bluuebunny/crossref_metadata_2025 huggingface dataset:
Your Firm Needs a Sustainable Business Innovation Ecosystem
Authors: Zhang Shihong , Lee Min-Jae , Chen Guanyu , Jung Jin-Sup , Cho Moon Hwan
Published: December 2024

There have been many discussions about the business ecosystem in order to promote the sustainable growth of firms recently. Business ecosystems have developed independently from three perspectives: business, innovation, and the platform ecosystem. However, considering the emergence of advanced technology and social values, there is a growing need to look at business ecosystems from an integrated point of view. Based on a new win–win platform combining these discussions, we have designed and demonstrated a sustainable business innovation ecosystem (SBIE) framework. Using the triple helix model, data were collected from 290 experts—industry (95), government (100), and university (95)—in Korea. Results show that firms should consider social values as well as economic values when building a SBIE. The findings also emphasize that performances are more effective when core agents of ecosystem build a win–win platform using the fourth industrial revolution (FIR) technology.
Biological Control of Aphids in Spain’s Urban Green Spaces
Authors: Lumbierres Belén , Meseguer Roberto , Levi-Mourao Alexandre , Pons Xavier
Published: December 2024

Green spaces in urban areas, such as parks and gardens, provide recreational, social, and health benefits for more than half of the world’s inhabitants. Arthropods in urban vegetation may cause some disruption to humans but also provide vital ecological services such as biological control and pollination. However, little is known about the ecology of urban pests, their natural enemies, and how to manage them in an ecofriendly manner, especially in Southern Europe. In this review article, we consider the information available concerning the biological control of aphids in the urban green areas of Spain, mainly focusing on the different aphid species, their natural enemies (and how to enhance them), and the sampling methods used to study them. A wide range of aphid species is found in Spain, but only a few are responsible for the majority of damage (so-called k-aphids, most of which are holocyclic species), and these show two distinct injury profiles (short and long) that determine monitoring and control strategies. Urban aphids have numerous natural enemies, including more than 20 species of ladybeetles, as well as predatory hoverflies, midges, lacewings, bugs, and other groups. More than 40 species of aphid parasitoids and their tritrophic aphid plant associations have been reported. The availability and usefulness of commercially reared aphid natural enemies is discussed, and two methods to enhance natural enemies are described. We also review aphid sampling methods developed for urban green spaces. The studies provide basic information on the ecology of aphids to support conservation biological control as a reliable strategy in the urban green areas of Spain.
The Competitiveness of Turkish Tourism in the Global Market
Authors: Aktaş Çimen Zeynep , Kutlu Didem , Sarıçoban Kazım , Ongun Utku
Published: December 2024

Assessing a country’s tourism competitiveness is vital for identifying its tourism potential. The aim of this study is to determine Türkiye’s competitiveness in world tourism exports over the period 2010–2023 and to compare the similarity of Türkiye’s exports to the world tourism market with 40 tourism exporting countries that provide complete data for the analyzed period. The study uses the Relative Export Advantage (RXA) Index and Export Similarity Index (ESI) from the Revealed Comparative Advantage indexes. The RXA analysis, based on Trade Map data, reveals that out of 26 competitive countries, 10 have a “strong”, 9 a “moderate”, and 7 a “weak” advantage. The top countries with a “strong” advantage are Macao, the Dominican Republic, Mexico, Jordan, Croatia, Saudi Arabia, Thailand, Vietnam, Australia, and New Zealand. According to 2023 Trade Map data, Türkiye, ranking sixth globally in tourism export revenues, is the most competitive among Spain, Portugal, Malaysia, Morocco, Egypt, Indonesia, Greece, and Italy, which have a “medium” competitive advantage. The ESI results show that Türkiye’s export similarity with highly competitive countries was initially higher during 2010–2023 but has since decreased.
Constructing Safety Management Systems in Modern Industry and Trade Enterprises: A STAMP-Based Approach
Authors: Xu Xiaomeng , Li Donghui , Huang Guojun , Wang Ziheng , Zhu Lingjie , Ni Xinyi
Published: December 2024

With the burgeoning landscape of new enterprises and business paradigms, industrial and trade enterprises are facing escalating pressure to ensure operational safety. Conventional safety management mechanisms have proven to be inadequate for adapting to the dynamic market demands and intricacies of modern production environments. To improve safety management practices, this study integrates complex network theory to dissect the causal chains underlying accidents in industry and trade enterprises. A network model is established to elucidate the factors contributing to accidents and leverage datasets from safety inspections to construct a repository of latent safety risks. To address deficiencies in extant safety frameworks, a comprehensive safety management evaluation system is formulated, comprising ten primary evaluation indices and 30 secondary metrics. Based on the established frameworks, such as ISO 45001 for occupational health and safety management systems (OHSMS), standardized safety production protocols, and risk hierarchical management and control systems and hidden hazard identification and treatment systems (dual prevention systems), a holistic safety management system (SMS) is synthesized on the basis of system-theoretic accident model and process (STAMP) theory. This systematic approach culminates in a robust framework tailored to modern industrial and trade enterprises, fostering flexibility and efficacy in safety management capabilities. This case analysis underscores the model’s ability to enhance its safety management proficiency, thereby amplifying its relevance in fortifying enterprise operations and fostering sustainable growth. This study represents a pivotal step toward augmenting safety management capacities within the industrial and trade enterprises to safeguard enterprise vitality and advance sustainable business practices.
Exploration of Research Hotspots and Trends in Photovoltaic Landscape Studies Based on Citespace Analysis
Authors: Jiang Feihu , Wang Chaohong , Shi Yu , Zhang Xudong
Published: December 2024

