bluuebunny/crossref_metadata_2025 huggingface dataset:
Remote Sensing of Chlorophyll-a and Water Quality over Inland Lakes: How to Alleviate Geo-Location Error and Temporal Discrepancy in Model Training
Authors: Park Jongmin , Khanal Sami , Zhao Kaiguang , Byun Kyuhyun
Published: July 2024

Harmful algal blooms (HABs) threaten lake ecosystems and public health. Early HAB detection is possible by monitoring chlorophyll-a (Chl-a) concentration. Ground-based Chl-a data have limited spatial and temporal coverage but can be geo-registered with temporally coincident satellite imagery to calibrate a remote sensing-based predictive model for regional mapping over time. When matching ground and satellite data, positional and temporal discrepancies are unavoidable due particularly to dynamic lake surfaces, thereby biasing the model calibration. This limitation has long been recognized but so far has not been addressed explicitly. To mitigate such effects of data mismatching, we proposed an Akaike Information Criterion (AIC)-like weighted regression algorithm that relies on an error-based heuristic to automatically favor “good” data points and downplay “bad” points. We evaluated the algorithm for estimating Chl-a over inland lakes in Ohio using Harmonized Landsat Sentinel-2. The AIC-like weighted regression estimates showed superior performance with an R2 of 0.91 and an error variance (σE2) of 0.29 μg/L, outperforming linear regression (R2 = 0.34, σE2 = 2.34 μg/L) and random forest (R2 = 0.82, σE2 = 0.92 μg/L). We also noticed the poorest performance occurred in the spring due to low reflectance variation in clear water and low Chl-a concentration. Our weighted regression scheme is adaptive and generically applicable. Future studies may adopt our scheme to tackle other remote sensing estimation problems (e.g., terrestrial applications) for alleviating the adverse effects of geolocation errors and temporal discrepancies.
Research on Jianghan Plain Water System Dynamics and Influences with Multiple Landsat Satellites
Authors: Dong Feiyan , Huang Jie , Meng Linkui , Li Linyi , Zhang Wen
Published: July 2024

The study of the spatio-temporal distribution and evolution trends of water resources in large regions plays an important role in the study of regional water resource planning, regional economic and social development, and water disasters. In this study, a Landsat multi-index relationship and water probability thresholding method is developed based on the Google Earth Engine (GEE) platform, which can support the integration of multiple Landsat satellites. The algorithm jointly combines multiple remote sensing metrics along with the calculation of water probability to produce an interannual water body product for the Jianghan Plain on a 20-year time series. The results indicate that the Landsat multi-index relationship algorithm used in this study has high accuracy in extracting long-term water bodies in extensive, flat terrain areas such as the Jianghan Plain, with an overall accuracy (OA) of 97.23%. By analyzing the water body products and landscape patterns, we have identified the following features: (1) From 2002 to 2021, the changes in river water bodies in the Jianghan Plain were relatively small, and some lakes experienced a shrinkage in area. Overall, there is a strong correlation between water distribution and precipitation. (2) The complexity index of water bodies shows a strong negative correlation with effective irrigation area and population, indicating a strong mutual influence between water bodies and socio-economic activities. (3) Through the study of the distribution characteristics of built-up areas and the water system, it was found that for large rivers, the larger the size of the river, the more built-up areas are nearby. Most extensive built-up areas are located near large rivers. This study contributes to providing methods and data support for urban planning, water resource management, and disaster research in the Jianghan Plain.
Near-Complete Sampling of Forest Structure from High-Density Drone Lidar Demonstrated by Ray Tracing
Authors: Zhang Dafeng , Král Kamil , Krůček Martin , Cushman K. C. , Kellner James R.
Published: July 2024

Drone lidar has the potential to provide detailed measurements of vertical forest structure throughout large areas, but a systematic evaluation of unsampled forest structure in comparison to independent reference data has not been performed. Here, we used ray tracing on a high-resolution voxel grid to quantify sampling variation in a temperate mountain forest in the southwest Czech Republic. We decoupled the impact of pulse density and scan-angle range on the likelihood of generating a return using spatially and temporally coincident TLS data. We show three ways that a return can fail to be generated in the presence of vegetation: first, voxels could be searched without producing a return, even when vegetation is present; second, voxels could be shadowed (occluded) by other material in the beam path, preventing a pulse from searching a given voxel; and third, some voxels were unsearched because no pulse was fired in that direction. We found that all three types existed, and that the proportion of each of them varied with pulse density and scan-angle range throughout the canopy height profile. Across the entire data set, 98.1% of voxels known to contain vegetation from a combination of coincident drone lidar and TLS data were searched by high-density drone lidar, and 81.8% of voxels that were occupied by vegetation generated at least one return. By decoupling the impacts of pulse density and scan angle range, we found that sampling completeness was more sensitive to pulse density than to scan-angle range. There are important differences in the causes of sampling variation that change with pulse density, scan-angle range, and canopy height. Our findings demonstrate the value of ray tracing to quantifying sampling completeness in drone lidar.
Unmasking the Authoritarian Mob Boss: A Critical Analysis of Donald Trump’s Political Leadership
Authors: Baptist Najja K. , Clark Kenneth A.
Published: July 2024

