bluuebunny/crossref_metadata_2025 huggingface dataset:
A Quantitative Model to Measure the Level of Culture and Tourism Integration Based on a Spatial Perspective: A Case Study of Beijing from 2000 to 2022
Authors: Xu Dandan , Li Xiangliang , Yan Shuo , Cui Liying , Liu Xiaokun , Zheng Yaomin
Published: May 2024

The integration of culture and tourism has become an important factor in the development of the cultural tourism industry, and a quantitative measure of the degree of integration is important for understanding and promoting the high-quality development of the global cultural tourism industry. This study aims to put forward a comprehensive analysis model to show the development trend of cultural and tourism integration, measure the degree of cultural and tourism integration, and analyze the factors affecting the regional heterogeneity of cultural and tourism integration. Using the spatial quantification method of entropy, the spatial coupling coordination degree model, and the geographical weighting model, this paper analyzes the effect and influencing factors of cultural and tourism integration in various districts and counties in Beijing. The results show that the cultural tourism resource endowment of Beijing presents an upward trend and a gradual spillover trend, with obvious spillover to the east and north. The effect of district integration in Beijing has gradually weakened from the city center to the outside, but there is still a serious phenomenon of two levels of differentiation. Factors such as the economic development level, tourism output, cultural output, policy support, and consumption level have spatial heterogeneity on the effect of cultural and tourism integration in each district of Beijing, but the degree of influence is small.
Functional-Combination-Based Comprehensive Benefit Evaluation of Energy Storage Projects under Source-Grid-Load Scenarios via Super-Efficiency DEA
Authors: Qu Hong , Ye Ze
Published: May 2024

As an important support for power systems with high penetration of sustainable energy, the energy storage system (ESS) has changed the traditional model of simultaneous implementation of electricity production and consumption. Its installed capacity under the source-grid-load scenario is rising year by year, contributing to sustainable development, but it faces the problems of insufficient utilization and benefits. This study analyzes the functional combination of ESS under source-grid-load scenarios. A comprehensive benefit evaluation method of energy storage projects (ESPs), based on a fuzzy decision-making trial and evaluation laboratory (DEMATEL) and super-efficiency data envelopment analysis (DEA), is proposed. Firstly, the functional requirements of energy storage in source-grid-load scenarios are explored, and the characteristics of various functions are analyzed to form eight functional combination schemes. Secondly, index modeling is carried out from three aspects—the whole life cycle cost, functional combination benefits, and social and environmental benefits—and a comprehensive benefit evaluation index system of ESP is proposed. Then, the intuitionistic trapezoidal fuzzy number (ITFN) is combined with DEMATEL to form an effective analysis method for the input–output relationship of the indices, and the comprehensive evaluation is realized based on the SE-DEA model. Compared with other methods, this model can ensure the objectivity and stability of the evaluation results in ESP evaluation. Finally, the effectiveness of the proposed evaluation method and the rationality of the functional combination are verified under source-grid-load scenarios. The calculation results show that in the application scenario of source-grid-load, after adopting the functional combination scheme formulated in this article, the comprehensive investment benefits of ESPs have been improved. Moreover, the source side effect is at its best, with an efficiency value of 2.209.
An Approach to the Key Soil Physical Properties for Assessing Soil Compaction Due to Livestock Grazing in Mediterranean Mountain Areas
Authors: Blanco-Sepúlveda Rafael , Gómez-Moreno María Luisa , Lima Francisco
Published: May 2024

The selection of key soil physical properties (SPPs) for studying the impact of livestock treading is an unexplored research topic, especially in studies that analyze the influence of livestock management on the degradation process. The objective of this work was to demonstrate that the key SPPs for studying the impact of livestock treading depend on the objectives of the research and the environmental characteristics of the study site. This work used discriminant analysis to establish the most significant SPPs among the following: bulk density (BD), total porosity (P), field capacity (FC), infiltration capacity (IC), and aggregate stability (AS). Results showed that (1) IC and BD are the key properties for identifying the areas affected (bare patch) and unaffected (vegetated patch) by livestock treading, (2) none of the SPPs are significant under increasing stocking rates, and (3) BD is the key property for analyzing livestock impact with increasing stocking rate, using soil calcium carbonate content, slope exposure, and grass cover. We concluded that the relationship between physical soil degradation and stocking rate is not linear because it depends on environmental factors; therefore, to establish the key SPPs, it is necessary to take this fact into account.
Is There a Digital Rebound in the Process of Urban Green Development? New Empirical Evidence Using Ensemble Learning Methods
Authors: Ping Ying , Li Zhuolin
Published: May 2024