This study examines the photovoltaic (PV) landscape-related literature indexed in the Web of Science database from 2005 to 2024, employing a combination of bibliometric analysis software and a manual review to analyze, explore, and summarize the development trajectory and future trends in PV landscape research. Over the past two decades, PV landscape research has progressed through three stages: the foundational stage from 2005 to 2008, during which studies primarily focused on the environmental impacts of PV installations; the developmental stage from 2009 to 2020, characterized by interdisciplinary integration, with research shifting its focus to the combination of PV systems with living and production environments, advancements in PV landscape technologies, and innovations in PV materials; and the maturity stage from 2021 to 2024, which has seen heightened requirements for energy conversion efficiency and stability in PV systems, along with the establishment of a systematic research framework for PV landscapes, enabling more diverse explorations of its development. Based on this analysis, this study summarizes key research frontiers in PV landscapes, including the impacts and assessment of PV installations on the ecological environment, the deep integration of PV systems with living environments, and the visual aesthetic impacts and evaluation of PV landscapes. Finally, this study proposes three future prospects for PV landscapes and briefly discusses the limitations of this research.
Artificial Neural Networks as a Method for Forecasting Migration Balance (A Case Study of the City of Lublin in Poland)
Authors: Gawryluk Adam , Komor Agnieszka , Kulisz Monika , Zarębski Patrycjusz , Katarzyński Dominik
Published: December 2024

Internal migration regulates both the size and structure of human resources and affects the labor market at different spatial scales. It therefore has not only a demographic dimension, but also a spatial one, which is why it can significantly affect development on both a local and regional scale. The main objective of this study was to examine the usefulness of artificial neural networks (ANN) for predicting the internal migration balance for the city of Lublin in Poland. Another objective was to develop an experimental neural network model for forecasting the internal migration balance for the city of Lublin (for one year ahead) based on selected economic and social factors. The study area included the city of Lublin and 14 municipalities located in the vicinity of the city and functionally connected to it (they form the Lublin Functional Area), i.e., a total of 15 spatial units. Data for the analysis covered the years 2005–2022 and were obtained from the Local Data Bank (BDL) of the Central Statistical Office (GUS). The number of input variables for the ANN model was reduced using principal component analysis (PCA), allowing for the inclusion of the most relevant demographic and economic features. These components can thus be considered reliable predictors of the migration balance for the city of Lublin. This suggests that artificial neural networks may be an effective tool in supporting decision-making processes for forecasting the migration balance of this city.
Greening the Gulf: A Deep-Dive into the Synergy Between Natural Resources, Institutional Quality, Foreign Direct Investment, and Pathways to Environmental Sustainability
Authors: Qin Feng , Imran Ali
Published: December 2024

Environmental quality is a global concern, especially in Gulf Cooperation Council (GCC) countries where abundant mineral resources, economic growth, and globalization have strained the environment through urbanization and resource exploitation. This study examines the impact of globalization (GLOL), urbanization (URBN), natural resource extraction (NRER), institutional quality (INSQ), and foreign direct investment (FDI) on environmental quality in GCC countries from 1999 to 2021. Cross-sectional dependence (CSD) was assessed using the Lagrange Multiplier (LM) and cross-dependence (CD) techniques, and stationarity was confirmed with the Levin–Lin–Chu test. The Augmented Dickey–Fuller (ADF) co-integration test verified long-term relationships, and Pooled Mean Group Autoregressive Distributed Lag (PMG-ARDL) methodology assessed short- and long-term effects. Our findings show that FDI, GLOL, and INSQ have negative long-term impacts on environmental quality, while NRER and URBN are beneficial. In the short term, FDI and INSQ improve green quality, while GLOL, URBN, and NRER have detrimental effects. Policy recommendations include discouraging FDI in non-renewable projects, promoting sustainable FDI, addressing income inequality to improve environmental quality, and investing in urban development to reduce ecological footprints (ECFTs) and enhance environmental quality in GCC countries.
Framework for Monitoring the Spatiotemporal Distribution and Clustering of the Digital Society Index of Indonesia
Authors: Jaya I Gede Nyoman Mindra , Pahlevi Said Mirza , Susenna Argasi , Agustina Lidya , Kusumasari Dita , Sukma Yan Andriariza Ambhita , Hernikawati Dewi , Rahmi Anggi Afifah , Pravitasari Anindya Apriliyanti , Kristiani Farah
Published: December 2024

