bluuebunny/crossref_metadata_2025 huggingface dataset:
Integrated Analysis of Genomic and Genome-Wide Association Studies Identified Candidate Genes for Nutrigenetic Studies in Flavonoids and Vascular Health: Path to Precision Nutrition for (Poly)phenols
Authors: Ruskovska Tatjana , Postolov Filip , Milenkovic Dragan
Published: April 2024

Flavonoids exert vasculoprotective effects in humans, but interindividual variability in their action has also been reported. This study aims to identify genes that are associated with vascular health effects of flavonoids and whose polymorphisms could explain interindividual variability in response to their intake. Applying the predetermined literature search criteria, we identified five human intervention studies reporting positive effects of flavonoids on vascular function together with global genomic changes analyzed using microarray methods. Genes involved in vascular dysfunction were identified from genome-wide association studies (GWAS). By extracting data from the eligible human intervention studies, we obtained 5807 differentially expressed genes (DEGs). The number of identified upstream regulators (URs) varied across the studies, from 227 to 1407. The search of the GWAS Catalog revealed 493 genes associated with vascular dysfunction. An integrative analysis of transcriptomic data with GWAS genes identified 106 candidate DEGs and 42 candidate URs, while subsequent functional analyses and a search of the literature identified 20 top priority candidate genes: ALDH2, APOE, CAPZA1, CYP11B2, GNA13, IL6, IRF5, LDLR, LPL, LSP1, MKNK1, MMP3, MTHFR, MYO6, NCR3, PPARG, SARM1, TCF20, TCF7L2, and TNF. In conclusion, this integrated analysis identifies important genes to design future nutrigenetic studies for development of precision nutrition for polyphenols.
What Is Considered Healthy Eating? An Exploratory Study among College Students of Nutrition and Food Science
Authors: de Moraes Prata Gaspar Maria Clara , Soar Claudia , Aguilera Mari , Gomez Maria Clara , Celorio-Sardà Ricard , Comas-Basté Oriol , Vidal-Carou M. Carmen
Published: April 2024

In modern industrialized societies, the focus on healthy eating has increased significantly across multiple sectors, including the media, public policy, expert opinion, and public awareness. The aim of this research was to explore the perceptions of healthy eating and the barriers to adopting a healthy diet among undergraduate students in Human Nutrition and Dietetics (HND) and Food Science and Technology (FST) degrees in Spain. An exploratory and descriptive cross-sectional study was conducted using a qualitative and quantitative methodology and convenience sampling. Two focus groups and a questionnaire were utilized (300 participants from all academic years completed the survey). Differences in definitions of healthy eating and perceived barriers were found between genders and students at different stages of training (p < 0.05). In their understanding of healthy eating, the students placed importance on balance, variety, moderation, and individual factors. Although students considered it easy to follow a healthy diet, family’s eating habits, time availability, and emotional states were found to be the main barriers to the implementation of healthy practices. The obtained data supports the need to critically address perceptions of healthy eating throughout the training of nutrition and food science professionals. The insights obtained on the perceived barriers highlight the importance of considering both individual and environmental factors.
A Patented Dietary Supplement (Hydroxy-Methyl-Butyrate, Carnosine, Magnesium, Butyrate, Lactoferrin) Is a Promising Therapeutic Target for Age-Related Sarcopenia through the Regulation of Gut Permeability: A Randomized Controlled Trial
Authors: Rondanelli Mariangela , Gasparri Clara , Cavioni Alessandro , Sivieri Claudia , Barrile Gaetan Claude , Mansueto Francesca , Perna Simone
Published: April 2024

Adequate diet, physical activity, and dietary supplementation with muscle-targeted food for special medical purposes (FSMP) or dietary supplement (DS) are currently considered fundamental pillars in sarcopenia treatment. The aim of this study is to evaluate the effectiveness of a DS (containing hydroxy-methyl-butyrate, carnosine, and magnesium, for its action on muscle function and protein synthesis and butyrate and lactoferrin for their contribution to the regulation of gut permeability and antioxidant/anti-inflammation activity) on muscle mass (assessed by dual X-ray absorptiometry (DXA)), muscle function (by handgrip test, chair test, short physical performance battery (SPPB) test, and walking speed test), inflammation (tumor necrosis factor-alpha (TNF-a), C-reactive protein (CRP), and visceral adipose tissue (VAT)) and gut axis (by zonulin). A total of 59 participants (age 79.7 ± 4.8 years, body mass index 20.99 ± 2.12 kg/m2) were enrolled and randomly assigned to intervention (n = 30) or placebo (n = 28). The skeletal muscle index (SMI) significantly improved in the supplemented group compared to the placebo one, +1.02 (CI 95%: −0.77; 1.26), p = 0.001; a significant reduction in VAT was observed in the intervention group, −70.91 g (−13.13; −4.70), p = 0.036. Regarding muscle function, all the tests significantly improved (p = 0.001) in the supplemented group compared to the placebo one. CRP, zonulin, and TNF-alpha significantly decreased (p = 0.001) in intervention, compared to placebo, −0.74 mg/dL (CI 95%: −1.30; −0.18), −0.30 ng/mL (CI 95%: −0.37; −0.23), −6.45 pg/mL (CI 95%: −8.71; −4.18), respectively. This DS improves muscle mass and function, and the gut muscle has emerged as a new intervention target for sarcopenia.
Multi-Instrument Observation of the Ionospheric Irregularities and Disturbances during the 23–24 March 2023 Geomagnetic Storm
Authors: Tahir Afnan , Wu Falin , Shah Munawar , Amory-Mazaudier Christine , Jamjareegulgarn Punyawi , Verhulst Tobias G. W. , Ameen Muhammad Ayyaz
Published: April 2024