The convergence of digitization and greening is an unavoidable path of modern economic progress. Nonetheless, the digital economy does not consistently align with the principles of green development, potentially leading to a rebound effect in urban digitalization initiatives. To investigate the correlation between the digital rebound effect and urban green development, this study utilizes panel data from Chinese prefecture-level cities spanning from 2011 to 2019. By examining the dual impact of the digital economy on green development, the paper posits a theoretical hypothesis regarding the nonlinear marginal effect of the digital economy. This research demonstrates an inverted U-shaped correlation between the digital economy and urban green development via empirical analyses employing the random forest algorithm and partial dependency plots. It supports the existence of a moderate digital resiliency effect, which eventually reaches a state of stability rather than greatly diminishing the degree of green development in urban areas. In addition, the heterogeneity analysis reveals that the positive effects of the digital economy are more popular in cities located in the eastern and central regions, as well as in the National Comprehensive Pilot Zone for Big Data. However, these effects do not vary significantly among different ranks of cities. The mechanism test found that the information effect and the capital allocation effect are the mechanisms by which the digital economy affects green development, and there is a “U-shaped” relationship between the digital economy and information asymmetry and capital mismatch. According to the study’s results, improving the digital economy’s governance structure continues to make more sense than merely increasing the number of digital inputs.
A Study on the Impact of Income Gap on Consumer Demand: An Empirical Test Based on the Spatial Panel Durbin Model
Authors: Wang Dan
Published: May 2024

The study utilizes China Household Panel Survey (CFPS) data from 2010 to 2020 to create a spatial panel Durbin model and examines the spatial spillover effect of the income gap on consumer demand using spatial econometric techniques. Studies have shown that the income gap has a notable inverted U-shaped influence on consumer demand, and there is a strong inverted U-shaped spatial spillover effect between surrounding locations. Expanding the income difference within a specific range boosts consumer demand in both local and surrounding areas. Further increasing the income difference impedes the growth of consumer demand in both local and surrounding regions. Regional variations significantly impact how the income gap affects consumer demand through spatial spillover. From the perspective of consumption quantity, the “inverted U-shaped” inflection point in economically developed regions and eastern regions is on the left side of economically underdeveloped regions and western regions; from the perspective of consumer quality, this result is exactly the opposite. China should persist in enhancing efforts to advance income distribution system reform and improvement, bolster the development of inclusive, fundamental, and grassroots livelihoods, manage residents’ income gap amid evolving income levels, and stimulate consumer demand in local and neighboring regions.
Discrepancies of Functional Requirements of Façade Opening System between Real-Life Public and Built Environment Experts Focusing on Thermal Comfort and Ventilation
Authors: Lee Woohyoung , Choi Dong Hee , Kang Dong Hwa
Published: May 2024

A survey was conducted to analyze the discrepancies of the functional requirements of the façade system in residential units among 605 of the real-life public and 73 experts. Personal and housing information, resident life patterns, public façade usage behavior, and functional requirements were collected from the respondents. Both the public and experts recognized insulation as the main function of façade opening systems. More than 85% of the public and experts opened windows for ventilation, but ventilation was ranked 3rd amongst the public and 4th amongst experts in the main functions list of façade systems. The public cited the inflow of fine dust as the main reason for dissatisfaction with opening windows. In contrast, the experts cited a decrease in thermal comfort due to the inflow of external moisture as the reason for dissatisfaction with opening windows. The results showed that discrepancies exist between the public and experts’ perceptions of the main function of housing façade systems. Analyzing the common points and differences between the public and experts’ perception can help in developing façade system design and control technology.
Can Digital Finance Enable China’s Industrial Carbon Unlocking under Environmental Regulatory Constraints? Joint Tests of Regression Analysis and Qualitative Comparative Analysis
Authors: Xu Weicheng , Li Hanxia
Published: May 2024

Sustainable development goals challenge the carbon lock-in dilemma of the industrial economy, and identifying the motivation and mechanism behind carbon unlocking has become an urgent priority. With its inclusive and precise advantages, digital finance (DF) provides a new impetus for the economy’s low-carbon transformation, while reasonable environmental regulation (ER) acts as an important guiding constraint. We focus on the carbon unlocking performance of DF under ER constraints. After constructing and calculating the industrial carbon unlocking efficiency (ICUE), we observe the trends of ICUE fluctuating positively, clustering towards the eastern region, and polarization. Subsequently, based on theoretical analyses, we explore the marginal and configuration effects of DF and ER in improving ICUE using panel data from 30 Chinese provinces between 2011 and 2021 and adopt a mixed research method with regression analysis (Tobit hierarchical regression and quantile regression for panel data (QRPD)) and dynamic fuzzy-set qualitative comparative analysis (fsQCA). The regression analysis results show that DF can notably enhance China’s provincial ICUE, with ER generally serving as a positive moderator; however, the unlocking potential of informal environmental regulations needs further exploration. As ICUE improves in a specific location or time, the positive contribution of DF to ICUE also increases, whereas the moderating effect of ER exhibits an optimal range and follows an inverted U-shape. The dynamic fsQCA results support the findings of the regression analysis and further emphasize that effective cooperation between DF and ER is crucial for high ICUE, while inadequate DF support and the absence of formal environmental regulations remain bottlenecks in industrial carbon lock-in. Moreover, configuration paths demonstrate clear path dependency in both time and space, indicating a prolonged unlocking endeavor.
Factors Influencing Public Building Energy Consumption: A Case Study of Changjiang River Administration of Navigation Affairs in China
Authors: Wang Longhua , Cao Jingxin , Zheng Yuanzhou , Xu Yang , You Long , Wang Yibo
Published: May 2024