Digital disparities remain a significant challenge in Indonesia, particularly across its diverse regions, with uneven access to digital infrastructure, skills, and economic opportunities. This study aims to map these digital disparities at the district level, analyze the spatial distribution and clustering of digital transformation using the Digital Society Index of Indonesia (IMDI), and investigate the key drivers of digital inequality across four core pillars: Infrastructure and Ecosystem, Digital Skills, Empowerment, and Jobs. To measure the IMDI, primary data were collected from the industrial sector and the general population over three years (2022–2024), combined with secondary data on internet usage and service standards. A multistage random sampling approach ensured representativeness, considering demographic variations and industrial segments. The analysis employed spatiotemporal methods to capture temporal trends and spatial clustering. The results revealed a significant IMDI increase from 37.80 in 2022 to 43.18 in 2023, followed by stability at 43.34 in 2024. The hotspots of digital transformation remain concentrated on Java Island, while low spots persist in eastern Indonesia. This study provides critical insights into Indonesia’s digital readiness, identifying priority areas for targeted interventions to bridge the digital divide and foster equitable digital development.
Increasing Socioeconomic Exposure to Compound Dry and Hot Events Under a Warming Climate in the Yangtze River Basin
Authors: Zhang Jiexiang , Zhang Xuejun , Lyu Juan , Qu Yanping , Leng Guoyong
Published: December 2024

Investigating changes in compound dry and hot events (CDHEs) and evaluating the associated socioeconomic exposure under climate change are critical for developing effective climate change mitigation and adaptation strategies. However, the socioeconomic exposure and the contributions of various driving factors to socioeconomic exposure under different warming levels remain poorly understood. Using the latest climate experiments from Coupled Model Intercomparison Project Phase 6 (CMIP6), this study assessed future changes in the frequency and socioeconomic exposure of CDHEs and explored the contributing drivers in the Yangtze River Basin (YRB) under 1.5 °C, 2.0 °C, and 3.0 °C global warming scenarios. Results indicate that the occurrences of CDHEs are projected to increase by 2.9, 3.9, and 4.8 times in a 1.5 °C, 2.0 °C, and 3.0 °C warmer world, respectively, compared to the present period (1985–2014). Population exposure to CDHEs increases significantly, with the greatest magnitude occurring at the 2 °C warming scenario. GDP exposure is expected to intensify continuously as the global average temperature rises, with the area experiencing significant increases continuously expanding. Climate change is the dominant driver of total projected changes in population exposure to CDHEs, accounting for approximately 105.6% at 1.5 °C, 110.3% at 2.0 °C, and 141.0% at 3.0 °C. At 1.5 °C, 2.0 °C, and 3.0 °C warming levels, changes in GDP exposure are primarily driven by the synergistic interaction between climate and GDP, accounting for 50.7%, 62.0%, and 64.8%, respectively. These findings provide valuable insights for climate change mitigation and adaptation strategies.
Geographical Variability of Set-Aside in Poland: Environmental and Anthropogenic Impacts on the Implementation of Complementary EU Instrument
Authors: Leśniewska-Napierała Katarzyna , Napierała Tomasz , Nalej Marta
Published: December 2024

The aim of this paper is to determine whether the complementary instrument of agricultural cyclical set-aside has been implemented in Poland over the past decade (2014–2023). Additionally, this study examines the geographical variability in the set-aside application and identifies factors that contribute to this spatial variability. Geographically Weighted Regression is employed to capture the spatial variation in environmental and anthropogenic factors influencing set-aside measures. Findings confirm that rotational set-aside practices vary across Polish municipalities. Negative impacts on set-aside measures are associated with the following independent variables: farm size, environmental protection, low-quality soils, water surface, and social capital. However, the magnitude and significance of these impacts vary spatially. Geographically differentiated impacts are observed for variables such as length of the growing season, precipitation, mineral fertilizer consumption, and slope of the terrain. Interestingly, a general positive influence is not confirmed for any predictor regarding the frequency and extent of set-aside practices. The findings suggest reconsidering and emphasizing the geographical aspects of the Common Agricultural Policy within the European Union.
The Role of Marketing Artificial Intelligence in Enhancing Sustainable Financial Performance of Medium-Sized Enterprises Through Customer Engagement and Data-Driven Decision-Making
Authors: Magableh Ihab K. , Mahrouq Maher H. , Ta’Amnha Mohammad A. , Riyadh Hosam Alden
Published: December 2024