This article comprehensively examines Donald Trump’s political leadership, arguing that his tenure as the 45th President of the United States exhibited characteristics commonly associated with authoritarian mob bosses. Drawing upon various empirical evidence and theoretical political science frameworks, the study sheds light on the underlying dynamics that shaped Trump’s leadership style and its implications for democratic governance. The analysis begins by contextualizing Trump’s rise to power within the erosion of democratic norms. It explores how his rhetoric, characterized by demagoguery and the demonization of opponents, mirrors the tactics employed by mob bosses to consolidate their power and suppress dissent. Moreover, the study uncovers the striking similarities between Trump’s administration management and the hierarchical structures of organized crime, highlighting his reliance on loyalty, personal connections, and a disregard for institutional checks and balances. Furthermore, this research delves into Trump’s autocratic tendencies, as evidenced by his disdain for the free press, attacks on the judiciary, and attempts to undermine the integrity of democratic processes. It reveals how these actions align with the strategies employed by authoritarian leaders to silence opposition and perpetuate their dominance. By examining Trump’s presidency through process tracing, this study contributes to our understanding of the complex relationship between authoritarianism and the erosion of democratic institutions. The findings underscore the urgent need for continued scholarly and public scrutiny of leaders who exhibit traits akin to authoritarian mob bosses to safeguard the principles of democratic governance and protect the integrity of liberal democracies.
Pre-Exercise Caffeine and Sodium Bicarbonate: Their Effects on Isometric Mid-Thigh Pull Performance in a Crossover, Double-Blind, Placebo-Controlled Study
Authors: Kaçoğlu Celil , Kirkaya İzzet , Ceylan Halil İbrahim , de Assis Gilmara Gomes , Almeida-Neto Paulo , Bayrakdaroğlu Serdar , Chaves Oliveira César , Özkan Ali , Nikolaidis Pantelis T.
Published: July 2024

Caffeine and sodium bicarbonate are extensively researched ergogenic aids known for their potential to enhance exercise performance. The stimulant properties of caffeine on the central nervous system, coupled with the buffering capacity of sodium bicarbonate, have been associated with improved athletic performance. This has led to investigations of their combined effects on strength. The aim of the present study is to investigate the effect of isolated and combined caffeine and sodium bicarbonate consumption on strength using the isometric mid-thigh pull test (IMTP). Nineteen male college students (age 23.6 ± 1.6 years) participated in this crossover, double-blind, placebo-controlled study. They were exposed to the following conditions: control (no supplement), placebo (20 g maltodextrin), caffeine (6 mg/kg), sodium bicarbonate (0.3 g/kg), and a combination of caffeine and sodium bicarbonate. Supplements and placebo were diluted in water and consumed 60 min prior to the IMTP tests. Two 5 s IMTP trials were performed at 40–60% and 60–80% of One Repetition of Maximum (1RM) with a 60 s rest between. Consumption of caffeine or Caf + NaHCO3 did not significantly change peak IMTP strength values at any intensity (p = 0.110). The peak IMTP values did not show significant differences between conditions or from control condition values (1091 ± 100 N) to Caf (1224 ± 92 N), NaHCO3 (1222 ± 74 N), and Caf ± NaHCO3 (1152 ± 109 N). However, the test of the results of the ANOVA analysis of repeated measures of effect within the caffeine condition was significant for the increase in IMTP relative strength compared to control (p < 0.05). Thus, the IMTP force values increased significantly from control to Caf (p = 0.016) and from Pla to Caf (p = 0.008), but not for other comparisons (p > 0.05). In summary, caffeine supplementation alone, taken 60 min before exercise, positively affects submaximal strength performance. In contrast, sodium bicarbonate, whether taken alone or in combination with caffeine, does not enhance submaximal strength in the IMTP tests.
How Financial Inclusion and Green Innovation Promote Green Economic Growth in Developing Countries
Authors: Abbas Sohail , Dastgeer Ghulam , Nasreen Samia , Kousar Shazia , Riaz Urooj , Arsh Saira , Imran Muhammad
Published: July 2024

The aim of this study is to analyze the impact of financial inclusion on green economic growth in developing countries. For this purpose, 12 developing countries were selected based on the availability of data: Armenia, Egypt, Ethiopia, India, Indonesia, Iran, Jamaica, Kenya, Pakistan, Sri Lanka, Thailand, and Tunisia. Annual data for the period from 2004 to 2023 were used for this study. The focus of this study is on the achievement of Sustainable Development Goal 13 (SDG 13), which requires immediate intervention to address the challenges of climate change and its consequences. This study used principal component analysis (PCA) to construct the financial inclusion index. In this study, we conducted a unit root analysis using the second-generation unit root test. For long-run estimates, we used the Fully Modified Least Squares (FMOLS) model. According to the findings of the study, green innovation (β = 0.052 *), foreign direct investment (β = 0.438 *), and trade openness (β = 0.016 **) have positive and significant impacts on green economic growth (GEG). The extent of the positive effect of foreign direct investment (FDI) is greater, compared to green innovation and trade openness (TR). The results also indicate that financial inclusion (β = −0.241) and population (β = −0.291) have significantly detrimental impacts on GEG. However, the population impacts GEG to a greater extent, compared to financial inclusion. Similarly, results indicate that the negative impact of financial inclusion on GEG is greater than the positive impact of green innovation on GEG. On the basis of the findings of this study, policymakers are advised to promote green innovation, foreign direct investment, and trade openness to promote green economic growth. Moreover, this study suggests that green finance or financial inclusion constrained by environmental quality should be promoted to safeguard environmental quality.
Vehicle Turning Carbon Emissions and Highway Planar Alignment Design Indicators
Authors: Dong Yaping , Li Tong , Xu Jinliang , Wang Bin
Published: July 2024