Based on the energy consumption data of the Changjiang River Administration of Navigation Affairs public building located in Wuhan, China, this paper analyzes the energy consumption characteristics of public buildings. Using the DesignBuilder energy simulation software (v7.0.0.096), various factors influencing building energy consumption are investigated. Furthermore, SPSS (v26.0.0.0) is employed to conduct correlation analyses between measured and simulated energy consumption data. The results indicate that the most significant factors affecting energy consumption are outdoor temperature, office equipment usage time, anticipated room temperature settings, boiler usage time, and per capita daily water consumption. By exploring the factors influencing energy consumption in public buildings, this study contributes novel insights into setting targets, adjusting schemes, and achieving energy-saving effects.
Public Bicycle Dispatch Method Based on Spatiotemporal Characteristics of Borrowing and Returning Demands
Authors: Liu Zhizhen , Wu Ziyi , Tang Feng , Gao Chao , Chen Hong , Xiang Wang
Published: May 2024

Public bicycle systems (PBSs) serve as the ‘last mile’ of public transportation for urban residents, yet the problem of the difficulty in borrowing and returning bicycles during peak hours remains a major bottleneck restricting the intelligent and efficient operation of public bicycles. Previous studies have proposed reasonable models and efficient algorithms for optimizing public bicycle scheduling, but there is still a lack of consideration for actual road network distances between stations and the temporal characteristics of demand at rental points in the model construction process. Therefore, this paper aims to construct a public bicycle dispatch framework based on the spatiotemporal characteristics of borrowing and returning demands. Firstly, the spatiotemporal distribution characteristics of borrowing and returning demands for public bicycles are explored, the origin–destination (OD) correlation coefficients are defined, and the intensity of connections between rental point areas is analyzed. Secondly, based on the temporal characteristics of rental point demands, a random forest prediction model is constructed with weather factors, time characteristics, and rental point locations as feature variables, and station bicycle-borrowing and -returning demands as the target variable. Finally, bicycle dispatch regions are delineated based on actual path distances between stations and OD correlation coefficients, and a public bicycle regional dispatch optimization method is established. Taking the PBS in Ningbo City as an example, the balancing optimization framework proposed in this paper is validated. The results show that the regional dispatch optimization method proposed in this paper can achieve optimized dispatch of public bicycles during peak hours. Additionally, compared with the Taboo search algorithm (TSA), the genetic algorithm (GA) exhibits a 11.1% reduction in rebalancing time and a 40.4% reduction in trip cost.
Study on Mechanical Characteristics of Living Stumps and Reinforcement Mechanisms of Slopes
Authors: Jiang Xueliang , Liu Wenjie , Yang Hui , Wang Haodong , Li Zhenyu
Published: May 2024

As a novel technology for slope protection, living stumps have demonstrated the ability to significantly enhance slope stability. This study aims to investigate the mechanical properties of living-stump root systems and their reinforcement mechanisms on slopes through three-dimensional modeling tests. Using ABS materials, a 3D model of a living elm stump was created via 3D printing; this was followed by slope model testing. The reinforcement mechanisms of living stumps were examined through a combination of model testing and numerical simulation. The results reveal that the presence of living stumps in the lower and middle sections of a slope causes the maximum-shear-stress zone of the soil to shift deeper. The stress distribution around the living stump is notably improved owing to the lateral root system. Living stumps positioned in the lower part of the slope intersect the potential sliding surface, gradually transferring soil shear stress to the root system through root–soil interactions. Furthermore, the tap roots and lateral roots of living stumps form a robust spatial network that can collectively withstand soil shear stress, thereby enhancing slope stability.
The Link between Environment and Organizational Architecture for Decision-Making in Educational Institutions: A Systemic Approach
Authors: Serra Fernanda Neves Tavares , Gonçalves Marcelo Carneiro , Bortoluzzi Sandro César , Costa Sergio Eduardo Gouvêa , Dias Izamara Cristina Palheta , Benitez Guilherme Brittes , Benitez Lisianne Brittes , Nara Elpidio Oscar Benitez
Published: May 2024

Numerous organizations employ decision-making processes to support operational activities; however, decisions and mistakes can significantly impact Market Performance (MP) due to the oversight of organizational architecture and the environment. This becomes particularly critical in the realm of strategic management, where improper practices and a lack of management understanding can lead to substantial losses. Hence, a systemic investigation was undertaken to explore the repercussions of not adopting such an approach concerning organizational architecture and the environment. Employing a quantitative analysis via hierarchical regression involving Confirmatory Factor Analysis and Ordinary Least Squares, using data gathered from a survey encompassing 134 collaborators from Brazilian Federal Universities. The findings show that the organizational environment positively impacts decision-making, leading to better MP. Additionally, organizational architecture partially mediates the link between the organizational environment and decision-making. Remarkably, national literature lacked research combining Student Assistance Program (PNAES) actions with MP improvement to assess Brazilian Federal Universities’ effectiveness.
Digital Transformation as a Driver of Sustainability Performance—A Study from Freight and Logistics Industry
Authors: Mutambik Ibrahim
Published: May 2024