This study aims to examine the impact of marketing artificial intelligence (AI) and the specific channels it uses to influence the performance of Jordanian SMEs. In contrast to prior research that focused solely on the direct effects of marketing AI on organizational performance, our study introduces innovative pathways involving customer engagement, customer satisfaction, and data-driven decision-making. These channels serve as indirect mechanisms through which the impact of marketing AI extends to influence the Sustainable Financial Performance of SMEs. Using a framework for structural equation modeling, we looked at the answers of 250 small and medium-sized enterprises (SMEs) chosen through cluster sampling from industrially active areas in Jordan. Our findings reveal that the adoption of AI technologies leads to a notable 42.5% enhancement in Sustainable Financial Performance among SMEs, driven by a 50% increase in customer engagement and a 76% improvement through data-driven decision-making processes. While our study did not establish a direct correlation between marketing AI and long-term financial performance, it demonstrated the connection between technology adoption, customer-focused strategies, and data-driven practices. The findings offer actionable insights and recommendations for Jordanian SMEs leveraging marketing AI to achieve competitive advantage and sustainable growth. The study offers significant contributions to how marketing AI improves the Sustainable Financial Performance of Jordanian SMEs by identifying crucial indirect pathways. Unlike previous studies, it focuses on the roles of customer engagement, satisfaction, and data-driven decision-making as mediators rather than emphasizing direct impacts. The findings highlight the importance of integrating technology with customer-centric and data-oriented strategies to drive sustainable growth and competitiveness in SMEs.
The Spatiotemporal Distribution Characteristics and Influencing Factors of Unicorn Companies and Gazelle Companies in Jiangsu Province
Authors: Li Xueyu , Ye Lei , Chen Huangwei
Published: December 2024

In recent years, Jiangsu Province has increasingly prioritized the coordinated regional development of innovation. Unicorn and gazelle companies, characterized by technological or business model innovation, serve as significant indicators of regional innovation capacity. Therefore, this study uses unicorn and gazelle companies recognized between 2020 and 2022 in Jiangsu Province as samples, employing ArcGIS and geographical detectors to investigate the spatial distribution characteristics and influencing factors of these companies, and to propose optimization strategies, with the aim of assessing the innovation landscape of Jiangsu Province. The key findings and conclusions are as follows: (1) over the past three years, the average nearest-neighbor distance decreased from 10.491 km to 1.706 km, indicating a significant spatial agglomeration; the peak core density of business clusters increased substantially, reflecting the growth in the number of companies as clustering deepened. (2) Unicorns and gazelles exhibit clear clustering characteristics. The standard deviation ellipse of unicorns is centered around Suzhou, while gazelles display a continuous distribution pattern in Southern and Central Jiangsu. (3) Geographical detector analysis reveals that the level of urban technological innovation is the most influential factor, with key determinants of distribution including total retail sales and patent grants. (4) To foster the development of unicorn and gazelle companies in Jiangsu, the government should focus on enhancing regional innovation capacity, ensuring the sustainable nurturing of innovative firms, and promoting the catalytic development of surrounding areas through core cities.
Exploring the Application Method of Bamboo Powder in Promoting the Development of Sustainable Outdoor Furniture
Authors: Fan Yafei , Zhu Ziqian , Luan Jiacheng , Liu Yi
Published: December 2024

With the depletion of fossil fuels, more and more green products are appearing in daily necessities. Bamboo is a common sustainable biomaterial with the characteristics of fast growth, easy bending, low cost, and easy processing, and it is widely used in furniture design. However, the poor aging resistance and UV resistance of natural bamboo materials limit their application in outdoor furniture. In order to improve the service life of outdoor bamboo furniture, this study prepared bamboo boards from bamboo powder and utilized them in the design of outdoor furniture. The research was conducted in two stages. In the first stage, functional modification was carried out on the surface of bamboo fibers (BF). Epoxy resin and UV absorber ZnO were introduced into the bamboo powder matrix, and a three-dimensional network structure of bamboo powder-based polymer material was formed by adjusting the material ratio and reaction conditions. With the increase of ZnO content, the absorption of moisture by the bamboo powder-based polymer materials decreased. The compressive strength of 1.5%ZnO-Board reached 36.8 MPa, exceeding the compressive strength of C30 concrete. In the second stage, 1.5% ZnO-Board was selected for solidification and demolding, and used as the seat surface for outdoor chairs. Through the car crushing experiment, the chair panel did not undergo significant deformation during the car crushing process. The anti-aging experiment showed that the structure and morphology of the panel would not be damaged by long-term UV irradiation. The panel did not show any weight changes in the anti-water-absorption experiment. By using low-contrast color combinations, the seats can be organically integrated into the environmental background, effectively enhancing the coordination and unity of the overall aesthetic harmony of the space. Compared with the commonly used plastic outdoor seats, the outdoor seats prepared in this study showed a 144% increase in carbon reduction effect. This study highlights the potential of modified bamboo powder for the design of outdoor furniture, which is of great significance to reducing outdoor plastic products and promoting sustainable life.
Barriers to Sustainable Healthcare Waste Management: A Grey Method Approach for Barrier Ranking
Authors: Quttainah Majdi Anwar , Singh Priya
Published: December 2024