The carbon emitted by vehicles traveling on curved roads is greatly affected by the alignment of the route, yet the mechanism behind this is not yet clear, leading to current horizontal alignment designs being unable to avoid this problem. To clarify the principles and indicator thresholds of low-carbon design for planar geometry, this study takes the carbon emission of traveling on curved routes as the research object, and establishes a relationship model between carbon emissions and design indicators based on the principles of vehicle dynamics and kinematics. Field tests were conducted to validate the quantitative relationship model. The model shows that both radius and superelevation are negatively correlated with carbon emissions, while the lateral force coefficient is positively correlated with carbon emissions. The contribution of radius to carbon emissions is greater than that of superelevation. This study clarifies the recommended values of low-carbon design indicators by assessing carbon emissions according to the current route design specification, outlines the principles of superelevation settings, and proposes a methodology to deal with the relationship between superelevation and the lateral friction coefficient. The research findings promote the quantification and standardization of low-carbon highway design, contributing to the early mitigation of high-carbon emissions from curved traffic during the design phase.
An OVR-FWP-RF Machine Learning Algorithm for Identification of Abandoned Farmland in Hilly Areas Using Multispectral Remote Sensing Data
Authors: Wang Liangsong , Li Qian , Wang Youhan , Zeng Kun , Wang Haiying
Published: July 2024

Serious farmland abandonment in hilly areas, and the resolution of commonly used satellite-borne remote sensing images are insufficient to meet the needs of identifying abandoned farmland in such regions. Furthermore, addressing the problem of identifying abandoned farmland in hilly areas with a certain level of accuracy is a crucial issue in the research of extracting information on abandoned farmland patches from remote sensing images. Taking a typical hilly village as an example, this study utilizes airborne multispectral remote sensing images, incorporating various feature factors such as spectral characteristics and texture features. Aiming at the issue of identifying abandoned farmland in hilly areas, a method for extracting abandoned farmland based on the OVR-FWP-RF algorithm is proposed. Furthermore, two machine learning algorithms, Random Forest (RF) and XGBoost, are also utilized for comparison. The results indicate that the overall accuracy (OA) of the OVR-FWP-RF, Random Forest, and XGboost classification algorithms have reached 92.66%, 90.55%, and 90.75%, respectively, with corresponding Kappa coefficients of 0.9064, 0.8796, and 0.8824. Therefore, by combining spectral features, texture features, and vegetation factors, the use of machine learning methods can improve the accuracy of identifying ground objects. Moreover, the OVR-FWP-RF algorithm outperforms the Random Forest and XGboost. Specifically, when using the OVR-FWP-RF algorithm to identify abandoned farmland, its producer accuracy (PA) is 3.22% and 0.71% higher than Random Forest and XGboost, respectively, while the user accuracy (UA) is also 5.27% and 6.68% higher, respectively. Therefore, OVR-FWP-RF can significantly improve the accuracy of abandoned farmland identification and other land use type recognition in hilly areas, providing a new method for abandoned farmland identification and other land type classification in hilly areas, as well as a useful reference for abandoned farmland identification research in other similar areas.
Zero-Carbon Vehicles and Power Generation
Authors: Yu Wenbin , Zeng Guang
Published: July 2024

In recent decades, traditional fossil fuels such as coal, oil, and natural gas have made the greatest contributions to the economic development of the industrial sector [...]
Carbon Footprint of Main Grain Crop Production in Hubei and Jiangsu Provinces, 2005–2019
Authors: Han Yunxia , Xi Wende , Xu Jing , Yao Guanxin
Published: July 2024

Hubei and Jiangsu Provinces, significant in grain production, play a crucial role in national food security. We studied the carbon footprint of main grain crops (rice, maize, and wheat) from 2005 to 2019 in these provinces to identify trends, contributing factors, and emission efficiencies. This study seeks to inform sustainable agricultural practices and policies in the context of climate change mitigation. Jiangsu Province’s rice and wheat output surpasses Hubei’s due to higher yields per unit area. Rice consistently shows the highest carbon footprint per unit area, followed by wheat, with maize exhibiting the lowest. Carbon footprint per unit yield varies significantly: for rice, it ranges from 0.15 to 0.29 kg CO2-eq per kg; for wheat, from 0.19 to 0.22 kg CO2-eq per kg; and for maize, from 0.13 to 0.15 kg CO2-eq per kg. The distribution of crop production affects these footprints; central regions generally exhibit lower values compared to southwest and southeast areas. Fertilizer and electricity together contribute significantly to carbon emissions, especially in rice production (over 75%), and to a lesser extent in maize and wheat production (approximately 69% and 85%, respectively). Improving fertilizer efficiency, irrigation, and mechanization is crucial for developing low-carbon agriculture in these pivotal grain-producing regions.
Does the Low-Carbon Transition Affect the Wage Level of Enterprises? Evidence from China’s Low-Carbon City Pilot Policies
Authors: Peng Su , Liu Shudong
Published: July 2024