This work investigates the ionospheric response to the March 2023 geomagnetic storm over American and Asian sectors from total electron content (TEC), rate of TEC index, ionospheric heights, Swarm plasma density, radio occultation profiles of Formosat-7/Cosmic-2 (F7/C2), Fabry-Perot interferometer driven neutral winds, and E region electric field. During the storm’s main phase, post-sunset equatorial plasma bubbles (EPBs) extend to higher latitudes in the western American longitudes, showing significant longitudinal differences in the American sector. Over the Indian longitudes, suppression of post-sunset irregularities is observed, attributed to the westward prompt penetration electric field (PPEF). At the early recovery phase, the presence of post-midnight/near-sunrise EPBs till post-sunrise hours in the American sector is associated with the disturbance of dynamo-electric fields (DDEF). Additionally, a strong consistency between F7/C2 derived amplitude scintillation (S4) ≥ 0.5 and EPB occurrences is observed. Furthermore, a strong eastward electric field induced an increase in daytime TEC beyond the equatorial ionization anomaly crest in the American region, which occurred during the storm’s main phase. Both the Asian and American sectors exhibit negative ionospheric storms and inhibition of ionospheric irregularities at the recovery phase, which is dominated by the disturbance dynamo effect due to equatorward neutral winds. A slight increase in TEC in the Asian sector during the recovery phase could be explained by the combined effect of DDEF and thermospheric composition change. Overall, storm-time ionospheric variations are controlled by the combined effects of PPEF and DDEF. This study may further contribute to understanding the ionospheric responses under the influence of storm-phase and LT-dependent electric fields.
Arctic Thin Ice Detection Using AMSR2 and FY-3C MWRI Radiometer Data
Authors: Mäkynen Marko , Similä Markku
Published: April 2024

Thin ice with a thickness of less than half a meter produces strong salt and heat fluxes which affect deep water circulation and weather in the polar oceans. The identification of thin ice areas is essential for ship navigation. We have developed thin ice detection algorithms for the AMSR2 and FY-3C MWRI radiometer data over the Arctic Ocean. Thin ice (<20 cm) is detected based on the classification of the H-polarization 89–36-GHz gradient ratio (GR8936H) and the 36-GHz polarization ratio (PR36) signatures with a linear discriminant analysis (LDA) and thick ice restoration with GR3610H. The brightness temperature (TB) data are corrected for the atmospheric effects following an EUMETSAT OSI SAF correction method in sea ice concentration retrieval algorithms. The thin ice detection algorithms were trained and validated using MODIS ice thickness charts covering the Barents and Kara Seas. Thin ice detection is applied to swath TB datasets and the swath charts are compiled into a daily thin ice chart using 10 km pixel size for AMSR2 and 20 km for MWRI. On average, the likelihood of misclassifying thick ice as thin in the ATIDA2 daily charts is 7.0% and 42% for reverse misclassification. For the MWRI chart, these accuracy figures are 4% and 53%. A comparison of the MWRI chart to the AMSR2 chart showed a very high match (98%) for the thick ice class with SIC > 90% but only a 53% match for the thin ice class. These accuracy disagreements are due to the much coarser resolution of MWRI, which gives larger spatial averaging of TB signatures, and thus, less detection of thin ice. The comparison of the AMSR2 and MWRI charts with the SMOS sea ice thickness chart showed a rough match in the thin ice versus thick ice classification. The AMSR2 and MWRI daily thin ice charts aim to complement SAR data for various sea ice classification tasks.
Spatiotemporal Evolution Characteristics of 2022 Pakistan Severe Flood Event Based on Multi-Source Satellite Gravity Observations
Authors: Cui Lilu , Meng Jiacheng , Li Yu , An Jiachun , Zou Zhengbo , Zhong Linhao , Mao Yiru , Wu Guiju
Published: April 2024

