bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessing Global Waste Management: Alternatives to Landfilling in Different Waste Streams—A Scoping Review
Authors: Karimi Nima
Published: September 2023

This scoping review examines global strategies and enterprises for sustainable solid waste management, with a focus on alternative landfilling approaches. The study collected and analyzed a significant number of documents from different regions, revealing Asia as the major contributor (for the collected documents) (48.7%), followed by North America (24.3%) and Europe (15.8%). Recycling emerged as the most effective alternative waste treatment method, representing 52.3% of the documented approaches, with industrial recycling (22.6%) and residential/nonresidential recycling (20.2%) as prominent categories. Food waste was a significant concern across regions, constituting 21.4% of the collected documents. Composting was widely adopted (15.4%) due to its simplicity and benefits for gardening and soil improvement. Other methods like biogas extraction, reusing, raising awareness, incinerating, redistributing, reducing, and fermentation accounted for 13.1% cumulatively. The study highlights the need for adopted waste management solutions based on regional challenges and successful practices. Promoting recycling infrastructure, composting, and waste reduction approaches are crucial to achieving sustainable waste management aligned with SDGs. Collaboration and knowledge sharing between regions are essential to improve inefficient waste management mechanisms. Integrating the findings into policymaking and industry practices can lead to a more sustainable future with reduced environmental impact.
A Retrospection on Mercury Contamination, Bioaccumulation, and Toxicity in Diverse Environments: Current Insights and Future Prospects
Authors: Kumar Vinay , Umesh Mridul , Shanmugam Manoj Kumar , Chakraborty Pritha , Duhan Lucky , Gummadi Sathyanarayana N. , Pasrija Ritu , Jayaraj Iyyappan , Dasarahally Huligowda Lohith Kumar
Published: September 2023

Owing to various industrial applications of mercury (Hg), its release into the environment at high concentration is becoming a great threat to living organisms on a global scale. Human exposure to Hg is greatly correlated with contamination in the food chain through cereal crops and sea foods. Since Hg is a non-essential component and does not possess a biological role and exhibits carcinogenic and genotoxic behaviour, biomonitoring with a focus on biomagnification of higher living animals and plants is the need of the hour. This review traces the plausible relationship between Hg concentration, chemical form, exposure, bioavailability, bioaccumulation, distribution, and ecotoxicology. The toxicity with molecular mechanisms, oxidative stress (OS), protein alteration, genomic change, and enzymatic disruptions are discussed. In addition, this review also elaborates advanced strategies for reducing Hg contamination such as algal and phytoremediation, biochar application, catalytical oxidation, and immobilization. Furthermore, there are challenges to overcome and future perspectives considering Hg concentrations, biomarkers, and identification through the nature of exposures are recommended.
The Relationship between the Evaluation of Public Transport Services and Travel-Based CO2 Emissions from Private Transport Modes in Regional and Metropolitan Areas in Japan
Authors: Pradhan Shreyas , Ujihara Takehito , Hashimoto Seiji
Published: September 2023

Promoting public transport use is expected to contribute to reducing CO2 emissions in the transport sector. Using Okayama City and Central Tokyo as representative case studies of regional and metropolitan areas in Japan, this study examines the impact of the evaluation of the ‘hard’ and ‘soft’ attributes of rail and bus services on the overall evaluation. This study then explores the relationship between the overall evaluation and usage frequency of rail and bus services, as well as the relationship between the usage frequency and travel-based CO2 emissions from private transport modes. Furthermore, this study investigates whether the emissions cause differences in the evaluation of the ‘hard’ and ‘soft’ attributes of public transport services. The findings suggest prioritising an improvement in ‘hard’ rather than ‘soft’ attributes in order to reduce emissions through the use of public transport in regional areas. However, in metropolitan areas, no relationship was found between the evaluation of public transport services and emissions, presumably because of the lower ownership rate of private cars that residents can use freely and the markedly higher level of rail and bus services. This study provides a methodological reference for analysing the potential to reduce travel-based emissions from private transport modes by enhancing public transport service contents.
Tracing and Determining the Duration of Illegal Sand Mining in Specific River Channels in the Limpopo Province
Authors: Rapholo Maropene Tebello Dinah , Rampedi Isaac Tebogo , Sengani Fhatuwani
Published: September 2023

Artisanal and Small-scale river sand mining is one of the upcoming activities associated with the environmental crisis concerning the water ecosystem. However, the determination of the duration in which illegal sand mining has occurred, and the future prediction on the extent of river sand mining is not well-established in most of the world. This study aimed to assess the extent of river sand mining activities across some of the catchments in Limpopo province, South Africa and understand the sustainable extraction of sand resources. This was followed by the determination of when sand mining activities commenced in each of the individual catchments. Thus, remote sensing was applied to predict the extent of river sand mining from the year 1992 to 2022, and statistical prediction models were utilised to predict the extent of sand mining for the next 10 years. The results of the study suggest that most of the catchments started to experience illegal sand mining activities from the year 1992, though the extraction was relatively low. Equally, a decrease in vegetation coverage across the river system has been evidenced, which also suggests that the extraction of sand and gravel has been elevated from the year 2010. In terms of the prediction model, the Turfloop River system was predicted to experience a large extraction ratio in the coming 10 years, with about 92.415 ha of land expected to be affected. Meanwhile, the Molototsi River system was denoted to be the least affected river system, with a reduced extraction ratio of about 6.57 ha expected in the next 10 years’ time.
Modeling of Artificial Intelligence-Based Automated Climate Control with Energy Consumption Using Optimal Ensemble Learning on a Pixel Non-Uniformity Metro System
Authors: Justin Shekaina , Saleh Wafaa , Lashin Maha M. A. , Albalawi Hind Mohammed
Published: September 2023