Healthcare Waste Management (HCWM) is critical for public health and environmental sustainability. However, healthcare facilities face significant barriers to implementing sustainable HCWM practices, particularly in developing regions. Identifying and prioritizing these barriers is essential to developing practical solutions. This study aims to identify and rank barriers to sustainable HCWM using an integrated methodology. It seeks to provide actionable insights for policymakers and healthcare administrators to improve HCWM practices. The study employed a multi-method approach, combining a comprehensive literature review, expert consultations, and Grey Relational Analysis (GRA). The literature review identified 17 potential barriers across economic, social, technical, and regulatory dimensions. Eight experts from diverse sectors evaluated these barriers based on ten criteria. GRA was used to rank the barriers, and sensitivity analysis assessed the robustness of the rankings under varying parameters. The findings revealed that the most critical barriers include the lack of standardized guidelines and protocols, ineffective waste segregation, awareness and knowledge gaps, and inadequate training. Financial constraints and disposal infrastructure also ranked highly, highlighting systemic challenges in HCWM. Sensitivity analysis demonstrated that these rankings remained stable across varying conditions, affirming the robustness of the results. Addressing the prioritized barriers—mainly through policy standardization, enhanced training programs, and improved resource allocation—can significantly improve HCWM practices. This study underscores the need for a holistic approach integrating technical, social, and regulatory interventions to enhance sustainability in healthcare waste management.
Tripartite Evolutionary Game Analysis of Green Coal Mining: Insights from Central Environmental Protection Inspection
Authors: Zou Shaohui , Xie Jiahang
Published: December 2024

This paper constructs an evolutionary game model involving the “central government–local government–coal enterprises” to explore the impact mechanism of central environmental protection inspection on green coal mining. By analyzing the strategic behaviors of the key actors, this study identifies critical factors that influence their decisions. System simulations are conducted to assess the effects of key parameters on system stability and convergence. The findings indicate the following: (1) Increasing inspection costs weaken the central government’s support for green mining, with excessive costs potentially causing regulatory fatigue. Moderating inspection investments is key to sustaining long-term effectiveness. (2) Higher penalties for local governments improve the enforcement of green mining policies, particularly in the mid-term, showing that stringent penalties are an effective regulatory tool. (3) Lower technical costs and greater economic incentives encourage coal enterprises to adopt green mining practices, highlighting the role of innovation and profitability in driving green transitions. (4) Central government subsidies enhance local governments’ short-term enforcement but may lead to dependence if overused. Balanced subsidy policies are essential for sustained policy implementation at the local level. Based on these findings, the paper proposes policy recommendations to improve inspection mechanisms, optimize policy tools, and establish a collaborative regulatory system to ensure the long-term effectiveness of green coal mining.
Manipulating Time Series Irreversibility Through Continuous Ordinal Patterns
Authors: Zanin Massimiliano
Published: December 2024

Time irreversibility, i.e., the lack of invariance of a system under the operation of time reversal, has long attracted the attention of the statistical physics community, and has been shown to be a relevant marker of altered dynamics in many real-world problems. Here, I introduce and analyse the complementary problem of its manipulation. In other words, I ask whether, given a time series, it can be manipulated to achieve desired irreversibility while maintaining its original dynamics. I show how this problem can be tackled using Continuous Ordinal Patterns, a non-linear transformation of a time series based on the local structure created by neighbouring values. I further illustrate the relevance of this problem in the context of brain dynamics, determining that schizophrenic patients and control subjects are characterised by different “distances to irreversibility”. Finally, I discuss some open questions, including the meaning of such manipulation from both theoretical and applied viewpoints.
Machine Learning for Predicting Zearalenone Contamination Levels in Pet Food
Authors: Wang Zhenlong , An Wei , Wang Jiaxue , Tao Hui , Wang Xiumin , Han Bing , Wang Jinquan
Published: December 2024

Zearalenone (ZEN) has been detected in both pet food ingredients and final products, causing acute toxicity and chronic health problems in pets. Therefore, the early detection of mycotoxin contamination in pet food is crucial for ensuring the safety and well-being of animals. This study aims to develop a rapid and cost-effective method using an electronic nose (E-nose) and machine learning algorithms to predict whether ZEN levels in pet food exceed the regulatory limits (250 µg/kg), as set by Chinese pet food legislation. A total of 142 pet food samples from various brands, collected between 2021 and 2023, were analyzed for ZEN contamination via liquid chromatography–tandem mass spectrometry. Additionally, the “AIR PEN 3” E-nose, equipped with 10 metal oxide sensors, was employed to identify volatile compounds in the pet food samples, categorized into 10 different groups. Machine learning algorithms, including liner regression, k-nearest neighbors, support vector machines, random forests, XGBoost, and multi-layer perceptron (MLP), were used to classify the samples based on their volatile profiles. The MLP algorithm showed the highest discrimination accuracy at 86.6% in differentiating between pet food samples above and below the ZEN threshold. Other algorithms showed moderate accuracy, ranging from 77.1% to 84.8%. The ensemble model, which combined the predictions from all classifiers, further improved the classification performance, achieving the highest accuracy at 90.1%. These results suggest that the combination of E-nose technology and machine learning provides a rapid, cost-effective approach for screening ZEN contamination in pet food at the market entry stage.
Disk Evolution Study Through Imaging of Nearby Young Stars (DESTINYS): Dynamical Evidence of a Spiral-Arm-Driving and Gap-Opening Protoplanet from SAO 206462 Spiral Motion
Authors: Xie Chen , Xie Chengyan , Ren Bin B. , Benisty Myriam , Ginski Christian , Fang Taotao , Casassus Simon , Bae Jaehan , Facchini Stefano , Ménard François , van Holstein Rob G.
Published: December 2024