In the summer of 2022, Pakistan experienced a severe flood event that brought great destruction to the local people and ecosystem. However, there is no comprehensive study on the process, spread and causes of this flood. Therefore, we combined multiple satellite gravity data, meteorological data, hydrological data, and satellite remote sensing data to conduct a thorough investigation and study of this flood. The results show that a 20-year time series of the terrestrial water storage change based multiple gravity data has the high accuracy and reliability, which is used for detecting the flood. The flood propagated through meteorological system (three months), agricultural system (six months) and terrestrial ecosystems (five months), respectively, and the two southern provinces (Balochistan and Sindh) are the most affected by the flood, whose flood severity is 6.955 and 9.557, respectively. The center of the severe flood is located at the border region between the above two province. The severe flood is attributed primarily to the global extreme climate events (La Niña and negative Indian Ocean Dipole events) that altered the transport path of water vapor in the Indian Ocean, causing large amounts of water vapor to converge over Pakistan, resulting in heavy precipitation, and secondarily to the melting of extensive glacier in the mountainous of northern Pakistan as a result of the high temperature in March-May 2022. The above results contribute to the understanding of the mechanism of the impact of extreme climate events on the regional climate, and provide some references for the study of severe floods.
Assessing the Spatiotemporal Variations in the Hydrological Response of the Qin River Basin in Loess Plateau, China
Authors: Guo Peng , Wang Yingjie , Yan Yilin , Wang Fei , Lyu Jiqiang , Ge Wenyan , Chen Hao , Jiao Juying
Published: April 2024

In recent decades, the hydrological processes on the Loess Plateau have undergone significant changes due to the combined effects of climate change and human activities. This study investigates the Qin River basin, the core area of the Loess Plateau. Between 1971 and 2000, the hydrometeorology of the flood season in the Qin basin on the Loess Plateau in China changed abruptly in 1982 and 1992. This study uses distributed hydrologic modeling and statistical analysis to distinguish the spatial and temporal impacts of climate change and human activities. The fastest dynamic changes in land use occurred in grassland and construction land, accounting for 0.36% and −0.1%, respectively, from 1982 to 1991. From 1992 to 2000, it was 0.29% and 0.3%, respectively. The increase in basin area where the Normalized Difference Vegetation Index increased was 95%. However, except for significant changes in runoff from 1981 to 1992, there were no significant changes in precipitation, runoff, and temperature during other flood seasons. During the two studied variation periods, from 1982 to 1991 and from 1992 to 2000, the contribution rate of climate change to flood season runoff (CClimate) decreased from 83.26% to 74.47%, while the contribution rate of human activity disturbance to flood season runoff (Chuman) increased from 16.74% to 25.53%. In terms of spatial distribution, from 1982 to 1991, areas with a Chuman > 50% were primarily concentrated in the upper reaches of the basin, while from 1992–2000, these areas shifted to the lower reaches. This study offers valuable insights for water resource planning and soil conservation measures in the Loess Plateau and similar arid regions worldwide, aiming to ensure water resource safety and sustainability in response to climate change and human interference.
Temperature Effects in AMSR2 Soil Moisture Products and Development of a Removal Method Using Data at Ascending and Descending Overpasses
Authors: Lu Minjiao , Hoang Kim Oanh , Kumarasiri Agampodi Deva Thisaru Nayanathara
Published: April 2024

Soil moisture is among the most essential variables in hydrology and earth science. Many satellite missions, such as AMSR-E/2, have been launched to observe it in broader spatial coverage to overcome the shortage of in situ observations. However, the satellite soil moisture products have been reported to comprise errors caused by the so-called “temperature effects” widely observed in dielectrically measured in situ volumetric soil water content (SWC). In this work, we confirmed the existence of these errors in AMSR2 soil moisture products. A new algorithm was developed to remove these errors using satellite data at ascending and descending overpasses. The application of this algorithm to both satellite and in situ data of SWC and soil temperature at the Mongolia site shows that the difference between SWC values at ascending and descending overpasses caused by temperature effects is effectively removed. We assess the impact of this removal method on satellite data by comparing it with in situ data, utilizing metrics such as the correlation coefficient and other widely adopted evaluation methods. It is shown that the difference between the original and corrected in situ SWC is much smaller than that between AMSR2 and in situ SWC, either corrected or not. The results indicate that the metric values between the corrected AMSR2 and in situ SWC, after removing apparent differences caused by temperature effects, slightly improved compared to those between the original AMSR2 and in situ SWC. Though these findings imply that the removed errors may not be the most dominant, considering the current significant difference between AMSR2 and in situ SWC, the removal makes the ascending and descending data have close characteristics. It may allow using data at both ascending and descending overpasses and double the temporal resolution of AMSR2 SWC data.
Toward Synthetic Physical Fingerprint Targets
Authors: Ruzicka Laurenz , Strobl Bernhard , Bergmann Stephan , Nolden Gerd , Michalsky Tom , Domscheit Christoph , Priesnitz Jannis , Blümel Florian , Kohn Bernhard , Heitzinger Clemens
Published: April 2024

