality, this paper sets 25 evaluation indicators in seven dimensions: energy supply, energy consumption, energy efficiency improvement, clean and low-carbon, safety and reliability, low-carbon transport, and scientific and technological innovation, and constructs a secondary indicator system for evaluating the strategic development of urban energy. The system adopts the hierarchical analysis method to determine the weights of the indicators, the double-baseline progression method to standardize the indicator scores, and finally the weighted composite index method to calculate the level of urban energy strategy development. This paper applies the index system to evaluate the current energy development status of Wenzhou city in 2020 and 2022, and to predict the energy strategy development in 2025 and 2030. The scores of Wenzhou city's urban energy strategy development level in the corresponding four periods are 63.56, 70.59, 77.87 and 85.06, indicating that by 2023, Wenzhou city's urban energy development level will go from medium development to high development. Wenzhou City should accelerate the proportion of renewable energy in the future. It is necessary to complement multiple energy sources and improve the integration of heat, electricity, gas and cold. In terms of end consumption, it is necessary to improve the efficiency of energy use, reduce energy intensity, implement electric energy substitution and form an energy consumption pattern centered on electricity.

Urban Growth and Its Ecological Effects in China

As the largest developing nation, China is currently experiencing rapid urban growth. Conducting a thorough scientific assessment of this expansion and its ecological consequences is of paramount importance for advancing China’s ecological civilization and aligning with the United Nations’ Sustainable Development Goals. This study employs multi-source remote sensing data to investigate the spatiotemporal trends in Chinese urban development and explore its impact on the ecological environment. From 2013 to 2021, the findings indicate an increasing trend in China’s total nocturnal light, with the southern and central regions exhibiting higher growth rates. This suggests a decade-long expansion of Chinese cities, especially in the southern and central regions. However, the impact of urban expansion on ecological quality varies. Beijing, Shenyang, and Xi’an have witnessed improved environmental quality, while Kunming and Shenzhen have experienced minimal changes, and Hefei and Wuhan have encountered a decline. The observed spatial heterogeneity underscores the intricate relationship between urban expansion and ecological shifts. This study reveals the spatiotemporal dynamics of China’s urban expansion and its ecological impact, providing valuable insights and policy recommendations for fostering the harmonized development of urbanization and ecological preservation.

Comparing Indigenous Soil Quality Knowledge Systems and Scientific Soil Assessment in a Traditional Upland Rice-based Agroecosystem in Southern Philippines

Like traditional agroecosystems worldwide, the Sarangani upland agroecosystem in Southern Philippines is presently under threat from myriad pressures such as environmental destruction, bio-cultural erosion, and agricultural modernization. In these marginal areas, farmland degradation is particularly devastating because of its implications for food security and the long-term survival of ethnic communities. Using a mixed-methods approach, this study revealed a significant linkage between farmers’ soil quality knowledge systems (SQKS) and scientific soil fertility assessments despite their holistic and reductionist natures, respectively. Furthermore, both SQKS and scientific soil knowledge ascribed diminishing soil quality in the Sarangani uplands to unregulated resource extraction, natural calamities, hillside cultivation without soil conservation measures and the inherent vulnerabilities of the upland landscape. These results warrant a closer examination of SQKS and their utilization along with technical soil knowledge systems to craft a comprehensive soil management strategy specifically tailored to the conditions in the Sarangani uplands. Finally, while the study underscored close relationships between local soil assessment and scientific assessment paradigms, more comprehensive studies need to be undertaken before their integration into diverse and complex farming systems such as the Sarangani uplands.

Hugh Lacey and values in contemporary science: era of technology and crises

This article provides an understanding of Hugh Lacey's ideas regarding the influence of values in contemporary science. We explore the interaction between scientific activity and values, fostering critical awareness of scientific practice and its impact on society. The aim is to fill gaps in the comprehension of cognitive, social, and ethical values, considering how they have been shaped by technological transformations and sociocultural crises. A comprehensive literature review examines Lacey's key tenets presented in works such as "Values and Scientific Activity 1 and 2" and Oliveira's "From Cognitive Science to Dialectic", as well as articles in scientific databases and communications with the philosopher in 2023. According to him, values and science should be intrinsically linked, provided there is impartiality in scientific assessments. This relationship does not compromise the ongoing pursuit of a robust understanding of the phenomena in the world. The results highlight the relevance of Lacey's perspectives on values in contemporary science, as in contexts such as transgenic research, which raises crucial ethical questions. The applications of such research can have profound impacts, highlighting the importance of ethics.

Resilience Assessment of Historical and Cultural Cities from the Perspective of Urban Complex Adaptive Systems

Due to the increasingly complex global climatic environment and the rapid development of China’s urban construction, China’s historical and cultural cities are experiencing an external impact as well as internal fragility. Representing the capacity of the urban system to address impact and pressure, resilience can effectively guarantee the sustainable development of historical and cultural cities. A scientific and reasonable resilience assessment system can guide the resilience construction of historical and cultural cities in an effort to effectively counter the impact and pressure they face. Therefore, it is necessary to research the resilience of historical and cultural cities. On the basis of the complex adaptive system (CAS), and by applying multiple assessment indicators, this paper established a resilience assessment system for China’s historical and cultural cities, comprising 38 indicators in six dimensions, to analyze the characteristics and the influencing mechanisms of the resilience of the historical and cultural cities and to reveal the inherent logic underlying their complex presentation. Using six historical and cultural cities in east China as an example, the study applied the assessment system to assess and analyze the different resilience levels of the cities. The comprehensive resilience of Changzhou City obtained the highest score at 0.64, indicating a higher degree of resilience; the scores of Yantai City, Huzhou City, and Nantong City were 0.59, 0.54, and 0.50, respectively, representing moderate degrees of resilience; the scores of Zhongshan City and Quzhou City were 0.44 and 0.40, respectively, exhibiting a lower degree of resilience. Moreover, the factors that result in an unbalanced development of urban resilience were explored from the perspectives of economy, system, and culture. The paper contains some significance in guiding the development of the resilience of historical and cultural cities.