Over the past two decades, environmental sustainability has become a key corporate and organisational issue. Today, firms are increasingly turning to existing and emerging digital technologies to help ensure that they meet the medium and long-term needs and expectations of customers and other stakeholders with respect to sustainability performance. This raises the important question of which digitisation factors most significantly impact environmental sustainability performance, as well as the mediating factor of sustainability innovation balance (the ability of a firm to balance the exploration of new innovations with the exploitation of existing innovations). A comprehensive survey instrument was developed and refined through expert feedback and a pilot study, leading to data collection from 374 professionals in the Freight and Logistics industry in Saudi Arabia, all of whom held senior positions in areas such as business development, IT, and Environmental, Social, and Governance (ESG) departments. This data was then analysed using structural equation modelling (SEM). The results of this analysis showed that the key factors impacting sustainability performance were digital competence, strategy alignment, digital adaptability, innovation exploitation and innovation exploration. These findings contribute to the current literature by expanding our understanding of the real-world drivers of sustainability performance. In practical terms, the study will help managers improve sustainability performance by enhancing resource efficiency, streamlining, and supply chain management, as well as improving employee engagement and training, fostering a culture of sustainability within the organisation.
Optimization Study of Soil Organic Matter Mapping Model in Complex Terrain Areas: A Case Study of Mingguang City, China
Authors: Mei Shuai , Tong Tong , Zhang Shoufu , Ying Chunyang , Tang Mengmeng , Zhang Mei , Cai Tianpei , Ma Youhua , Wang Qiang
Published: May 2024

Traditional soil organic matter mapping is mostly polygonal drawing, which is even more difficult to accurately depict in complex terrain areas. The spatial distribution of soil organic matter is closely related to agricultural production, natural resources, environmental governance, and socio-economic development. Efficiently, economically, and accurately obtaining information on changes in soil organic matter in areas with diverse topography is an urgent problem to be solved. Mingguang City has a high research value because of its unique topography and natural landscape. To solve the problem of soil organic matter mapping in this area, this study will construct an excellent organic matter prediction model. Using 173 soil survey samples (123 for training and 50 for testing), the optimal feature variable subsets selected from 31 environmental variables through Pearson correlation, stepwise regression-variance inflation factor, and recursive feature elimination models based on different algorithms were employed. Each selected feature subset was then used to construct organic matter prediction models using multiple advanced machine learning algorithms. By comparing accuracy validation and model performance, the organic matter prediction model suitable for Mingguang City (RFE-RF_SVM) was obtained, that is, the prediction model of organic matter based on support vector machines with the feature variables screened by the feature recursive elimination algorithm of random forest with RMSE = 3.504, VSI = 0.036, and R-squared = 0.730. Furthermore, the analysis focused on assessing the significance of the predictive factors. The mapping results of this study show that the soil organic matter content in the central and northwestern parts of the study area is low, and the reasons for this situation are different. The central part is mainly caused by the change of land use and topography, while the northwestern part is caused by the loose soil structure caused by the parent material. The government can take targeted measures to improve the soil in the areas with poor organic matter.
Dynamic Mechanical Performance of Sulfate-Bearing Soils Stabilized by Magnesia-Ground Granulated Blast Furnace Slag
Authors: Li Wentao , Yang Kang , Cheng Yang , Huang Ke , Hu Yan , Liu Le , Li Xing
Published: May 2024

Sulfate soils often caused foundation settlement, uneven deformation, and ground cracking. The distribution of sulfate-bearing soil is extensive, and effective stabilization of sulfate-bearing soil could potentially exert a profound influence on environmental protection. Ground granulated blast furnace slag (GGBS)–magnesia (MgO) can be an effective solution to stabilize sulfate soils. Dynamic cyclic loading can be used to simulate moving vehicles applied on subgrade soils, but studies on the dynamic mechanical properties of sulfate-bearing soil under cyclic loading are limited. In this study, GGBS-MgO was used to treat Ca-sulfate soil and Mg-sulfate soil. The swelling of the specimens was analyzed by a three-dimensional swelling test, and the change in compressive strength of the specimens after immersion was analyzed by an unconfined test. The dynamic elastic properties and energy dissipation of GGBS-MgO-stabilized sulfate soils were evaluated using a fatigue test, and the mineralogy and microstructure of the stabilized soils were investigated by X-ray diffraction and scanning electron microscopy. The results showed that the maximum swelling percentage of stabilized Ca-sulfate soil was achieved when the GGBS:MgO ratio was 6:4, resulting in an expansion rate of 14.211%. In contrast, stabilized Mg-sulfate soil exhibited maximum swelling at GGBS:MgO = 9:1, with a swelling percentage of 5.127%. As the GGBS:MgO ratio decreased, the dynamic elastic modulus of stabilized Ca-sulfate soil diminished from 2.8 MPa to 2.69 MPa, and energy dissipation reduced from 0.02 MJ/m3 to 0.019 MJ/m3. Conversely, the dynamic elastic modulus of stabilized Mg-sulfate soil escalated from 2.16 MPa to 6.12 MPa, while energy dissipation decreased from 0.023 MJ/m3 to 0.004 MJ/m3. After soaking, the dynamic elastic modulus of Ca-sulfate soil peaked (4.01 MPa) and energy dissipation was at its lowest (0.012 MJ/m3) at GGBS:MgO = 9:1. However, stabilized Mg-sulfate soil exhibited superior performance at GGBS:MgO = 6:4, with a dynamic elastic modulus of 0.74 MPa and energy dissipation of 0.05 MJ/m3. CSH increased significantly in the Ca-sulfate soil treated with GGBS-MgO. The generation of ettringite increased with the decrease in the GGBS-MgO ratio after immersion. MSH and less CSH were formed in GGBS-MgO-stabilized Mg-sulfate soil compared to Ca-sulfate soils. In summary, the results of this study provide some references for the improvement and application of sulfate soil in the field of road subgrade.
Exploring the Role of Digital Economy in Enhanced Green Productivity in China’s Manufacturing Sector: Fresh Evidence for Achieving Sustainable Development Goals
Authors: Zhao Fengyu , Xu Ziqing , Xie Xiaowen
Published: May 2024