Biometric fingerprint identification hinges on the reliability of its sensors; however, calibrating and standardizing these sensors poses significant challenges, particularly in regards to repeatability and data diversity. To tackle these issues, we propose methodologies for fabricating synthetic 3D fingerprint targets, or phantoms, that closely emulate real human fingerprints. These phantoms enable the precise evaluation and validation of fingerprint sensors under controlled and repeatable conditions. Our research employs laser engraving, 3D printing, and CNC machining techniques, utilizing different materials. We assess the phantoms’ fidelity to synthetic fingerprint patterns, intra-class variability, and interoperability across different manufacturing methods. The findings demonstrate that a combination of laser engraving or CNC machining with silicone casting produces finger-like phantoms with high accuracy and consistency for rolled fingerprint recordings. For slap recordings, direct laser engraving of flat silicone targets excels, and in the contactless fingerprint sensor setting, 3D printing and silicone filling provide the most favorable attributes. Our work enables a comprehensive, method-independent comparison of various fabrication methodologies, offering a unique perspective on the strengths and weaknesses of each approach. This facilitates a broader understanding of fingerprint recognition system validation and performance assessment.
Robust Tracking Control of Wheeled Mobile Robot Based on Differential Flatness and Sliding Active Disturbance Rejection Control: Simulations and Experiments
Authors: Abadi Amine , Ayeb Amani , Labbadi Moussa , Fofi David , Bakir Toufik , Mekki Hassen
Published: April 2024

This paper proposes a robust tracking control method for wheeled mobile robot (WMR) against uncertainties, including wind disturbances and slipping. Through the application of the differential flatness methodology, the under-actuated WMR model is transformed into a linear canonical form, simplifying the design of a stabilizing feedback controller. To handle uncertainties from wheel slip and wind disturbances, the proposed feedback controller uses sliding mode control (SMC). However, increased uncertainties lead to chattering in the SMC approach due to higher control inputs. To mitigate this, a boundary layer around the switching surface is introduced, implementing a continuous control law to reduce chattering. Although increasing the boundary layer thickness reduces chattering, it may compromise the robustness achieved by SMC. To address this challenge, an active disturbance rejection control (ADRC) is integrated with boundary layer sliding mode control. ADRC estimates lumped uncertainties via an extended state observer and eliminates them within the feedback loop. This combined feedback control method aims to achieve practical control and robust tracking performance. Stability properties of the closed-loop system are established using the Lyapunov theory. Finally, simulations and experimental results are conducted to compare and evaluate the efficiency of the proposed robust tracking controller against other existing control methods.
Early-Stage Ice Detection Utilizing High-Order Ultrasonic Guided Waves
Authors: Rekuvienė Regina , Samaitis Vykintas , Jankauskas Audrius , Sadaghiani Abdolali K. , Saeidiharzand Shaghayegh , Koşar Ali
Published: April 2024

Ice detection poses significant challenges in sectors such as renewable energy and aviation due to its adverse effects on aircraft performance and wind energy production. Ice buildup alters the surface characteristics of aircraft wings or wind turbine blades, inducing airflow separation and diminishing the aerodynamic properties of these structures. While various approaches have been proposed to address icing effects, including chemical solutions, pneumatic systems, and heating systems, these solutions are often costly and limited in scope. To enhance the cost-effectiveness of ice protection systems, reliable information about current icing conditions, particularly in the early stages, is crucial. Ultrasonic guided waves offer a promising solution for ice detection, enabling integration into critical structures and providing coverage over larger areas. However, existing techniques primarily focus on detecting thick ice layers, leaving a gap in early-stage detection. This paper proposes an approach based on high-order symmetric modes to detect thin ice formation with thicknesses up to a few hundred microns. The method involves measuring the group velocity of the S1 mode at different temperatures and correlating velocity changes with ice layer formation. Experimental verification of the proposed approach was conducted using a novel group velocity dispersion curve reconstruction method, allowing for the tracking of propagating modes in the structure. Copper samples without and with special superhydrophobic multiscale coatings designed to prevent ice formation were employed for the experiments. The results demonstrated successful detection of ice formation and enabled differentiation between the coated and uncoated cases. Therefore, the proposed approach can be effectively used for early-stage monitoring of ice growth and evaluating the performance of anti-icing coatings, offering promising advancements in ice detection and prevention for critical applications.
A Design Method for an SVM-Based Humidity Sensor for Grain Storage
Authors: Liu Lining , Song Chengbao , Zhu Ke , Liu Pingzeng
Published: April 2024