ESG (Environmental, Social, and Governance) performance is necessary to establish sustainable corporations. As the scale effect of the market application of low-carbon technologies is yet to be realised, China’s enterprises may find it difficult to balance their environmental (low-carbon transition) and social (increase in wages) responsibilities, and are caught in a governance dilemma. Therefore, in order to test the above hypotheses, we utilised the staggered difference-in-differences method to investigate the wage effects of low-carbon transformations. The results are displayed as follows. First, the low-carbon transition constraint initially increases firms’ labour demand and reduces energy consumption, leading to lower productivity and thus negatively affecting firms’ wages, even though the low-carbon transition can promote internal equity. Second, the impact of the policy on wages is heterogeneous. It has a more pronounced negative impact on enterprise wages in state-owned enterprises, old enterprises, primary and secondary industry enterprises, and low-carbon enterprises, whereas its promoting effect on internal fairness within old enterprises, secondary industry enterprises, and low-carbon enterprises is more significant. Finally, the negative impact of low-carbon policies on corporate wages gradually decreases while strengthening the promoting effect on the internal fairness of employee remuneration. The above results confirm that at this stage, when China’s enterprises are pursuing the environmental goal of low-carbon transition, it will affect their efficiency in the short term, which in turn will lead to lower wages. Moreover, this problem is too difficult to be solved by enterprises alone and requires assistance from the government. Under the ESG concepts, we provide insights into how to coordinate policies to improve living standards and promote low-carbon transformations.
Assessment of Nitrate and Phosphate Concentrations in Discharge Water from Ditch Networks across Different Peatland Use Types: Implications for Sustainable Peatland Use Management
Authors: Apori Samuel Obeng , Giltrap Michelle , Dunne Julie , Tian Furong
Published: July 2024

Peat soils, when drained and transformed for different land uses, can release pollutants such as nitrate and phosphate into nearby water bodies and ecosystems through ditch networks. However, there have been limited studies to ascertain the extent and impact of these nutrient releases under various peatland use types. A total of fifty-four water samples were collected between October 2021 and January 2022 from five industrial cutaway bogs, twenty-five grasslands, and twenty-four forest plantations. The water samples were subsequently examined for nitrate–nitrogen and phosphate–phosphorus using the HACH DR890 colorimeter. This study showed that the nitrate–nitrogen concentration of the discharge water ranged from 6.9 mg/L from forestry to 10.52 mg/L from grassland. The phosphate–phosphorus concentration ranged from 0.43 mg/L from forestry to 0.78 mg/L from grassland. The nitrate–nitrogen and phosphate–phosphorus concentrations in the drainage channel exhibited by the grassland and the cutover did not differ significantly (p > 0.05). Upon comparing the results obtained with the established safety limits set by the European Union (EU) and World Health Organization (WHO), it was observed that phosphate–phosphorus and nitrite–nitrogen concentration in the surface water (specifically, discharge water) exceeded the permissible threshold concentrations in surface water. The nutrient pollution index revealed that the discharge water from the ditch networks across the studied peatland use type was highly polluted, with a trend following the order of grassland > cutover > forestry. These results are in line with the broader issue of excessive nutrient inputs in freshwater ecosystems, which can lead to eutrophication. This study promotes sustainable water resources and peatland management practices by determining nitrate–nitrogen and phosphate–phosphorus concentrations in discharge water from ditch networks associated with different peatland use types: grassland, forestry, and cutover. This research emphasizes the critical need for sustainable peatland management to improve water quality in the river basin districts under the Water Framework Directive.
Organic Fraction Municipal Solid Waste Compost and Horse Bean Green Manure Improve Sustainability of a Top-Quality Tobacco Cropping System: The Beneficial Effects on Soil and Plants
Authors: Sifola Maria Isabella , Cozzolino Eugenio , Todisco Daniele , Palladino Mario , Sicignano Mariarosaria , del Piano Luisa
Published: July 2024