Climate control in a pixel non-uniformity metro system includes regulating the air, humidity, and temperature quality within metro trains and stations to ensure passenger comfort and safety. The climate control system in a PNU metro system combines intelligent algorithms, energy-efficient practices, and advanced technologies to make a healthy and comfortable environment for passengers while reducing energy consumption. The proposed an automated climate control using an improved salp swarm algorithm with an optimal ensemble learning technique examines the underlying factors, including indoor air temperature, wind direction, indoor air relative humidity, light sensor 1 (wavelength), return air relative humidity, supply air temperature, wind speed, supply air relative humidity, airflow rate, and return air temperature. Moreover, this new proposed technique applies ISSA to elect an optimal set of features. Then, the climate control process takes place using an ensemble learning approach comprising long short-term memory, gated recurrent unit, and recurrent neural network. Lastly, the Harris hawks optimization algorithm can be employed to adjust the hyperparameters related to the ensemble learning models. The extensive results demonstrated the supremacy of the proposed algorithms over other approaches to the climate control process on PNU metro systems.
Heterogeneity Analysis of Spatio-Temporal Distribution of Vegetation Cover in Two-Tider Administrative Regions of China
Authors: Shang Guoxiu , Wang Xiaogang , Li Yun , Han Qi , He Wei , Chen Kaixiao
Published: September 2023

Vegetation cover is a crucial component of regional ecological environments that plays a vital role in maintaining ecosystem balance. This investigation utilized Google Earth Engine and MODIS NDVI products to examine the spatiotemporal heterogeneity of regional vegetation coverage based on the multi-year average NDVI in China. Using the multi-year average NDVI, multi-year change trend slope, coefficient of variation, and Hurst exponent, the spatial and temporal heterogeneity of provincial and prefectural administrative regions were quantified. The results indicated an upward trend in vegetation coverage from 2000 to 2021 at both provincial and prefectural levels, with growth rates of 0.032/10a and 0.03/10a, respectively. Moreover, the multi-year average NDVI significantly correlated with regional precipitation. Notably, vegetation growth was fastest in the Loess Plateau, while degradation was observed in southern Jiangsu and northern Zhejiang. Additionally, the degree of vegetation cover change in Ningxia and Macau was particularly prominent. These findings support the effectiveness of the Loess Plateau greening project and highlight the potential cost of economic and population growth on the ecosystem in eastern and southeastern coastal areas, where local vegetation degradation occurs. This study can serve as a valuable reference for ecosystem restoration and developmental planning at the administrative regional level, with the goal of enhancing vegetation management and conservation efforts in China.
Spatial–Temporal Characteristics and Influencing Factors on Carbon Emissions from Land Use in Suzhou, the World’s Largest Industrial City in China
Authors: Han Yue , Ge Xiaosan
Published: September 2023

Exploring carbon emissions in Suzhou, a city with a significant heavy industry presence, and understanding the factors that influence these emissions are crucial in achieving China’s dual-carbon goals within the framework of global climate governance. This study utilized land use data and statistical data from 2008 to 2020 in Suzhou. The carbon emission coefficient method was employed to calculate carbon emissions, while GIS technology was used to analyze their temporal and spatial distribution, as well as carbon emission risk. Additionally, the LMDI model was applied to investigate the contribution of influencing factors and TAPIO was used to analyze the decoupling relationship between the main influencing factors and carbon emissions. The study yielded the following findings: (1) From 2008 to 2020, land use changes in all regions of Suzhou are obvious, and there are mutual transformations among different land types. (2) The overall carbon emission in Suzhou showed an upward trend, with a spatial distribution characterized by higher emissions in the northern regions and lower emissions in the southern regions. (3) The risk and pressure index of carbon emission in all regions of Suzhou are too large, and the amount of carbon emission and carbon absorption is seriously out of balance, resulting in an overall carbon imbalance. (4) Among the influencing factors on land use carbon emissions in Suzhou, energy intensity exerted the strongest negative effect, and economic growth showed the strongest positive effect. (5) Decoupling analysis showed that economic growth and carbon emissions are generally shifting towards a strong decoupling and, except for Zhangjiagang, other regions have a good development model. Based on the research findings, this paper proposes specific suggestions for reducing carbon emissions, aiming to provide actionable recommendations for Suzhou and other urban areas in achieving low-carbon and environmentally sustainable cities.
Correction: Raivio et al. Caring for Worldviews in Early Childhood Education: Theoretical and Analytical Tool for Socially Sustainable Communities of Care. Sustainability 2022, 14, 3815
Authors: Raivio Magdalena , Skaremyr Ellinor , Kuusisto Arniika
Published: September 2023