One of the crucial factors in grain storage is appropriate moisture content, which plays a significant role in reducing storage losses and ensuring quality. However, currently available humidity sensors on the market fail to meet the demands of modern large-scale grain storage in China in terms of price, size, and ease of implementation. Therefore, this study aims to develop an economical, efficient, and easily deployable grain humidity sensor suitable for large-scale grain storage environments. Simultaneously, it constructs humidity calibration models applicable to three major grain crops: millet, rice, and wheat. Starting with the probe structure, this study analyzes the ideal probe structure for grain humidity sensors. Experimental validations are conducted using millet, rice, and wheat as experimental subjects to verify the accuracy of the sensor and humidity calibration models. The experimental results indicate that the optimal length of the probe under ideal conditions is 0.67 m. Humidity calibration models for millet, rice, and wheat are constructed using SVM models, with all three models achieving a correlation coefficient R2 greater than 0.9. The measured data and model-calculated data show a linear relationship, closely approximating y = x, with R2 values of all three fitted models above 0.9. In conclusion, this study provides reliable sensor technological support for humidity monitoring in large-scale grain storage and processing, with extensive applications in grain storage and grain safety management.
Identifying the Effect of Cognitive Motivation with the Method Based on Temporal Association Rule Mining Concept
Authors: Phukhachee Tustanah , Maneewongvatana Suthathip , Chaiyanan Chayapol , Iramina Keiji , Kaewkamnerdpong Boonserm
Published: April 2024

Being motivated has positive influences on task performance. However, motivation could result from various motives that affect different parts of the brain. Analyzing the motivation effect from all affected areas requires a high number of EEG electrodes, resulting in high cost, inflexibility, and burden to users. In various real-world applications, only the motivation effect is required for performance evaluation regardless of the motive. Analyzing the relationships between the motivation-affected brain areas associated with the task’s performance could limit the required electrodes. This study introduced a method to identify the cognitive motivation effect with a reduced number of EEG electrodes. The temporal association rule mining (TARM) concept was used to analyze the relationships between attention and memorization brain areas under the effect of motivation from the cognitive motivation task. For accuracy improvement, the artificial bee colony (ABC) algorithm was applied with the central limit theorem (CLT) concept to optimize the TARM parameters. From the results, our method can identify the motivation effect with only FCz and P3 electrodes, with 74.5% classification accuracy on average with individual tests.
Enhancing Sensitivity in Gas Detection: Porous Structures in Organic Field-Effect Transistor-Based Sensors
Authors: Lim Soohwan , Nguyen Ky Van , Lee Wi Hyoung
Published: April 2024

Gas detection is crucial for detecting environmentally harmful gases. Organic field-effect transistor (OFET)-based gas sensors have attracted attention due to their promising performance and potential for integration into flexible and wearable devices. This review examines the operating mechanisms of OFET-based gas sensors and explores methods for improving sensitivity, with a focus on porous structures. Researchers have achieved significant enhancements in sensor performance by controlling the thickness and free volume of the organic semiconductor layer. Additionally, innovative fabrication techniques like self-assembly and etching have been used to create porous structures, facilitating the diffusion of target gas molecules, and improving sensor response and recovery. These advancements in porous structure fabrication suggest a promising future for OFET-based gas sensors, offering increased sensitivity and selectivity across various applications.
A Combined Persistence and Physical Approach for Ultra-Short-Term Photovoltaic Power Forecasting Using Distributed Sensors
Authors: Malinkovich Yakov , Sitbon Moshe , Lineykin Simon , Dagan Kfir Jack , Baimel Dmitry
Published: April 2024

This paper presents a novel method for forecasting the impact of cloud cover on photovoltaic (PV) fields in the nowcasting term, utilizing PV panels as sensors in a combination of physical and persistence models and integrating energy storage system control. The proposed approach entails simulating a power network consisting of a 22 kV renewable energy source and energy storage, enabling the evaluation of network behavior in comparison to the national grid. To optimize computational efficiency, the authors develop an equivalent model of the PV + energy storage module, accurately simulating system behavior while accounting for weather conditions, particularly cloud cover. Moreover, the authors introduce a control system model capable of responding effectively to network dynamics and providing comprehensive control of the energy storage system using PID controllers. Precise power forecasting is essential for maintaining power continuity, managing overall power-system ramp rates, and ensuring grid stability. The adaptability of our method to integrate with solar fencing systems serves as a testament to its innovative nature and its potential to contribute significantly to the renewable energy field. The authors also assess various scenarios against the grid to determine their impact on grid stability. The research findings indicate that the integration of energy storage and the proposed forecasting method, which combines physical and persistence models, offers a promising solution for effectively managing grid stability.
Exploration-Based Planning for Multiple-Target Search with Real-Drone Results
Authors: Yousuf Bilal , Lendek Zsófia , Buşoniu Lucian
Published: April 2024