Organic amendment and green manuring are two agricultural practices highly recommended to improve sustainability in agriculture since they show numerous beneficial effects on both soils and crops. The main aim of the present study was to evaluate the effect of both, specifically organic fraction municipal solid waste (OFMSW) compost and horse bean (Vicia faba L., cv minor) green manure, combined separately or together with a mineral fertilization using synthetic products and in comparison with a mineral fertilization alone (control), on a top-quality tobacco crop (dark fire-cured Kentucky) grown in the cultivation district of Central Italy (High Tiber Valley, Tuscany region) in 2020 and 2021. The following parameters were measured: (i) leaf emergence rate (LER, leaves day−1); (ii) crop growth rate (CGR, kg dry biomass ha−1 day−1); (iii) root weight density (RWD, mg cm−3); (iv) yield of cured product (CLY, Mg ha−1). Analytical determinations were carried out on soil, sampled at the 0–0.3 m depth (organic matter, %; total N, %; NO3-N, mg kg−1; C/N; P and K, mg kg−1), and on plant biomass (total N, %; NO3-N, kg ha−1). Soil water retention measures were also made. Water productivity (WP, kg cured product m−3 gross crop evapotranspiration, ETc gross), irrigation water use efficiency (IWUE, kg cured product m−3 seasonal irrigation volume) and N agronomic efficiency (NAE, kg cured product kg−1 mineral N applied by synthetic fertilizers) were calculated. Both the applications of OFMSW compost and horse bean green manure increased soil content of organic matter and main nutrients (N, P and K), as well as C/N, when compared with control conditions. There was an increase in soil water content in C conditions over the entire soil matric potential interval (0.04 to 1.2 MPa) with a maximum value at 1.2 MPa in both years. Both practices appeared promising for tobacco cultivation and could help to better address the nitrogen needs of the crop during the season and reduce potential water pollution due to nitrates. Considering the amount of synthetic nitrogen fertilizer saved by using both organic soil amendment and green manuring, there should be fewer potential carbon emissions due to the production, transportation and field application of synthetic nitrogen fertilizers.
Employing Artificial Intelligence for Enhanced Microbial Fuel Cell Performance through Wolf Vitamin Solution Optimization
Authors: Farahani Hamed , Ghasemi Mostafa , Sedighi Mehdi , Raut Nitin
Published: July 2024

The culture medium composition plays a critical role in optimizing the performance of microbial fuel cells (MFCs). One under-investigated aspect of the medium is the impact of the Wolf vitamin solution. This solution, known to contain essential vitamins like biotin, folic acid, vitamin B12, and thiamine, is believed to enhance bacterial growth and biofilm formation within the MFC. The influence of varying Wolf vitamin solution concentrations (2, 4, 6, 8, and 10 mL) on microbial fuel cell (MFC) performance is investigated in this study. Python 3.7.0 software is employed to enhance and anticipate the performance of MFC systems. Four distinct machine-learning algorithms, namely adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), categorical boosting algorithm (CatBoost), and support vector regression (SVR), are implemented to predict power density. In this study, a data split of 80% for training and 20% for testing was employed to optimize the artificial intelligence (AI) model. The analysis revealed that the optimal concentration of Wolf mineral solution was 5.8 mL. The corresponding error percentages between the experimental and AI-predicted values for current density, power generation, COD removal, and coulombic efficiency were found to be remarkably low at 0.79%, 0.5%, 1.89%, and 1.27%, respectively. These findings highlight the significant role of Wolf mineral solution in maximizing MFC performance and demonstrate the exceptional precision of the AI model in accurately predicting MFC behavior.
Land Cover and Socioeconomic Analysis for Recommended Flood Risk Reduction Strategies in Java Island, Indonesia
Authors: Sigit Adityawan , Harada Morihiro
Published: July 2024

This study utilizes a novel approach by analyzing land use and socioeconomic factors to enhance flood risk reduction strategies on Java Island, Indonesia. Using datasets from inaRISK hazard profiles, GlobCover land cover data, and Indonesian national statistics, the research offers a methodology for mitigating flood risks in diverse geographic and socioeconomic landscapes. The study found flood exposure rates ranging from 1.1% to 63%, averaging 26.5% across 114 districts, and revealed a correlation between high flood exposure and socioeconomic indicators. Cluster analysis identified four types of regions with unique flood risk management needs. Socioeconomic analysis showed significant income and education level variations across clusters, with urban areas having a higher Gross Regional Domestic Product and better education levels than rural areas. This socioeconomic divide is crucial for understanding different regions’ capacities to respond to and recover from floods. Integrating socioeconomic factors with land use and flood exposure data allows for tailored disaster risk reduction strategies. For high-risk urban areas, structural interventions and community-focused initiatives are recommended, while rural areas benefit from sustainable land management practices. This study highlights the need for a combined approach to flood risk management and strategies, and provides a model adaptable to similar regions.
Optimizing Ghana’s Socioeconomic Metabolism Amid Urbanization from 2000 to 2019: An Emergy Synthesis
Authors: Boateng Prince Osei , Lee Jae Min
Published: July 2024