In the early stages of planetary system formation, young exoplanets gravitationally interact with their surrounding environments and leave observable signatures on protoplanetary disks. Among these structures, a pair of nearly symmetric spiral arms can be driven by a giant protoplanet. For the double-spiraled SAO 206462 protoplanetary disk, we obtained three epochs of observations spanning 7 yr using the Very Large Telescope’s SPHERE instrument in near-infrared J-band polarized light. By jointly measuring the motion of the two spirals at three epochs, we obtained a rotation rate of −0.°85±0.°05yr−1. This rate corresponds to a protoplanet at 66±3 au on a circular orbit dynamically driving both spirals. The derived location agrees with the gap in ALMA dust-continuum observations, indicating that the spiral driver may also carve the observed gap. What is more, a dust filament at ∼63 au observed by ALMA coincides with the predicted orbit of the spiral-arm-driving protoplanet. This double-spiraled system is an ideal target for protoplanet imaging.
High-Throughput Sequencing for the Detection of Viruses in Grapevine: Performance Analysis and Best Practices
Authors: Stevens Kristian A. , Al Rwahnih Maher
Published: December 2024

Among the cultivated crop species, the economically and culturally important grapevine plays host to the greatest number of distinctly characterized viruses. A critical component of the management and containment of these viral diseases in grapevine is both the identification of infected vines and the characterization of new pathogens. Next-generation high-throughput sequencing technologies, i.e., HTS technologies, have been widely adopted for their ability to quickly, broadly and directly characterize molecular sequences associated with potential pathogens. We empirically analyze the performance of HTS as a diagnostic tool in a phytosanitary context and make recommendations on its deployment for detecting known and novel viruses in grapevine. Three popular and widely used modalities for analyzing HTS data are characterized and compared using the standard diagnostic performance criteria of sensitivity (the true positive rate), specificity (the true negative rate) and analytical sensitivity (dilution series).
Mapping the Protein Phosphatase 1 Interactome in Human Cytomegalovirus Infection
Authors: Weinberger Stefan , Stecher Carmen , Kastner Marie-Theres , Nekhai Sergei , Steininger Christoph
Published: December 2024

Protein phosphorylation is a crucial regulatory mechanism in cellular homeostasis. The human cytomegalovirus (HCMV) incorporates protein phosphatase 1 (PP1) into its tegument, yet the biological relevance and mechanisms of this incorporation remain unclear. Our study offers the first characterization of the PP1 interactome during HCMV infection and its alterations. Using co-immunoprecipitation, mass spectrometry, and quantitative proteomics, we identified 159 high-confidence interacting proteins (HCIPs) in the PP1 interactome, consisting of 126 human and 33 viral proteins. We observed significant temporal changes in the PP1 interactome following HCMV infection, including the altered interactions of PP1 regulatory subunits. Further analysis highlighted the central roles of these PP1 interacting proteins in intracellular trafficking, with particular emphasis on the trafficking protein particle complex and Rab GTPases, which are crucial for the virus’s manipulation of host cellular processes in virion assembly and egress. Additionally, our study on the noncatalytic PP1 inhibitor 1E7-03 revealed a decrease in PP1’s interaction with key HCMV proteins, supporting its potential as an antiviral agent. Our findings suggest that PP1 docking motifs are critical in viral–host interactions and offer new insights for antiviral strategies.
Avian Reovirus: From Molecular Biology to Pathogenesis and Control
Authors: Nour Islam , Mohanty Sujit K.
Published: December 2024

Avian reoviruses (ARVs) represent a significant economic burden on the poultry industry due to their widespread prevalence and potential pathogenicity. These viruses, capable of infecting a diverse range of avian species, can lead to a variety of clinical manifestations, most notably tenosynovitis/arthritis. While many ARV strains are asymptomatic, pathogenic variants can cause severe inflammation and tissue damage in organs such as the tendons, heart, and liver. In broilers and turkeys, ARVs can induce severe arthritis/tenosynovitis, characterized by swollen hock joints and lesions in the gastrocnemius tendons. Additionally, ARVs have been implicated in other diseases, although their precise role in these conditions remains to be fully elucidated. In recent years, ARV cases have surged in the United States, emphasizing the need for effective control measures. Routine vaccination with commercial or autogenous vaccines is currently the primary strategy for mitigating ARV’s impact. Future research efforts should focus on enhancing our understanding of ARV-induced pathogenesis, identifying host factors that influence disease severity, and developing novel vaccines based on ongoing surveillance of circulating ARV strains. This review aims to explore the molecular aspects of ARV, including virus structure, replication, molecular epidemiology, the roles of its encoded proteins in host pathogenesis, and the immune response to ARV infection. Furthermore, we discuss the diagnostic approaches of avian reovirus and the potential biosecurity measures and vaccination trials in combating ARV and developing effective antiviral strategies.
Exploring the Behavior of the High-Andean Wetlands in the Semi-Arid Zone of Chile: The Influence of Precipitation and Temperature Variability on Vegetation Cover and Water Quality
Authors: Duhalde Denisse , Cortés Javiera , Arumí José-Luis , Boll Jan , Oyarzún Ricardo
Published: December 2024