The authors would like to make the following corrections to the published paper [...]
Research on the Progress of Agricultural Non-Point Source Pollution Management in China: A Review
Authors: Lu Yanrong , Wang Chen , Yang Rongjin , Sun Meiying , Zhang Le , Zhang Yuying , Li Xiuhong
Published: September 2023

In the 1980s, China began to recognize the gravity of the problem of non-point agricultural source pollution and conduct research on it. Agricultural non-point source pollution in China, on the other hand, differs from foreign agricultural non-point source pollution and industrial point source pollution. Because the features of agricultural non-point source pollution are complicated, it is critical to investigate a whole-chain management policy system appropriate for China’s agricultural pattern. Based on the current situation of agricultural non-point source pollution in China, this study summarizes the four stages of agricultural non-point source pollution prevention and control policies, namely the discovery stage with macro policies as the main focus, the exploration stage with single research indicators, the initial systematic strengthening stage, and the focused stage with targeted characteristics. Simultaneously, it examined the technological approaches that are suitable for China’s national circumstances and have been investigated by relying on international experience in present-day Chinese management. However, there are still some problems and challenges in agricultural non-point source pollution management policies, such as a lack of non-point source information support, a lack of coordination between different departments, a lack of support in measurement and retroactive calculation and treatment, a lack of an in-depth concept of zoning and classification, a lack of policy, an institutional system, and insufficient capital investment. Based on these problems and combining them with Green Agriculture, Beautiful China, and other goals, this paper puts forward suggestions to strengthen the policy data support of the agricultural non-point source pollution management system, enhance the research and development of the law of pollutant migration and transformation, encourage the innovation of low-cost and high-benefit treatment technology, improve the construction of the management system, strengthen the collaboration of departments, increase the investment of funds, and make other suggestions so as to promote the treatment of agricultural non-point source pollution with high quality and efficiency.
MMC-HVDC High-Frequency Resonance Suppression Strategy Based on Multi-Band Band-Stop Filters
Authors: Cui Tinghe , Wang Weiqing , Wang Haiyun
Published: September 2023

Renewable energy generation is a manifestation of global economic and societal advancement and serves as a fundamental assurance for humanity’s pursuit of sustainable development. However, recent years have witnessed several instances of high-frequency resonance events in high-voltage direct current (HVDC) transmission systems based on modular multilevel converters (MMC), which have resulted in converter station tripping and significant repercussions on the alternating current (AC) grid. This paper addresses the mid-to-high frequency resonance issues prevalent in flexible DC transmission systems employing modular multilevel converters (MMC-HVDC). To tackle these concerns, an impedance model for MMC’s AC side is established. Utilizing impedance analysis, the essential factors contributing to the negative damping characteristics of MMC are identified as delay and voltage feedforward loops, predominantly causing negative damping in the frequency range exceeding 400 Hz. In response, a suppression strategy is proposed, involving the incorporation of a multi-band stop filter and virtual impedance. This strategy ensures that within the 0–2000 Hz frequency range, only the impedance phase within 230–430 Hz slightly surpasses 90°. Consequently, the phase difference between MMC’s positive-sequence impedance and the AC system impedance is reduced from 222° to 174.7°, thus guaranteeing secure grid operation. Lastly, the accuracy and effectiveness of the theoretical analysis and suppression methodology are verified through the development of an electromagnetic transient model in MATLAB/Simulink, considering delay fluctuations of ±10%.
Study on the Basic Mechanical Properties and Discrete Element Method Simulation of Permeable Concrete
Authors: Xiao Qidan , Hu Xiumin , Li Xiaole , Zhang Guanguan , Zhao Jun
Published: September 2023

Permeable concrete pavement material has many voids and a good water permeability, which can reduce surface runoff and alleviate the problem of urban water logging. It also has the functions of acting as a supplementary source of groundwater, purifying water, bodies reducing the urban heat island effect, reducing road noise, and so on. It is an effective solution for urban infrastructures. However, at the same time, because it has a large number of pores, this also affects the strength of permeable concrete. The main factors affecting permeable concrete are particle size and the shape of the aggregate, the content of the cement paste and aggregate, the compaction degree of the mixture, and so on. In this study, the single-factor test method was used to study the effects of aggregate size, slurry-to-bone ratio and loose paving coefficient on the basic mechanical properties and permeability of permeable concrete. Here, the numerical model for permeable concrete is established by using the particle flow discrete element (Particle Flow Code (PFC)modeling method, and a numerical simulation test is carried out. It can be seen from the test results that the permeability coefficient of 50% 5–10 mm + 50% 10–15 mm mixed aggregate permeable concrete is slightly lower than that of 5–10 mm and 10–15 mm single-size aggregate, but has a higher compressive and splitting tensile strength. With the increase in paste-to-bone ratio, the permeability coefficient of permeable concrete decreases, and the compressive strength increases. The loose paving coefficient has a significant effect on the mechanics and permeability of permeable concrete with the increase in the loose paving coefficient, the water permeability decreases and the compressive strength increases. The numerical simulation results show that under the condition that the loose paving coefficient is 1.10 and the slurry-to-bone ratio is 0.5, compared with the experimental results, the error of the numerical simulation results of the compression test is less than 3%. The reliability of the simulation is verified. The discrete element modeling method in this study can be used to simulate the shape of the aggregate in permeable concrete, and the numerical model can effectively simulate the crack development and failure form of permeable concrete in compression tests.
Mixing Renewable Energy with Pumped Hydropower Storage: Design Optimization under Uncertainty and Other Challenges
Authors: Zisos Athanasios , Sakki Georgia-Konstantina , Efstratiadis Andreas
Published: September 2023