Confronted with challenges such as escalating demand, expanding energy consumption, and emissions, China’s manufacturing sector stands at a pivotal juncture on its path towards sustainable development. Against the backdrop of a new wave of technological revolution and industrial transformation, exploring how the digital economy can foster growth in green total factor productivity (GTFP), particularly amidst technological diversification, holds significant importance for realizing sustainable development objectives. This study employs the system generalized method of moments (System GMM), encompassing 30 provinces in China, to delve deeply into the notable and dynamic correlation between the development index of the digital economy and GTFP. The findings reveal that the advancement of the digital economy significantly influences GTFP, underscoring its direct and enduring impact on green productivity. Key mechanisms through which the digital economy promotes green productivity are identified, including resource optimization, green technological innovation, data-driven decision making, and the transformation of environmentally sustainable behaviors. By bridging gaps in existing literature, this study integrates economic and environmental perspectives, emphasizing the necessity for formulating digital innovation policies aligned with environmental objectives. It provides richer insights into the role of the digital economy in enhancing GTFP, accentuating the potential of digital technologies in driving green transformation. With its holistic approach, this study combines economic efficiency with environmental sustainability, offering crucial guidance for policymakers and industry stakeholders in crafting sustainable development strategies.
Calibrated Empirical Neutrosophic Cumulative Distribution Function Estimation for Both Symmetric and Asymmetric Data
Authors: Abbasi Hareem , Shahzad Usman , Emam Walid , Hanif Muhammad , Ali Nasir , Mukhtar Mubeen
Published: May 2024

The traditional stratification weight is widely used in survey sampling for estimation under stratified random sampling (StRS). A neutrosophic calibration approach is proposed under neutrosophic statistics for the first time with the aim of improving conventional stratification weight. This addresses the challenge of estimating the empirical cumulative distribution function (CDF) of a finite population using the neutrosophic technique. The neutrosophic technique extends traditional statistics, dealing with indeterminate, vague, and uncertain values. Thus, using additional information, we are able to obtain an effective estimate of the neutrosophic CDF. The suggested estimator yields an interval range in which the population empirical CDF is likely to exist rather than a single numerical value. The proposed family of neutrosophic estimators will be defined under suitable calibration constraints. A simulation study is also computed in order to assess the effectiveness of the suggested and adapted neutrosophic estimators using real-life symmetric and asymmetric datasets.
Monoclonal-Antibody-Based Immunoassays for the Mycotoxins NX-2 and NX-3 in Wheat
Authors: Maragos Chris M. , Vaughan Martha M. , McCormick Susan P.
Published: May 2024

The fungal infestation of crops can cause major economic losses. Toxins produced by the causative fungi (mycotoxins) represent a potential safety hazard to people and livestock consuming them. One such mycotoxin is deoxynivalenol (DON, also known as vomitoxin), a trichothecene associated with Fusarium Head Blight of wheat. DON is commonly found in cereal crops worldwide. A group of trichothecene mycotoxins closely related to DON, the NX toxins, have been reported to occur in the northeastern United States and southern Canada. While many commercial immunoassays are available to detect DON, there are no rapid screening assays for the NX toxins. We describe the development and isolation of three monoclonal antibodies (mAbs) specific towards two NX toxins: NX-2 and NX-3. The mAbs did not recognize DON or several other closely related trichothecenes. One of the mAbs was selected for development of an enzyme-linked immunosorbent assay (ELISA) for NX-2 and NX-3 in wheat. The dynamic ranges for the assay were 7.7 to 127 μg/kg for NX-2 and 59 μg/kg to 1540 μg/kg for NX-3 in wheat. Recoveries from spiked wheat averaged 84.4% for NX-2 and 99.3% for NX-3, with RSDs of 10.4% and 11.3%, respectively (n = 24). The results suggest that this assay can be used to screen for NX toxins in wheat at levels relevant to human food and animal feed safety.
Confronting Inequalities and Bridging the Divide: A Retrospective Study Assessment of Country-Level COVID-19 Vaccine Equality with a Cox Regression Model
Authors: Cheng Lan , Chan W. K. , Zhu Lijie , Chao Melody H. , Wang Yang
Published: May 2024