In recent decades, global ecosystems have increasingly faced impacts from heightened precipitation variability. Specifically, water availability is an essential factor in wetland dynamics and has ecological importance in the high-Andean wetlands in both mountains and downstream ecosystems, particularly in semi-arid regions. This study focused on a chain of twelve high-Andean wetlands within the “Estero Derecho” nature sanctuary at the headwaters of the Elqui River in north-central Chile. The analysis of the spatiotemporal dynamics of precipitation and vegetation cover used the Landsat 5 and 8 Satellite imagery-derived normalized difference vegetation index (NDVI) and normalized difference moisture index (NDMI) time series during the austral summer (December–March). We employed time series, boxplots, and least-squares regression analyses to explore vegetation cover behavior in relation to precipitation, water quality, and vegetation indices. Precipitation had a marked influence on vegetation behavior, particularly during the Chilean “megadrought” phenomenon. For both the NDVI and NDMI indices and precipitation, negative trends in the time series were observed, along with a highly significant correlation with a one-year lag between both indices and precipitation. The analysis of the individual wetlands showed different vegetation cover behaviors, which were attributable to the altitude, terrain slope, and additional water inputs from streams that have also given rise to alluvial fans that exert a shaping influence on the wetlands. In addition, significant correlations between both indices and water quality parameters (CE, Cl, Mg, Na, and Fe) were identified. The findings of this study can be incorporated into the Sanctuary’s management plan and concretely assist communities involved with wetland conservation.
Revealing Climate-Induced Patterns in Crop Yields and the Water-Energy-Food-Carbon Nexus: Insights from the Pearl River Basin
Authors: Ye Changxin , Yuan Ze , Chen Xiaohong , Zhong Ruida , Huang Lie
Published: December 2024

In the context of growing concerns over food security and climate change, research on sustainable agricultural development increasingly emphasizes the interconnections within agricultural systems. This study developed a regionally integrated optimization and prediction agricultural model to systematically analyze the impacts of climate change on agricultural systems and their feedback mechanisms from a water-energy-food-carbon (WEFC) nexus perspective. Applied to the Pearl River Basin, the model evaluates future trends in grain yield, water use, energy consumption, and carbon emissions under various climate scenarios throughout this century. The results indicate that rising temperatures significantly reduce crop yields, particularly in the western basin, increasing the environmental footprint per unit of grain produced. However, the CO2 fertilization effect substantially offsets these negative impacts. Under the SSP585 scenario, CO2 concentrations rising from 599.77 ppm to 1135.21 ppm by the century’s end led to a shift in crop yield trends from negative (Z = −7.03) to positive (Z = 11.01). This also reduces water, energy, and carbon footprints by 12.82%, 10.62%, and 10.59%, respectively. These findings highlight the critical importance of adaptive management strategies, including precision irrigation, optimized fertilizer use, and climate-resilient practices, to ensure sustainable agricultural production. Despite these insights, the model has limitations. Future research should incorporate uncertainty analysis, diverse adaptation pathways, and advanced technologies such as machine learning and remote sensing to improve predictive accuracy and applicability. This study offers valuable guidance for mitigating the adverse impacts of climate change on the WEFC nexus, supporting sustainable agricultural practices and science-based policy development.
Redesigning the Fuse Plug, Emergency Spillway, and Flood Warning System: An Application of Flood Management
Authors: Sajjadi Seyed Mohsen , Barihi Samireh , Ahadiyan Javad , Azizi Nadian Hossein , Valipour Mohammad , Bahmanpouri Farhad , Khedri Poria
Published: December 2024

According to the World Health Organization (WHO), floods are one of the most important natural disasters in the world, resulting in the severe loss of human lives and intense destruction of infrastructure. The frequent floods in recent decades have caused most parts of Iran to be affected by periodic and destructive floods. Consequently, the casualties and financial losses of floods have increased significantly. The present study aims to investigate redesigning the fuse plug, emergency overflow, and flood system at Ramshir Dam, Iran. In this regard, using a two-dimensional mathematical model, floods with a return period of 10 and 100 years with different scenarios have been investigated. Four scenarios were analyzed, including the current situation, flood channel dredging scenario, flood channel overhaul scenario, and flood channel overhaul scenario with reservoir dredging. The results show the following: (1) The flood channel in its current state cannot even discharge flows lower than the design, i.e., 1400 m3/s, and the flow overflows from the embankments on its sides. (2) Also, the reservoir dredging prevents the failure of the second fuse plug in the 100-year return period (flow rate 4370 m3/s). (3) Discharge more than 2400 m3/s cubic meters led to the activation of the first fuse plug. (4) The present research findings are of particular and essential importance in flood management. (5) The results of this research were based on the rehabilitation and simulation of the diversion dam facilities in the control and conveyance of flood and on three factors of spillway, flood channel, and flood plain, and the correct function of the fuse plug was reviewed.
Optimization of a Chlorella vulgaris-Based Carbon Sequestration Technique Using an Alkaline Medium of Wood Biomass Ash Extract
Authors: Fekete György , Klátyik Szandra , Sebők András , Dálnoki Anna Boglárka , Takács Anita , Gulyás Miklós , Czinkota Imre , Székács András , Gyuricza Csaba , Aleksza László
Published: December 2024