Hybrid renewable energy systems, complemented by pumped hydropower storage, have become increasingly popular amidst the increase in renewable energy penetration. Such configurations are even more prosperous in remote regions that are typically not connected to the mainland power grid, where the energy independence challenge intensifies. This research focuses on the design of such systems from the perspective of establishing an optimal mix of renewable sources that takes advantage of their complementarities and synergies, combined with the versatility of pumped hydropower storage. However, this design is subject to substantial complexities, due to the multiple objectives and constraints to fulfill, on the one hand, and the inherent uncertainties, on the other, which span over all the underlying processes, i.e., external and internal. In this vein, we utilize a proposed hybrid renewable energy system layout for the Aegean Island of Sifnos, Greece, to develop and evaluate a comprehensive simulation-optimization scheme in deterministic and, eventually, stochastic settings, revealing the design problem under the umbrella of uncertainty. In particular, we account for three major uncertain elements, namely, wind velocity (natural process), energy demand (anthropogenic process), and wind-to-power conversion (internal process, expressed in terms of a probabilistic power curve). Emphasis is also given to the decision-making procedure regarding the system’s key design parameters (reservoir size and solar power capacity), which is achieved by thoroughly interpreting the uncertainty-aware optimization outcomes. Finally, since the proposed pumped hydropower storage uses the sea as the lower reservoir, additional technical challenges are addressed.
Performance Evaluation of Asphalt Mixtures Containing Different Proportions of Alternative Materials
Authors: Khorshidi Meisam , Goli Ahmad , Orešković Marko , Khayambashi Kamiar , Ameri Mahmoud
Published: September 2023

With the increasing scarcity and cost of virgin materials for asphalt mixtures, the exploration of alternative components has intensified. Reclaimed asphalt pavement (RAP), crumb rubber (CR), steel slag (SS), and waste engine oil (WEO) have emerged as promising alternatives. Individually, RAP enhances rutting resistance but may compromise cracking tolerance; CR boosts cracking resistance; WEO affects cracking and rutting differently; and SS can influence moisture sensitivity. However, their combined impacts on asphalt performance, specifically on moisture damage, rutting, and cracking resistance, remain underexplored. In this study, 44 mixtures were assessed with varying RAP (0–75%), WEO (0–15%), and CR (0–15%) contents, alongside a constant SS aggregate (0% or 20%). The results indicate that specific combinations of these alternative materials can satisfy all performance thresholds for rutting, cracking, and moisture damage. To pinpoint ranges of optimal material contents for different high-traffic scenarios, prediction models were crafted using techniques like feed-forward neural network (FNN), generalized linear model (GLM), support vector regression (SVM), and Gaussian process regression (GPR). Among these, GPR demonstrated superior efficacy, effectively identifying regions of satisfactory performance.
Decision Support Frameworks in Solid Waste Management: A Systematic Review of Multi-Criteria Decision-Making with Sustainability and Social Indicators
Authors: Gutierrez-Lopez Jenny , McGarvey Ronald G. , Costello Christine , Hall Damon M.
Published: September 2023

Waste management is a critical sector that needs to co-ordinate its activities with outcomes that impact society. Multi-criteria decision-making methods for waste management have been widely considered using environmental and economic criteria. With the development of new social regulations and concerns, sustainable waste management needs to additionally target socially acceptable practices. Despite the need to aid solid waste management decision-makers in contemplating the three pillars of sustainability, a limited inclusion of social impact has been found in the multi-objective decision-making literature. This study presents a systematic literature review of multi-criteria decision-making methods in solid waste management. The purpose of this study is threefold. (1) Emphasize the application of multi-objective decision-making methods, summarizing the models that have been used and their applications; (2) provide insights into the quantification of social aspects and their inclusion in decision-making methods, providing a list of social indicators collected from the reviewed studies; (3) offer an analysis of stakeholders’ involvement in waste management. From the articles investigated, one can observe the importance of understanding the local context in which the waste management system is located and the necessity of community consultation to recognize the potential challenges and improvements to solid waste management systems. Consequently, the involvement of stakeholders is crucial during the quantification process of social indicators. In alignment with the findings and needs raised by this review, a methodological approach is suggested for integrating optimization, social aspects, and stakeholders under a waste management context.
Application of Internet of Things (IoT) Technologies in Green Stormwater Infrastructure (GSI): A Bibliometric Review
Authors: Chen Tong , Wang Mo , Su Jin , Ikram Rana Muhammad Adnan , Li Jianjun
Published: September 2023