Consider a drone that aims to find an unknown number of static targets at unknown positions as quickly as possible. A multi-target particle filter uses imperfect measurements of the target positions to update an intensity function that represents the expected number of targets. We propose a novel receding-horizon planner that selects the next position of the drone by maximizing an objective that combines exploration and target refinement. Confidently localized targets are saved and removed from consideration along with their future measurements. A controller with an obstacle-avoidance component is used to reach the desired waypoints. We demonstrate the performance of our approach through a series of simulations as well as via a real-robot experiment in which a Parrot Mambo drone searches from a constant altitude for targets located on the floor. Target measurements are obtained on-board the drone using segmentation in the camera image, while planning is done off-board. The sensor model is adapted to the application. Both in the simulations and in the experiments, the novel framework works better than the lawnmower and active-search baselines.
Greater than the Sum of Its Parts: Combining Entrepreneurial and Sustainable Competencies in Entrepreneurship Education
Authors: Planck Sebastian , Wilhelm Sonja , Kobilke Johanna , Sailer Klaus
Published: April 2024

Discussions about sustainability and entrepreneurship are often an “either/or” discourse. Many higher-education institutions offer sustainability education programs with the aim of enabling students to think and act sustainably without concrete tools for change. Similarly, many offerings in entrepreneurship fail to address sustainability issues. This article assumes a qualitative, constructivist, systems thinking approach to theorize and analyze the relationships between entrepreneurship and sustainability competencies and makes three contributions to theory and practice. First, it provides a thematic analysis of two important European competence frameworks—for sustainability (GreenComp) and entrepreneurial competencies (EntreComp)—and delineates their relationships. Second, through a case study of an experiential educational format, it offers three educational tools that integrate sustainability and entrepreneurial competencies. Third, it contributes to the growing field of research that combines sustainability and entrepreneurship education. The results of this paper are relevant for policymakers who want to combine sustainability and entrepreneurship in education, as well as for educators looking for methods to combine both competence frameworks.
Spatial Layout of Vegetation Buffer Zones around Water Bodies to Avoid Non-Point Source Pollution in a Mining Area
Authors: Wang Haochen , Lei Shaogang , Zhang Mian , Xu Yufan , Duan Lei
Published: April 2024

The riparian vegetation buffer zone plays an important role in the prevention and control of non-point source pollution, and consideration should be given to selecting one with a lower cost and better effect. The SWAT model was used to simulate the regulation ability of riparian vegetation buffer zone layout on runoff, nitrogen, and phosphorus in the Jiawang Basin, and five different vegetation buffer zone layout scenarios were set up. The results showed that (1) the SWAT model has good applicability in simulating runoff and water quality in the Jiawang Basin; (2) the reduction rates of runoff, total nitrogen, and total phosphorus in continuous forest riverbank buffer zones reached 2.46%, 6.63%, and 9.18%, and their regulatory effects were better than those in grasslands; (3) there is not much difference in the inhibitory effect of forest and grassland on total nitrogen, but the discontinuous forest buffer zone has a better reduction effect on total phosphorus than grassland. Therefore, in the actual arrangement of vegetation buffer zones, it should be tailored to local conditions to achieve ideal non-point source pollution prevention and control effects at a lower cost.
Image-Based Phenotyping Study of Wheat Growth and Grain Yield Dependence on Environmental Conditions and Nitrogen Usage in a Multi-Year Field Trial
Authors: Miklavcic Stanley J. , Chopin Joshua , Laga Hamid
Published: April 2024

As the global population and resource scarcity simultaneously increase, the pressure on plant breeders and growers to maximise the effectiveness of their operations is immense. In this article, we explore the usefulness of image-based data collection and analysis of field experiments consisting of multiple field sites, plant varieties, and treatments. The goal of this approach is to determine whether the noninvasive acquisition and analysis of image data can be used to find relationships between the canopy traits of field experiments and environmental factors. Our results are based on data from three field trials in 2016, 2017, and 2018 in South Australia. Image data were supplemented by environmental data such as rainfall, temperature, and soil composition in order to explain differences in growth and the development of plants across field trials. We have shown that the combination of high-throughput image-based data and independently recorded environmental data can reveal valuable connections between the variables influencing wheat crop growth; meanwhile, further studies involving more field trials under different conditions are required to test hypotheses and draw statistically significant conclusions. This work highlights some of the more responsive traits and their dependencies.
Evolutionary Game Analysis of Green Supply Chain Management Diffusion under Environmental Regulation
Authors: Qi Kai , Guo Xinyuan , Guan Xinying , Yang Zhi
Published: April 2024