Algae communities as primary producers are essential elements of aquatic ecosystems and contribute significantly to oxygen production, carbon dioxide fixation, and nutrient transport processes in water bodies. The use of algae-based carbon capture and storage technologies does not produce harmful by-products that require disposal, and the resulting algal biomass can be valuable across various industrial sectors. In this study, model experiments were conducted to develop sequential absorption–microalgae hybrid CO2-capture methods. To facilitate CO2 capture from flue gases, wood biomass ash (WBA), an agricultural by-product, was utilized for its alkaline properties, while the flue gas scrubbing medium was regenerated by algae that restored alkalinity during their growth. In our experiments, one of our goals was to determine the optimal conditions for achieving maximum algal biomass growth in the shortest possible time. The suitability of WBA for flue gas cleaning was tested via simulation of CO2 introduction. Moreover, a method was developed to determine the dissolved inorganic carbon content with the use of an OxiTop device monitoring the changes in pressure. The applied device was a closed, static, and pressure-based respirometer originally designed to determine the biological activity of microorganisms in both solid and liquid samples. In addition, the effects of CO2-enriched WBA extract on algae cultivation were also analyzed, confirming that it imposed no growth inhibition and identifying the concentration (10% WBA) that optimally promoted algal growth. The optimal initial algal concentration and nutrient conditions for maximum growth were also determined.
Effects of Underwater Lighting Time on the Growth of Vallisneria spinulosa Yan and Its Water Restoration Process
Authors: Wei Mengyi , Zhao Jinshan , Zhou Xiaolin , Li Fengdan , Zhao Min , Zheng Xiangyong , Tang Ye , Yang Chang , Jin Zhenmin , Wu Suqing
Published: December 2024

Submerged macrophytes play a crucial role in the ecological restoration of water bodies, and their restoration capacity is closely related to the underwater lighting conditions. This study explored the effects of underwater lighting time on the growth characteristics of Vallisneria spinulosa Yan (V. spinulosa) and its water restoration process. V. spinulosa achieved a higher Fv/Fm (0.64), ETRmax (10.43), chlorophyll content (0.85 mg/g), and removal efficiency of total phosphorus (0.37 × 10−3 g m−3 d−1) and a lower algal abundance with a longer lighting time (18 h every day). However, a higher removal efficiency of NH4+–N and TN was obtained with a shorter lighting time (6–12 h every day). The lighting time showed a significance influence on the microbial community of the V. spinulosa growth system, and the influence was significantly different in different regions. Temperature and electrical conductivity were the main environmental impact factors for the microbial community under different lighting times. The abundances of Proteobacteria, Bacteroidota, and Verrucomicrobia exhibited a great positive correlation with each other and a strong positive correlation with the two factors. In addition, the lighting time had a strongly significant correlation with the physical and chemical characteristics of the water environment (p < 0.001) and a significant correlation with the growth characteristics of V. spinulosa (p < 0.05).
Machine Learning-Based Model Prediction of an Adsorption Desalination System and Investigation of the Impact of Parameters on the System’s Outputs
Authors: Zarei Taleb , Chatavi Masoud , Nazari Masoud , Amirfakhraei Amirhossein , Salimi Mohsen , Amidpour Majid
Published: December 2024

Adsorption desalination (AD) has emerged as a novel technique for desalination, which works cyclically and via switching, and various variables have an effect on its performance. This study uses machine learning procedures to present a model predictive approach for adsorption desalination systems. The adsorption desalination system will be modeled through the utilization of multilayer perceptron (MLP) and radial-based function (RBF) neural network approach hes. The purpose of this research is to provide valuable insights into optimizing system efficiency and expanding the applicability of adsorption desalination technologies by investigating the strengths and limitations of each model. Hence, the Specific Daily Water Production (SDWP), coefficient of performance (COP), and specific cooling power (SCP) are determined. There are 55 instances in the dataset, each with five input variables: temperatures of the evaporator and condenser, adsorption beds, and inlet hot saltwater. Additionally, three output variables are recorded: COP, SCP, and SDWP. The results of this investigation show that the MLP is more effective for simulating the AD system, and the Roots of Mean Square Error of COP, SCP, and SDWP are 0.002, 0.5921, and 0.0465, respectively. Then, the impact of input factors on output parameters was examined. The results show that the inlet hot saltwater temperature parameter affected the output parameters the most. Subsequently, the COP parameter is mainly affected by the adsorption beds, evaporator, and condenser temperature. The SCP parameter is primarily influenced by the inlet hot saltwater temperature, condenser temperature, temperatures of the two adsorption beds, and evaporator temperature.