This study assessed Ghana’s sustainability from 2000 to 2019 using emergy synthesis. This research study also explored the relationship between changes in Ghana’s socioeconomic metabolism and the expansion of urban areas. The results showed a significant increase of 126% in total emergy use during the study period. This increase was mainly due to a rise in import emergy, which went up from 2.90% to 37.47%, while Ghana’s self-sufficiency capacity decreased from 97.10% to 62.53%. This shift in total emergy utilization indicates that Ghana’s socioeconomic system is transitioning from relying heavily on indigenous resources to increasingly depending on purchased resources to drive economic growth. The emergy sustainability index (EmSI) suggests that Ghana’s socioeconomic system is resource-consuming and has low system performance. To address this situation, this study recommends restructuring Ghana’s socioeconomic system to optimize its indigenous renewable resources while reducing import dependency and environmental stress. Expanding urban areas contributes to resource consumption, especially refined fuels and construction materials. This underscores the importance of urban policies that take into account changes in socioeconomic metabolism as a reference for effective urban land administration.
Dual-Channel Supply Chain Coordination Considering Green and Service Inputs
Authors: Guan Yefeng , Wan Chao , Wang Wei
Published: July 2024

The rise of the green economy and the dual-channel model has led to consumer preferences for a model that is both green and service-based. At the same time, customer service expectations have led to greater uncertainties in corporate decision-making. However, many research gaps remain in terms of how green and service-based models work together in a dual-channel supply chain to influence operational decisions and achieve efficiency improvements. Therefore, while considering customer expectations, this study adopts Stackelberg game theory to construct a dual-channel supply chain analysis that considers green and service inputs and analyzes the optimal decisions of manufacturers and retailers. The results show that when the costs of green inputs are low, this increases the greenness and prices of green products while also stimulating the retailer to improve service levels and common product prices. When the retailer’s service costs are low, this promotes higher service levels and product prices but inhibits product greenness and green product prices in the online channel. In addition, centralized decision-making is associated with higher product greenness, which is beneficial from an environmental perspective. Numerical analysis further reveals that profit-sharing contracts can be effective in achieving supply chain coordination. These findings have reference significance for the coexistence and interaction of green and service-based factors in dual-channel supply chains, as well as provide a reference value for the impact of customer service expectations on supply chain-related decision-making.
The Evolution of Behavioral Strategies in the Game Theory Context of National Park Management: A Comparison of Central and Local Government Objectives
Authors: Zhuang Lingwei , Wen Zuomin , Lin Mingxin , Wang Sijia , Hu Xiaoxiao
Published: July 2024

To address the complexities of national park management within China, this study investigated the evolutionary game between central and local governments in the context of Sanjiangyuan National Park, to explore strategic behavior and goal displacement issues. This research dissected the interplay and strategy evolution between governmental levels, considering the diverse interests, policy interpretations, and resource allocations that often lead to strategic misalignments. Employing an evolutionary game theory framework, we integrated a literature review and numerical simulations to delineate the dynamics of central–local governmental interactions. Our results underscore the pivotal role of strategic alignment in ensuring ecological conservation and socioeconomic development. The findings reveal that under certain conditions, characterized by minimization of rent-seeking behavior, cost-effective management, and risk mitigation, an evolutionarily stable strategy promoting optimal park management can emerge. This study concludes that a cooperative framework, underpinned by aligned incentives and strategic coherence between governmental levels, is critical for sustainable management of national parks. It contributes to understanding of governance models in national parks, offers insights into policy formulation and implementation within the ongoing environmental reform initiatives in China, reveals the behavioral strategies within national park management systems, and supports policy recommendations for enhancing governance quality and management efficiency.
Emission Control in Expressway Systems: Vehicle Emission Inventory and Policy Scenario Analysis
Authors: Chen Jingxu , Chen Junyi , Chen Dawei , Shen Xiuyu
Published: July 2024

Expressway systems play a vital role in facilitating intercity travels for both passengers and freights, which are also a significant source of vehicle emissions within the transportation sector. This study investigates vehicle emissions from expressway systems using the COPERT model to develop multi-year emission inventories for different pollutants, covering the past and future trends from 2005 to 2030. Thereinto, an integrated SARIMA-SVR method is designed to portray the temporal variation of vehicle population, and the possible future trends of expressway vehicle emissions are predicted through policy scenario analysis. The Jiang–Zhe–Hu Region of China is taken as the case study to analyze emission control in expressway systems. The results indicate that (1) carbon monoxide (CO) and volatile organic compounds (VOCs) present a general upward trend primarily originating from passenger vehicles, while nitrogen oxides (NOx) and inhalable particles (PM) display a slowing upward trend with fluctuations mainly sourcing from freight vehicles; (2) vehicle population constraint is an effective emission control policy, but upgrading the medium- and long-haul transportation structure is necessary to meet the continuous growth of intercity trips. Expressway vehicle emission reduction effectiveness can be further enhanced by curtailing the update frequency of emission standards, along with the scrapping of high-emission vehicles.
Innovative Approach for Human Semen Quality Assessment Based on Volatilomics
Authors: Capone Simonetta , Forleo Angiola , Radogna Antonio Vincenzo , Longo Valentina , My Giulia , Genga Alessandra , Ferramosca Alessandra , Grassi Giuseppe , Casino Flavio , Siciliano Pietro , Notari Tiziana , Pappalardo Sebastiana , Piscopo Marina , Montano Luigi
Published: July 2024