This bibliometric review elucidates the emerging intersection of Internet of Things (IoT) technologies and Green Stormwater Infrastructure (GSI), demonstrating the potential to reshape urban stormwater management. The study analyzes a steadily increasing corpus of literature since 2013, pointing out considerable international collaboration. Prominent contributions originate from the United States, Canada, Italy, China, and Australia, underscoring the global acknowledgement of the potential of IoT-enhanced GSI. Diverse GSI applications such as green roofs, smart rain barrels, bioretention systems, and stormwater detention ponds have demonstrated enhanced efficiency and real-time control with IoT integration. However, existing literature reveals several challenges, notably the requirement of advanced monitoring, the development of predictive optimization strategies, and extensive scalability. Comprehensive cost–benefit analyses are also critical for the widespread acceptance of IoT-integrated GSI. Current research addresses these challenges by exploring innovative strategies such as microbial-fuel-cell-powered soil moisture sensors and large-scale RTC bioretention systems. Emphasis is also on the need for security measures against potential digital threats. Future research needs to focus on real-time data-based monitoring plans, model validation, continuous optimization, and supportive policy frameworks. As the world confronts urban development, climate change, and aging infrastructure, IoT and GSI synergism presents a promising solution for effective stormwater management and enhancement of cultural ecosystem services. Continued exploration in this promising domain is crucial to pave the way for smarter, greener urban environments.
Urban Economic Efficiency, Environmental Factors, and Digital Finance: Impacts on Sustainable Development in Chinese Cities
Authors: Yuan Yuling , Li Dukangqi
Published: September 2023

This study investigates the potential of digital finance to mitigate the environmental impact of economic development. Utilizing panel data from 290 Chinese cities between 2011 and 2019, we employ a two-way fixed effects model to control for unobservable city characteristics and time-invariant macro factors. Our findings reveal that cities with higher proportions of value-added tax and secondary industries (mainly for manufacturing) tend to experience increased air pollution. Conversely, cities characterized by higher economic efficiency exhibit better air quality, underscoring the significance of prioritizing technology-intensive sectors during economic development. Pollution control technologies, such as centralized wastewater treatment systems and harmless treatment systems for household waste, also play positive roles. Moreover, technological and educational investments correlate with increased urban green coverage and lower air pollution, highlighting the pivotal role of technology development and residents’ literacy in fostering sustainable practices. Although we initially observed a positive association between the index of digital financial technology and air pollution, which could be attributed to the influence of economic growth, our study employs instrumental variable regression to unveil their true correlation. The results suggest the application of digital financial technology may enhance environmental awareness, contributing to the mitigation of air pollution.
Research on Urban Sustainability Indicators Based on Urban Grain: A Case Study in Jinan, China
Authors: Zhao Jilong , Hao Xinran , Yang Yang
Published: September 2023

As a concept to describe the characteristics of urban spatial forms, urban grain emphasizes the size of urban parcels. Fine grain and coarse grain are considered essential attributes. Fine grain plays a crucial role in promoting the adaptability of urban development, improving urban vitality, and helping achieve sustainable urban development. Current research on urban grain is scattered and difficult to apply to solve practical urban problems. Therefore, this paper aims to identify the spatial indicators that affect the urban grain, to solve urban problems by adjusting spatial indicators. It contains significant suggestions for improving urban design theory and promoting sustainable urban development. This study primarily uses the comparative method to identify spatial indicators influencing urban grain by comparing coarse- and fine-grain study areas. This study screens relevant spatial indicators (building density, road network density, age of housing structures, building façade width along streets, number of entrances and exits along streets, and function mixture) affecting urban grain through a review and measurements, and it visualizes the representation of spatial indicators using the grid method, determining the correlation between spatial indicators and urban grain. The results show that all six indicators have an impact on urban grain.
Assessing Farmers’ Willingness to Pay for Adopting Sustainable Corn Traits: A Choice Experiment in Italy
Authors: Barriviera Anna , Bosco Diego , Daniotti Sara , Pozzi Carlo Massimo , Saija Maria Elena , Re Ilaria
Published: September 2023

Corn is a major staple crop known for its nutritional value and versatility in industrial applications. Climate change threatens sustainable production, making understanding farmers’ preferences and willingness to pay (WTP) for desirable traits crucial in seed selection. This study employs the Choice Experiment (CE) to assess the importance of key attributes, including yield potential, disease resistance, yield under water stress conditions, and price. The evaluation was conducted in Italy on a sample of 31 producers in the Lombardy region, where corn cultivation occupies 50% of the arable land, and the national annual volume equals about 11 million tons. Results indicate that yield under water stress conditions is the most critical attribute reflecting the need for high productivity to cope with yield fluctuations and production costs induced by climate change. The significance of this study lies in its ability to provide insights into farmers’ preferences and their priorities for maize seed attributes, which in turn offer invaluable decision support to seed breeding programs. This contribution not only promotes the development of improved corn traits and varieties for sustainable production and global food security but also guides resilient investment decisions and effective marketing strategies.
Epigeic Carabids (Coleoptera, Carabidae) as Bioindicators in Different Variants of Scots Pine Regeneration: Implication for Forest Landscape Management
Authors: Kosewska Agnieszka , Kędzior Renata , Nietupski Mariusz , Borkowski Jakub
Published: September 2023