The continuous deterioration of the ecological environment and the increasing scarcity of resources have posed a serious challenge to the survival and development of human beings, and the implementation of green supply chain management (GSCM) in this context is an effective means to ensure the sustainable development of society and the economy. In order to seek the optimal strategy of evolutionary game in the implementation of green supply chain management and explore the influence of environmental regulation intensity and public preference degree on the evolution process of green supply chain management diffusion development, this paper takes the study of green supply chain management diffusion as the core innovation point, and under the premise of environmental regulation, selects the government, the core enterprise, and the public as the participating bodies of green supply chain management diffusion, and uses the theory of evolutionary game to construct a diffusion model of green supply chain management. Using evolutionary game theory to construct a diffusion model, and with the help of MATLAB and other mathematical tools for numerical simulation analysis, we discuss the diffusion of the green supply chain and derive the optimal combination strategy. The results of the study show that: (1) there are four evolutionary stable states in the process of green supply chain management diffusion: preliminary diffusion, extinction, semi-diffusion, and full diffusion; (2) it will be beneficial for the government to promote the evolutionary diffusion of green supply chain management by implementing a higher intensity of pollution tax policy while implementing green supply chain incentive strategies; (3) the government, while implementing environmental regulation policies, should also pay attention to the guidance of the public’s awareness of environmental friendliness and greenness, and focus on the role of the comprehensive strategy selection of the three parties of the game in reaching the optimal state. The conclusions of the study provide theoretical guidance and decision support for the implementation and diffusion of green supply chain management under environmental regulation.
Combining Zinc Biofortification and Native Trichoderma Inoculation Strategies for Subterranean Clover
Authors: García-Latorre Carlos , Velázquez Rocío , Hernández Alejandro , Tejero Paula , Poblaciones Maria J.
Published: April 2024

Using beneficial microorganisms along with sustainable strategies such as agronomic biofortification offers eco-friendly alternatives to combat climate change in ecosystems like dehesas. This study analyzes the combined effects of four wild Trichoderma spp. isolated from Extremadura, Spain (T. koningiopsis, two T. gamsii, and T. koningii, with negative and positive controls) and four Zn biofortification treatments (no Zn application; soil application of 5 mg of ZnSO4·7H2O per kg of soil, labeled soil Zn; two foliar applications of 5 mL 0.5% ZnSO4·7H2O, labeled foliar Zn; and soil + foliar combination, labeled SF) on Trifolium subterraneum performance. The combination of T. koningiopsis and T. gamsii with foliar Zn improved plant growth by up to 34.4%. Zinc accumulation was about 30% higher when T. gamsii and T. koningii were applied with SF, and their inoculation resulted in a 2.5-fold increase in ash. Trichoderma spp. affected nodulation differently; both T. gamsii inhibited nodulation by 24%, whereas neither T. koningiopsis nor T. koningii showed differences from the controls. These results highlight the potential of combining beneficial microorganisms with biofortification strategies to address nutrient deficiencies and improve agricultural sustainability. However, the complex interactions between both factors underscore the importance of strain selection and call for further research to optimize application strategies and elucidate underlying mechanisms.
Sustainable Infrastructure Maintenance: Crack Depth Detection in Tunnel Linings via Natural Temperature Variations and Infrared Imaging
Authors: Gu Wenchuan , Liu Xuezeng , Li Zhen
Published: April 2024

In this research, we propose the use of infrared detection methods for identifying cracks in the tunnel lining of concrete structures. Through thermal simulation experiments on pre-existing cracks, we investigate the heat conduction patterns in cracked linings under natural temperature variations. The influence of temperature differences inside and outside the lining, crack depth, and crack width on the temperature distribution on the inner surface of the lining is analyzed by using a controlled variable approach. This exploration aims to assess the feasibility and applicable conditions of using infrared thermal imaging technology for detecting lining crack defects, contributing to sustainable maintenance of infrastructure. We further validate the experimental approach through numerical simulations. Considering the temperature distribution on the inner surface of the lining, it becomes feasible to comprehensively determine the location and depth of cracks. This offers a novel and rapid inspection method for tunnel lining cracks, thereby enhancing the sustainability of tunnel infrastructure.
Dual Substitution of Rural Energy Structure in China: Its Evolutionary Characteristics and Carbon Decoupling Effects
Authors: Liu Chuang , Zhang Hengshuo , Yan Bing , Qian Xuesheng
Published: April 2024

Accelerating the transformation of the rural energy structure is an indispensable part of energy transformation in developing countries. In this novel study, the transformation effect of China’s rural energy structure from 2001 to 2020 was evaluated. Further, this paper also identified the decoupling state between the rural energy structure transition and carbon emissions, and decomposed the spatial–temporal effects of rural carbon decoupling through efficiency measures. According to the survey, the dual substitution index of the rural energy structure in China increased from 0.466 to 1.828, and showed a decreasing trend in spatial distribution from the east to the central and western regions. Economic development and climate characteristics have become important influencing factors for the dual substitution of the rural energy structure. The decoupling relationship between the dual substitution of the rural energy structure and carbon emissions was mainly characterized in the strong decoupling, expansion negative decoupling, and strong negative decoupling states. Regional imbalances have deepened as the efficiency of rural energy carbon decoupling has gradually increased. The annual average efficiency of rural energy carbon decoupling in a dynamic perspective has increased by 10.579%, and the dual substitution of the energy structure has a significant driving effect on rural carbon reduction.
Environmental Education: A Systematic Review on the Use of Digital Tools for Fostering Sustainability Awareness
Authors: Hajj-Hassan Mira , Chaker Rawad , Cederqvist Anne-Marie
Published: April 2024