The volatilome profile of some biofluids (blood, urine, and human semen) identified by Solid-Phase Microextraction–Gas Chromatography/Mass Spectrometry (SPME-GC/MS) and collected from young men living in two high-pollution areas in Italy, i.e., Land of Fires and Valley of Sacco River, have been coupled to sperm parameters obtained by spermiogram analysis to build general multiple regression models. Panels of volatile organic compounds (VOCs) have been selected to optimize the models and used as predictive variables to estimate the different sperm quality parameters (sperm cell concentration, total and progressive motility/immotile cells, total/head/neck/tail morphology anomalies, semen round cell concentration). The results of the multiple linear regression models based on the different subgroups of data joining VOCs from one/two or three biofluids have been compared. Surprisingly, the models based on blood and urine VOCs have allowed an excellent estimate of spermiogram values, paving the way towards a new method of indirect evaluation of semen quality and preventive screening. The significance of VOCs in terms of toxicity and dangerousness was discussed with the support of chemical databases available online.
Interaction between SARS-CoV PBM and Cellular PDZ Domains Leading to Virus Virulence
Authors: Honrubia Jose M. , Valverde Jose R. , Muñoz-Santos Diego , Ripoll-Gómez Jorge , de la Blanca Nuria , Izquierdo Jorge , Villarejo-Torres Marta , Marchena-Pasero Ana , Rueda-Huélamo María , Nombela Ivan , Ruiz-Yuste Mercedes , Zuñiga Sonia , Sola Isabel , Enjuanes Luis
Published: July 2024

The interaction between SARS-CoV PDZ-binding motifs (PBMs) and cellular PDZs is responsible for virus virulence. The PBM sequence present in the 3a and envelope (E) proteins of SARS-CoV can potentially bind to over 400 cellular proteins containing PDZ domains. The role of SARS-CoV 3a and E proteins was studied. SARS-CoVs, in which 3a-PBM and E-PMB have been deleted (3a-PBM-/E-PBM-), reduced their titer around one logarithmic unit but still were viable. In addition, the absence of the E-PBM and the replacement of 3a-PBM with that of E did not allow the rescue of SARS-CoV. E protein PBM was necessary for virulence, activating p38-MAPK through the interaction with Syntenin-1 PDZ domain. However, the presence or absence of the homologous motif in the 3a protein, which does not bind to Syntenin-1, did not affect virus pathogenicity. Mutagenesis analysis and in silico modeling were performed to study the extension of the PBM of the SARS-CoV E protein. Alanine and glycine scanning was performed revealing a pair of amino acids necessary for optimum virus replication. The binding of E protein with the PDZ2 domain of the Syntenin-1 homodimer induced conformational changes in both PDZ domains 1 and 2 of the dimer.
A One Health Perspective on Camel Meat Hygiene and Zoonoses: Insights from a Decade of Research in the Middle East
Authors: Mohamed Mohamed-Yousif Ibrahim , Lakshmi Glindya Bhagya , Sodagari Hamidreza , Habib Ihab
Published: July 2024

The purpose of this review was to investigatethe microbial and chemical safety of camel meat and the zoonotic diseases associated with camels in the Middle East over the past decade, emphasizing the crucial role of a One Health approach. By systematically analyzing recent studies (in the past decade, from 2014), we assessed pathogen prevalence, contamination with heavy metals and pesticide residues, and the impact of zoonotic diseases like Middle East respiratory syndrome coronavirus (MERS-CoV). The findings revealed significant variability in pathogen prevalence, with the frequent detection of traditional foodborne pathogens (e.g., Salmonella and E. coli O157), as well as antibiotic-resistant strains like methicillin-resistant and vancomycin-resistant Staphylococcus aureus and extended-spectrum β-lactamase (ESBL)-producing E. coli, underscoring the need for stringent antibiotic use policies and robust food safety measures. Additionally, the review highlighted substantial contamination of camel meat with heavy metals and pesticide residues, posing significant public health concerns that necessitate stringent regulatory measures and regular monitoring. The persistent occurrence of zoonotic diseases, particularly MERS-CoV, along with other threats like trypanosomiasis, brucellosis, and Clostridium perfringens, emphasizes the importance of strengthening ongoing surveillance. Enhancing investment in diagnostic infrastructures, training programs, and planning capabilities is crucial to address these issues at the camel–human interface in the Middle East. Adopting a One Health perspective is vital to ensuring the safety and quality of camel meat and managing zoonotic risks effectively to ultimately safeguard public health and promote sustainable livestock practices.
Assessing the Relative and Combined Effect of Climate and Land Use on Water-Related Ecosystem Services in the Yangtze River Economic Belt, China
Authors: Wu Yifan , Yao Minglei , Tang Yangbo , Li Wei , Yu Tao , Ma Wenlue , Geng Xiaojun
Published: July 2024