COVID-19 vaccination is vital in reducing illness, hospitalization, and mortality in the face of this global pandemic. However, COVID-19 vaccination rates worldwide remain below WHO public health targets, and persistent structural inequities reduce vaccine uptake likelihood among populations of low socioeconomic status. We conducted a cross-sectional study based on publicly available data from the Our World in Data project. We included all 124 countries with available open epidemic data and a population of more than 5 million. We used a Cox Regression Model, with population, population density, median age, human development index, GDP per capita, gender inequality index, healthcare access and quality index, hospital beds per thousand people, completion rate of primary education, infection cases of COVID-19 by the end of 2022, and death rate due to COVID-19 by the end of 2022 as predictors for model hazard rates of completion of 50% population vaccination. According to our study, countries with higher populations, higher population density, higher human development index, lower gender inequality index, and lower hospital beds per 1000 people had a higher hazard rate, which means they were more likely to achieve 50% population vaccination faster. By utilizing the time to achieve vaccination rate goals as our primary endpoint, we evaluated inequity from a dual perspective, considering both the differences in vaccination rates and the duration required to attain them. Consequently, this study employed survival analysis approaches to gain a comprehensive understanding of vaccine drivers and population-level trends nationally and inform all communities from a statistical perspective to prepare for health emergencies. Development-level standing modified the effects of equal access to COVID-19 vaccination on cumulative cases and mortality, for which countries of low or medium human development tended to fare worse in outcomes than high human development countries. As COVID-19 vaccination efforts evolve, healthcare professionals, scholars, and policymakers need to identify the structural impediments to equitable vaccination awareness, access, and uptake so that future vaccination campaigns are not impeded by these barriers to immunization. Recognizing the complex nature of this significant barrier, it is evident that no single statistical analysis method can comprehensively address all intricacies.
An Efficient Seepage Element Containing Drainage Pipe
Authors: Xia Xiaozhou , Xu Xinxiang , Gu Xin , Zhang Qing
Published: May 2024

Drainage pipes are often positioned downstream of embankments to mitigate pore pressure, thereby reducing the risk of dam failure. Considering that the size of drainage pipes is much smaller than that of embankment dams, directly discretizing the drainage pipes will generate a huge number of elements. Therefore, this paper proposes a seepage element containing drainage pipes. In this element, the permeability of the drainage pipe is taken as the third type of permeable conductivity condition, and it is considered in the energy functional. The governing equations for the steady-state and the transient seepage element containing drainage pipe are derived using the variational principle, and the infiltration matrix, equivalent nodal seepage array, and water storage matrix of the seepage element containing drainage pipe are obtained. In conjunction with the user-defined element module UEL of ABAQUS 2016 software, the established seepage element containing drainage pipe is programmed. The accuracy and efficiency of the proposed seepage element containing drainage pipe are verified through seepage field simulations of three examples. Finally, the influence of the permeable conductivity of drainage pipes on the pressure reduction effect is investigated, providing a reference for the layout of drainage pipes in embankment defense systems.
Geochemistry of Arsenic and Salinity-Contaminated Groundwater and Mineralogy of Sediments in the Coastal Aquifers of Southwest Bangladesh
Authors: Uddin Md Riaz , Uddin Ashraf , Lee Ming-Kuo , Nelson Jake , Zahid Anwar , Haque Md Maruful , Sakib Nazmus
Published: May 2024

This study aimed to develop a geochemical database by thoroughly analyzing groundwater and sediments from coastal aquifers of southwest Bangladesh. Moreover, we investigated the source of sediment deposition and the mechanisms behind the presence of arsenic and salinity in groundwater. The seasonal distribution patterns of arsenic among the shallow and deep coastal aquifers were found to be 45.12 µg/l and 20.65 µg/l during dry and wet seasons, respectively. Moreover, the groundwater salinity distribution ranged from 3262.88 mg/l to 1930.88 mg/l during the dry and wet seasons. Cored sediment samples showed fine to medium sands of 92%, with silt and clay particles. The petrographic study of authigenic and heavy minerals revealed that the mineral grains were subangular to angular, indicating their textural immaturity of coastal sediments. The reactivity of goethite (FeOOH) and siderite (FeCO3) minerals suggests that the aquifers were subjected to slightly oxidized to moderately reducing conditions, with ORP values ranging from +50.40 mv to −149.5 mv. Such redox conditions could potentially result in the enrichment and mobility of arsenic in the groundwater. Although arsenic concentrations in deep aquifers are relatively low, higher salinity values are found in both shallow and intermediate coastal aquifers.
Incompressible Smoothed Particle Hydrodynamics Simulation of Sediment Erosion around Submarine Pipelines
Authors: Yan Sheng , Wang Dong , Li Yan , Gao Yu , Lin Jianguo , Shi Yawei
Published: May 2024