Maintaining biodiversity is one of the factors determining the proper functioning of ecosystems, especially those with high human impact. Ground beetles, as bioindicators, are particularly valuable in understanding ecosystem responses and sustainability in forest and landscape management. Focusing on the regeneration of pine forests, this study aimed to describe ground beetle assemblages on Scots pine natural and artificial regeneration in northeastern Poland. This study was conducted between 2016 and 2018. Pitfall traps were set up for catching epigeic carabids on previously prepared research plots designated for natural and artificial pine regeneration. The research areas included three variants: N—natural pine regeneration, plots without soil preparation; NP—natural pine regeneration with traditional soil preparation by ploughing; and A—artificial pine regeneration with ploughing. Four plots as replicants were selected in each experimental variant, with six pitfall traps in the transects running through the centre of each study plot. In each year of the study, 11 samples were collected from each plot; overall, 33 samples per plot were collected during the three years. As a result of this study, 26,654 ground beetle individuals belonging to 89 species were caught during the three-year observation. Natural regeneration without soil preparation (N) was the most favourable in terms of the occurrence of stabilised assemblages of ground beetles. However, the remaining methods of pine regeneration, on a multi-annual scale (2016–2018), contributed to the increase in the number of ground beetles but also provided high variability in assemblage composition, diversity indices, and life-history traits. Thus, in the early stage of pine regeneration, each of the examined variants of pine regeneration can be used without fear of causing damage to carabid populations. However, further studies are required to investigate the effect of different pine regeneration types on carabid beetle assemblages over a longer period.
The Impact of Environmental Regulation on the Upgrading of Urban Industrial Structure: A Quasi-Natural Experiment Based on the Two Control Zones Policy
Authors: Liu Yongfu , Guan Shuai
Published: September 2023

This paper considers the two control zones policy implemented in 1998 in China as a quasi-natural experiment, examines the impact of environmental regulation on the upgrading of urban industrial structure by constructing a DID model, and tests the heterogeneity of its role at the regional and urban levels. Results have found that: (1) From a national perspective, the two control zones policy has significantly promoted the upgrading of urban industrial structure. In addition, from the perspective of different control zones, the two control zones policy has a positive promoting effect on the upgrading of industrial structure. (2) The two control zones policy has significant long-term effects in promoting industrial structure upgrading, and its impact on industrial structure upgrading shows dynamic effects. (3) The industrial structure upgrading effect of the two control zones policy exhibits significant heterogeneity across different city scales. (4) In terms of regions, the two control zones policy has significant spatial heterogeneity.
Modeling of System Availability and Bayesian Analysis of Bivariate Distribution
Authors: Farooq Muhammad , Gul Ahtasham , Alshanbari Huda M. , Khosa Saima K.
Published: September 2023

To meet the desired standard, it is important to monitor and analyze different engineering processes to obtain the desired output. The bivariate distributions have received a significant amount of attention in recent years due to their ability to describe randomness of natural as well as artificial mechanisms. In this article, a bivariate model is constructed by compounding two independent asymmetric univariate distributions and by using the nesting approach to study the effect of each component on reliability for better understanding. Furthermore, the Bayes analysis of system availability is studied by considering prior parametric variations in the failure time and repair time distributions. Basic statistical characteristics of marginal distribution like mean median and quantile function are discussed. We used inverse Gamma prior to study its frequentist properties by conducting a Monte Carlo Markov Chain (MCMC) sampling scheme.
Analytical Size Exclusion Chromatography Coupled with Mass Spectrometry in Parallel with High-Throughput Venomics and Bioassaying for Venom Profiling
Authors: Terzioglu Sedef , Bittenbinder Mátyás A. , Slagboom Julien , van de Velde Bas , Casewell Nicholas R. , Kool Jeroen
Published: September 2023

Modern analytical size exclusion chromatography (SEC) is a suitable technique to separate venom toxin families according to their size characteristics. In this study, a method was developed to separate intact venom toxins from Bungarus multicinctus and Daboia russelii venoms via analytical SEC using volatile, non-salt-containing eluents for post-column mass spectrometry, coagulation bioassaying and high-throughput venomics. Two venoms were used to demonstrate the method developed. While the venom of Bungaurs multicinctus is known to exert anticoagulant effects on plasma, in this study, we showed the existence of both procoagulant toxins and anticoagulant toxins. For Daboia russelii venom, the method revealed characteristic procoagulant effects, with a 90 kDa mass toxin detected and matched with the Factor X-activating procoagulant heterotrimeric glycoprotein named RVV-X. The strong procoagulant effects for this toxin show that it was most likely eluted from size exclusion chromatography non-denatured. In conclusion, the separation of snake venom by size gave the opportunity to separate some specific toxin families from each other non-denatured, test these for functional bioactivities, detect the eluting mass on-line via mass spectrometry and identify the eluted toxins using high-throughput venomics.
Revise the Phase-Space Analysis of the Dynamical Spacetime Unified Dark Energy Cosmology
Authors: Paliathanasis Andronikos
Published: September 2023