The ecosystem service (ES) is essential for residents’ health and well-being. The ecosystem service value (ESV) is one of the measures to scientifically quantify the wealth of ESs. However, climate and human activities intensely affect the sustainability of ESs. Therefore, knowing the relative and combined effects of climate and human activities on ESs and ESV can be crucial. This study selects the Yangtze River Economic Belt (YREB) as the study area to detect how climate and human activities affected the ES and ESV changes during 2001–2020, including net primary productivity, water yield, soil retention, water purification, and integrated ESV. The results show that the southern YREB has relatively higher ESs than the northern YREB, except for the NDR-P, which is mainly located in the urban agglomeration area. The general ranking for the ESV of different provinces in the YREB is sequenced from higher to lower as Sichuan, Yunnan, Hunan, Jiangxi, Guizhou, Hubei, Zhejiang, Anhui, Jiangsu, Chongqing, and Shanghai. Specifically, the ESV of Sichuan is the highest at about 972 billion yuan (133.57 billion USD), while the lowest ESV has been discovered in Shanghai at approximately 0.25 billion yuan (0.03 billion USD). It can be noticed that the regions where climate is the major influencing factor for ESs are concentrated upstream of the YREB, and human activities mainly influence ESs in highly urbanized areas. Furthermore, climate and human activities account for the highest proportion (86%) of synergistic effects for ESV in Yunnan. In contrast, Jiangsu, Zhejiang, and Shanghai accounted for the lowest proportions, at 18%, 26%, and 31%, respectively. This study may provide crucial insights into how ESs and ESV in the YREB have changed during the study period to inform policymakers, drawing more attention to the inhibitory and synergistic effects arising from the interaction between climate and human activities, to make more reliable decisions on adapting to climate crises in the future.
Dynamic Response Characteristics of Rotating and Fixed Components of the Kaplan Turbine under Low and Medium Heads
Authors: Luo Hongyun , Wang Guiyu , Chen Xiaobin , Liu Chengming , Zhou Lingjiu , Wang Zhengwei
Published: July 2024

The vibration of large Kaplan turbines has always been one of the key research issues of turbines. Affected by the load and head of the power station, the Kaplan turbine will operate under medium and low heads, and the components will vibrate violently, seriously threatening the stable operation of the unit. Compared with other types of turbines, the runner structure of the Kaplan turbine is more complex. Therefore, in addition to the fixed components, the dynamic response characteristics of the rotating components are also be the focus of this study. In this paper, four operating points under high, medium and low heads are selected. The unsteady flow field and fluid–structure interaction are calculated. The modal and dynamic stress characteristics of the fixed components (bottom ring, head cover and support cover) and the rotating components (blades, runner body and main shaft) are analyzed. The results show that the location of the stress concentration of fixed components under low heads changes significantly, and the stress fluctuates greatly due to the influence of the stay vanes. The rotating components are more affected by the rotation of the runner under low heads, and the displacement and stress fluctuations of the rotating structure are significantly greater than those of medium and high heads. The pressure fluctuations in the vaneless area and draft tube cause some low-frequency excitation. The stress fluctuations of rotating components under low heads are much greater than those of the fixed components. This shows that the head has a greater impact on the rotating components, which is more likely to cause damage to the rotating components, seriously threatening the stable operation of the unit.
Development-Ecological Protection Conflicts and Coordination at West Taijinel Salt Lake
Authors: Zha Xizhuoma , Jia Shaofeng
Published: July 2024

The Qaidam Basin in China, recognized for its copious salt lake mineral resources, holds immense significance for the nation’s sustenance and industrial progression. However, the escalating exploitation of these resources has led to substantial conflicts between economic pursuits and ecological conservation. Ongoing activities like water diversion for flood control and brine extraction are hindering the preservation of the lake’s natural ecosystem. This study examines the challenges of salt lake exploitation and ecological conservation, proposing measures for environmental stewardship. These include delineating the responsibilities of production zones designated for salt lake development; advocating the comprehensive harnessing of flood resources; and establishing a collaborative platform for integrating ecological data among government entities, regulatory bodies, and private enterprises. This research aims to lay the groundwork for ecological management policies for salt lakes in the Qaidam region to balance the development of a top-tier salt lake production base with environmental preservation.
Solar-Powered Desalination as a Sustainable Long-Term Solution for the Water Scarcity Problem: Case Studies in Portugal
Authors: Apolinário Rita , Castro Rui
Published: July 2024

The challenge of global water scarcity, exacerbated by population growth, pollution, and uneven resource distribution, demands innovative solutions. Seawater desalination, particularly Reverse Osmosis (RO) desalination technology, offers a promising remedy due to its efficiency, economic attractiveness, and enduring durability. This study explores the potential of solar-powered desalination to replace grid-imported electricity as a cost-effective solution to water scarcity, emphasizing economic and environmental aspects. We delve into the economic viability of desalination by developing a model that considers desalination capacity, input electricity prices, and specific energy consumption. Applying this model to case studies in Portugal (Porto Santo Island in the Madeira Archipelago and Algarve in the southern mainland) demonstrates that integrating photovoltaic (PV) solar energy systems to supply the electricity required in the desalination process can reduce the unit production costs of desalinated water by about 33%. The obtained unit production cost of desalinated water using solar PV input is lower than current water tariffs, underscoring the economic feasibility of this approach. The proposed solution is in line with the United Nations Sustainable Development Goals (SDGs), contributing to Goal 6 (Clean Water and Sanitation), Goal 7 (Affordable and Clean Energy), and Goal 8 (Decent Work and Economic Growth).