Sediment erosion around submarine pipelines is a popular topic, widely investigated in both ocean and submarine-pipeline engineering. In this paper, the incompressible smoothed-particle hydrodynamics (ISPH) method is modified for simulation of local scouring process around the submarine pipeline under the action of unidirectional flow. The erosion model is based on the Clear Water Particle–Turbid Water Particle–Critical Shear Stress (CWP-TWP-CSS) concept, and a sand–water two-phase model is proposed to deal with the sediment-entrained flow. The results of the numerical simulation are compared with the experimental data to verify the accuracy and applicability of the numerical model. The scouring process around the pipeline is investigated under different conditions, i.e., pipeline diameters, gap ratios, and flow velocities. The ISPH model is further used to study the flow characteristics of the scour pits around the submarine pipeline and the influence of the vortices on the maximum scour depth, to provide a theoretical basis for the stability design of submarine pipelines.
Karenia brevis and Pyrodinium bahamense Utilization of Dissolved Organic Matter in Urban Stormwater Runoff and Rainfall Entering Tampa Bay, Florida
Authors: Muni-Morgan Amanda L. , Lusk Mary G. , Heil Cynthia A.
Published: May 2024

This study investigated how nitrogen and dissolved organic matter (DOM) from stormwater runoff and rainfall support the growth of Karenia brevis and Pyrodinium bahamense. Excitation–emission matrix spectroscopy coupled with parallel factor analysis tracked changes in the optical properties of DOM in each bioassay, revealing greater reactivity of terrestrial humic-like DOM. Significant increases in cell yield and specific growth rates were observed upon additions of runoff for both species, with significant increases in specific growth rates upon the addition of a 2 in simulated rain event for P. bahamense only. By hour 48, 100% of the dissolved organic nitrogen (DON) in each treatment was utilized by P. bahamense, and by hour 72, over 50% of the DON was utilized by K. brevis. The percentage of bioavailable dissolved organic carbon (DOC) was greater for P. bahamense compared to K. brevis, suggesting a greater affinity for DOC compounds by P. bahamense. However, the bioavailability of DOM for each species could be owed to distinct chemical characteristics of labile DOM conveyed from each site. This study demonstrates that stormwater runoff and rainfall are both sources of labile DOM and DON for K. brevis and P. bahamense, which has implications for blooms of these species in Tampa Bay waters.
Water Composition, Biomass, and Species Distribution of Vascular Plants in Lake Agmon-Hula (LAH) (1993–2023) and Nearby Surroundings: A Review
Authors: Gophen Moshe
Published: May 2024

A significant change to the land cover in the Hula Valley was carried out during the 1950s: A swampy area densely covered by aquatic vegetation and the old shallow lake Hula were drained. The natural shallow lake and swamps land cover were converted into agricultural development land use in two stages: (1) Drainage that was accomplished in 1957; (2) Implementation of the renovated hydrological system structure, including the newly created shallow Lake Agmon-Hula (LAH), was completed in 2007. The long-term data record of the restored diversity of the submerged and emerged aquatic plant community, and its relation to water quality in the newly created shallow Lake Agmon-Hula LAH, was statistically evaluated. Internal interactions within the LAH ecosystem between aquatic plants and water quality, including nitrification, de-nitrification, sedimentation, photosynthetic intensity, and plant biomass and nutrient composition, were statistically evaluated. The plant community in LAH maintains a seasonal growth cycle of onset during late spring–summer and dieback accompanied by decomposed degradation during fall–early winter. The summer peak of aquatic plant biomass and consequent enhancement of photosynthetic intensity induces a pH increase during daytime and carbonate precipitation. Nevertheless, the ecosystem is aerobic and sulfate reduction and H2S concentration are negligible. The Hula reclamation project (HP) is aimed at the improvement of eco-tourism’s integration into management design. The vegetation research confirms habitat enrichment.
Correction: Abu Arra, A.; Şişman, E. Characteristics of Hydrological and Meteorological Drought Based on Intensity-Duration-Frequency (IDF) Curves. Water 2023, 15, 3142
Authors: Abu Arra Ahmad , Şişman Eyüp
Published: May 2024

In the original publication [...]
Case Study for Predicting Failures in Water Supply Networks Using Neural Networks
Authors: Medeiros Viviano de Sousa , dos Santos Moisés Dantas , Brito Alisson Vasconcelos
Published: May 2024