We analyze the phase-space of an alternate scalar field cosmology that aims to combine the concepts of dark energy and the dark sector. The investigation focuses on stationary points within this phase-space, considering different functional forms of the two potential functions. Our findings indicate that a de Sitter universe is achievable solely when at the asymptotic limit the potential function is constant. For constant potential function, the de Sitter universe is recovered in the finite regime; however, for the exponential potential, the de Sitter universe exists at the infinity regime. The cosmological viability of the present theory is discussed.
Generation and Characterisation of Monoclonal Antibodies against Nairobi Sheep Disease Virus Nucleoprotein
Authors: Maze Emmanuel A. , Chrun Tiphany , Booth George , Limon Georgina , Charleston Bryan , Lambe Teresa
Published: September 2023

Nairobi sheep disease (NSD), caused by the viral agent NSD virus (NSDV), is a haemorrhagic fever disease affecting and inducing high mortality in sheep and goat populations. NSDV belongs to the genus Orthonairovirus of the Nairoviridae family from the order Bunyavirales. Other viruses circulating in livestock such as Crimean–Congo haemorrhagic fever virus (CCHFV) and Dugbe virus (DUGV) are members of the same genus and are reported to share antigenic features. There are very few available materials to study NSDV infection both in vitro and in vivo. In the present work, we characterised two monoclonal antibodies generated in mice that recognise NSDV specifically but not CCHFV or DUGV, along with a potential use to define virus-infected cells, using flow cytometry. We believe this tool can be useful for research, but also NSDV diagnostics, especially through immunological staining.
B-Cell Epitopes-Based Chimeric Protein from SARS-CoV-2 N and S Proteins Is Recognized by Specific Antibodies in Serum and Urine Samples from Patients
Authors: Ramos Fernanda F. , Pereira Isabela A. G. , Cardoso Mariana M. , Bandeira Raquel S. , Lage Daniela P. , Scussel Rahisa , Anastacio Rafaela S. , Freire Victor G. , Melo Marina F. N. , Oliveira-da-Silva Joao A. , Martins Vivian T. , Tavares Grasiele S. V. , Vale Danniele L. , Freitas Camila S. , Chaves Ana Thereza , Caporali Júlia F. M. , Vassallo Paula F. , Ravetti Cecilia G. , Nobre Vandack , Fonseca Flavio G. , Christodoulides Myron , Machado-de-Ávila Ricardo A. , Coelho Eduardo A. F. , Ludolf Fernanda
Published: September 2023

The impact of the COVID-19 pandemic caused by the SARS-CoV-2 virus underscored the crucial role of laboratorial tests as a strategy to control the disease, mainly to indicate the presence of specific antibodies in human samples from infected patients. Therefore, suitable recombinant antigens are relevant for the development of reliable tests, and so far, single recombinant proteins have been used. In this context, B-cell epitopes-based chimeric proteins can be an alternative to obtain tests with high accuracy through easier and cheaper production. The present study used bioinformatics tools to select specific B-cell epitopes from the spike (S) and the nucleocapsid (N) proteins from the SARS-CoV-2 virus, aiming to produce a novel recombinant chimeric antigen (N4S11-SC2). Eleven S and four N-derived B-cell epitopes were predicted and used to construct the N4S11-SC2 protein, which was analyzed in a recombinant format against serum and urine samples, by means of an in house-ELISA. Specific antibodies were detected in the serum and urine samples of COVID-19 patients, which were previously confirmed by qRT-PCR. Results showed that N4S11-SC2 presented 83.7% sensitivity and 100% specificity when using sera samples, and 91.1% sensitivity and 100% specificity using urine samples. Comparable findings were achieved with paired urine samples when compared to N and S recombinant proteins expressed in prokaryotic systems. However, better results were reached for N4S11-SC2 in comparison to the S recombinant protein when using paired serum samples. Anti-N4S11-SC2 antibodies were not clearly identified in Janssen Ad26.COV2.S COVID-19-vaccinated subjects, using serum or paired urine samples. In conclusion, this study presents a new chimeric recombinant antigen expressed in a prokaryotic system that could be considered as an alternative diagnostic marker for the SARS-CoV-2 infection, with the potential benefits to be used on serum or urine from infected patients.
The Use of High-Flow Nasal Cannula and Non-Invasive Mechanical Ventilation in the Management of COVID-19 Patients: A Prospective Study
Authors: Arunachala Sumalatha , Parthasarathi Ashwaghosha , Basavaraj Chetak Kadabasal , Malamardi Sowmya , Chandran Shreya , Venkataraman Hariharan , Ullah Mohammed Kaleem , Ganguly Koustav , Upadhyay Swapna , Mahesh Padukudru Anand
Published: September 2023

High-flow nasal cannula (HFNC) and ventilator-delivered non-invasive mechanical ventilation (NIV) were used to treat acute respiratory distress syndrome (ARDS) due to COVID-19 pneumonia, especially in low- and middle-income countries (LMICs), due to lack of ventilators and manpower resources despite the paucity of data regarding their efficacy. This prospective study aimed to analyse the efficacy of HFNC versus NIV in the management of COVID-19 ARDS. A total of 88 RT-PCR-confirmed COVID-19 patients with moderate ARDS were recruited. Linear regression and generalized estimating equations (GEEs) were used for trends in vital parameters over time. A total of 37 patients were on HFNC, and 51 were on NIV. Patients in the HFNC group stayed slightly but not significantly longer in the ICU as compared to their NIV counterparts (HFNC vs. NIV: 8.00 (4.0–12.0) days vs. 7.00 (2.0–12.0) days; p = 0.055). Intubation rates, complications, and mortality were similar in both groups. The switch to HFNC from NIV was 5.8%, while 37.8% required a switch to NIV from HFNC. The resolution of respiratory alkalosis was better with NIV. We conclude that in patients with COVID-19 pneumonia with moderate ARDS, the duration of treatment in the ICU, intubation rate, and mortality did not differ significantly with the use of HFNC or NIV for respiratory support.
Epidemiological Changes in Respiratory Viral Infections in Children: The Influence of the COVID-19 Pandemic
Authors: Almeida Teresa , Guimarães João Tiago , Rebelo Sandra
Published: September 2023

Background: Viruses are the major cause of acute respiratory infections in children, causing important morbimortality. Before the COVID-19 pandemic, in temperate regions, respiratory viruses displayed a typical seasonality in transmission. A disruption in this pattern was observed in several countries during the pandemic, with low prevalence during the typical season, and an interseasonal rise. We evaluated the effects of the COVID-19 pandemic in the epidemiology of non-COVID viral respiratory infections in children, in a tertiary care hospital in Portugal. Methods: Between March 2020 and August 2022, nasopharyngeal samples from children with respiratory symptoms in the Emergency Department (ED) and the Pediatric Ward were tested for RSV, influenza and other respiratory viruses, by real-time reverse transcriptase PCR (RT-PCR). Results: A seasonal variation was observed from 2018 to 2020, with prevalence increasing in winter (mainly RSV and influenza). In the winter of 2020/21, when measures to mitigate SARS-CoV-2 transmission were stricter, there was a disruption of the seasonal pattern, with unusually low numbers. In the summer of 2021, when measures were being relaxed, there was an atypical rise. In June 2021, RSV was first detected and peaked in October. Influenza (Influenza A H3) was detected for the first time in February 2022, peaking in March/April. Conclusions: These findings show a disruption of the seasonality of viral respiratory infections in children during the pandemic, with a virtual elimination during the months of usually higher prevalence, and a subsequent out-of-season increase, coinciding with variations in the measures implemented to control the SARS-CoV-2 transmission, and confirming their efficacy.
Development and Validation of a Panel of One-Step Four-Plex qPCR/RT-qPCR Assays for Simultaneous Detection of SARS-CoV-2 and Other Pathogens Associated with Canine Infectious Respiratory Disease Complex
Authors: Thieulent Côme J. , Carossino Mariano , Peak Laura , Strother Keith , Wolfson Wendy , Balasuriya Udeni B. R.
Published: September 2023

Canine infectious respiratory disease complex (CIRDC) is the primary cause of respiratory disease in the canine population and is caused by a wide array of viruses and bacterial pathogens with coinfections being common. Since its recognition in late 2019, Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) has been reported to cause respiratory disease in dogs. Therefore, the rapid detection and differentiation of SARS-CoV-2 from other common viral and bacterial agents is critical from a public health standpoint. Here, we developed and validated a panel of four one-step multiplex qPCR/RT-qPCR assays for the detection and identification of twelve pathogens associated with CIRDC (canine adenovirus-2, canine distemper virus, canine herpesvirus-1, canine influenza A virus, canine parainfluenza virus, canine pneumovirus, canine respiratory coronavirus, SARS-CoV-2, Bordetella bronchiseptica, Streptococcus equi subsp. zooepidemicus, Mycoplasma cynos, and M. canis), as well as the identification of three main CIV subtypes (i.e., H3N2, H3N8, and H1N1). All developed assays demonstrated high specificity and analytical sensitivity. This panel was used to test clinical specimens (n = 76) from CIRDC-suspected dogs. M. canis, M. cynos, and CRCoV were the most frequently identified pathogens (30.3%, 25.0%, and 19.7% of samples, respectively). The newly emerging pathogens CPnV and SARS-CoV-2 were detected in 5.3% of samples and coinfections were identified in 30.3%. This new multiplex qPCR/RT-qPCR panel is the most comprehensive panel developed thus far for identifying CIRDC pathogens, along with SARS-CoV-2.