This study deals with the prediction of recurring failures in water supply networks, a complex and costly task, but essential for the effective maintenance of these vital infrastructures. Using historical failure data provided by Companhia de Água e Esgotos da Paraíba (CAGEPA), the research focuses on predicting the time until the next failure at specific points in the network. The authors divided the failures into two categories: Occurrences of New Faults (ONFs) and Recurrences of Faults (RFs). To perform the predictions, they used predictive models based on machine learning, more specifically on MLP (Multi-Layer Perceptron) neural networks. The investigation unveiled that through the analysis of historical failure data and the consideration of variables including altitude, number of failures on the same street, and days between failures, it is possible to achieve an accuracy greater than 80% in predicting failures within a 90-day interval. This demonstrates the feasibility of using fault history to predict future water supply outages with significant accuracy. These forecasts allow water utilities to plan and optimize their maintenance, minimizing inconvenience and losses. The article contributes significantly to the field of water infrastructure management by proposing the applicability of a data-driven approach in diverse urban settings and across various types of infrastructure networks, including those pertaining to energy or communication. These conclusions underscore the paramount importance of systematic data collection and analysis in both averting failures and optimizing the allocation of resources within water utilities.
Optimization of Elbow Draft Tubes for Variable Speed Propeller Turbine
Authors: Souček Jiří , Nowak Petr
Published: May 2024

The design of the elbow draft tubes is challenging due to the complexity of the flow. The whole turbine unit’s power output strongly depends on the draft tube function, especially for the low-head turbines. The article presents a novel approach to optimizing elbow draft tubes for a variable-speed propeller turbine designed for low-head applications. First, the study addresses the specifics of the propeller variable speed turbine by comparing the classical Kaplan turbine. Then, the grid scaling test is conducted to evaluate the uncertainty of the pressure regeneration. Further, a new approach to parameterising the elbow draft tube geometry is introduced. The study employs ANSYS CFX 2021 R1 software for numerical simulation to optimise the elbow draft tube geometry in the CAESES environment. After the sensitivity test and deselecting the non-sensitive parameters, we perform multi-objective genetic algorithm (MOGA) optimization. The optimization process results in a Pareto front of optimised elbow draft tube shapes with the best pressure regeneration for different draft tube construction heights, enabling the selection of suitable candidates for various locations. Minimal difference in the performance of the selected elbow draft tube shapes with the simple straight draft tube confirms a high-quality draft tube optimization achievement.
Mitigation of Karenia brevis Cells and Brevetoxins Using Curcumin, a Natural Supplement
Authors: Hall Emily R. , Heil Cynthia A. , Frankle Jessica D. , Klass Sarah , Devillier Victoria , Lovko Vincent , Toyoda Jennifer H. , Pierce Richard
Published: May 2024

Curcumin, a natural plant product, was investigated as a mitigation tool against Karenia brevis, the toxic dinoflagellate responsible for Florida red tides. A series of laboratory bench-top studies were conducted with additions of 0.1, 1, 2, 3, 5, 10, 20, 30, and 40 mg/L curcumin to K. brevis at an average of 1.0 × 106 cells/L to determine the efficacy of curcumin against K. brevis cells and brevetoxins and to optimize treatment dosage. Treatment with 5 mg/L of curcumin reduced K. brevis cell abundance by 89% and total brevetoxins by 60% within 24 h. Lower concentrations of curcumin (0.1–3 mg/L) exhibited between a 2 and 45% reduction in K. brevis and a reduction in brevetoxins of between 2 and 44% within 24 h. At the highest curcumin doses, 30 and 40 mg/L, a 100% reduction in cell abundance was observed by 6 h, with reduction in total brevetoxins by at least 64% in 48 h. These results suggest that curcumin, used alone or potentially in combination with other technologies, is a promising K. brevis bloom mitigation option.
Modeling Environmental Vulnerability for 2050 Considering Different Scenarios in the Doce River Basin, Brazil
Authors: Campos Jasmine Alves , da Silva Demetrius David , Pires Gabrielle Ferreira , Filho Elpídio Inácio Fernandes , Amorim Ricardo Santos Silva , de Menezes Filho Frederico Carlos Martins , de Melo Ribeiro Celso Bandeira , Lorentz Juliana Ferreira , Aires Uilson Ricardo Venâncio
Published: May 2024

Understanding climate change and land use impacts is crucial for mitigating environmental degradation. This study assesses the environmental vulnerability of the Doce River Basin for 2050, considering future climate change and land use and land cover (LULC) scenarios. Factors including slope, elevation, relief dissection, precipitation, temperature, pedology, geology, urban distance, road distance, and LULC were evaluated using multicriteria analysis. Regional climate models Eta-HadGEM2-ES and Eta-MIROC5 under RCP 4.5 and RCP 8.5 emission scenarios were employed. The Land Change Modeler tool simulated 2050 LULC changes and hypothetical reforestation of legal reserve (RL) areas. Combining two climate and two LULC scenarios resulted in four future vulnerability scenarios. Projections indicate an over 300 mm reduction in average annual precipitation and an up to 2 °C temperature increase from 2020 to 2050. Scenario 4 (RCP 8.5 and LULC for 2050 with reforested RLs) showed the greatest basin area in the lowest vulnerability classes, while scenario 3 (RCP 4.5 and LULC for 2050) exhibited more high-vulnerability areas. Despite the projected relative improvement in environmental vulnerability by 2050 due to reduced rainfall, the complexity of associated relationships must be considered. These results contribute to mitigating environmental damage and adapting to future climatic conditions in the Doce River Basin.