Recently, sustainable development practices have increased attention as climate change and environmental impacts have increased. Interventions to encourage sustainability awareness are developing, so fostering them through education is crucial. Evidence-based studies conducted in this field have suggested the use of different digital tools to promote environmental learning gains and to foster better sustainability awareness among students. Following the PRISMA method, we found 21 articles published between 2013 and 2023 showing an interest in the use of digital tools in environmental education to foster sustainability awareness among learners. Findings indicate that virtual reality tools and climate change topics are the most trending in this research area. Further, the results show a positive impact of the use of digital tools on students’ concern for the sustainability of the planet.
Application of Radar-Based Precipitation Data Improves the Effectiveness of Urban Inundation Forecasting
Authors: Tri Doan Quang , Thu Nguyen Vinh , Hoa Bui Thi Khanh , Nguyen-Thi Hoang Anh , Hoa Vo Van , Hue Le Thi , Dat Dao Tien , Pham Ha T. T.
Published: April 2024

Using radar to estimate and forecast precipitation as input for hydrological models has become increasingly popular in recent years because of its superior spatial and temporal simulation compared with using rain gauge data. This study used radar-based quantitative precipitation estimation (QPE) to select the optimal parameter set for the MIKE URBAN hydrological model and radar-based quantitative precipitation forecasting (QPF) to simulate inundation in Nam Dinh city, Vietnam. The results show the following: (1) radar has the potential to improve the modeling and provide the data needed for real-time smart control if proper bias adjustment is obtained and the risk of underestimated flows after heavy rain is minimized, and (2) the MIKE URBAN model used to calculate two simulation scenarios with rain gauge data and QPE data showed effectiveness in combining the application of radar-based precipitation for the forecasting and warning of urban floods in Nam Dinh city. The results in Scenario 2 with rainfall forecast data from radar provide better simulation results. The average relative error in Scenario 2 is 9%, while the average relative error in Scenario 1 is 15%. Using the grid radar-based precipitation forecasting as input data for the MIKE URBAN model significantly reduces the error between the observed water depth and the simulated results compared with the case using an input rain gauge measured at Nam Dinh station (the difference in inundation level of Scenario 2 using radar-based precipitation is 0.005 m, and it is 0.03 m in Scenario 1). The results obtained using the QPE and QPF radar as input for the MIKE URBAN model will be the basis for establishing an operational forecasting system for the Northern Delta and Midland Regional Hydro-Meteorological Center, Viet Nam Meteorological and Hydrological Administration.
Sustainable Foods: Consumer Opinions and Behaviour towards Organic Fruits in Poland
Authors: Kazimierczak Renata , Obidzińska Justyna , Szumigaj Bartosz , Dobrowolski Hubert , Rembiałkowska Ewa
Published: April 2024

By producing high quality food with a low environmental impact, organic farming plays an essential role in developing sustainable food systems. Over time, consumer interest in organic food is systematically growing, which results in a generally positive attitude towards organic products. Many studies that are devoted to analysing organic food consumers’ behaviour aim to generalise the studied trends to the population of a given country or region. Given the varying rates of organic market development between countries, there is a need for more narrowly focused research, which could more profoundly facilitate local development of organic market. The aim of this study was to investigate the opinions of Polish consumers about organic fruit and to identify the socioeconomic and sociodemographic determinants of the propensity to choose and purchase organic fruit. Respondents were recruited via a market research agency using a consumer access panel. To collect responses, a formal, structured questionnaire was developed and distributed using the CAWI method. The general acceptance of price increases for organic apples amounts to less than around 30% (89% of responses). The effect of income and package size tend to interact with regard to the purchase preference of apples (p < 0.001). The highest frequency of organic fruit purchases were indicated for physical stores, in particular supermarkets (5.35 times/month, 95%CI). A relationship between willingness to consume organic fruits and the self-described economic situation (p = 0.005), as well as true household income (p = 0.007), has been shown. A relationship between the frequency of organic fruit purchases and the number of household members (p = 0.006), as well as number of household members under the age of 18 (p = 0.011), has also been shown. Marketing techniques for organic products should emphasize family welfare and be directed at younger consumers, especially at retail outlets where customers are most likely to buy them, namely physical supermarkets, local grocery stores and discount stores.
The Decolonisation of Climate Change and Environmental Education in Africa
Authors: Mbah Marcellus Forh , Ezegwu Chidi
Published: April 2024

This study examines key considerations for the decolonisation of climate change and environmental education (CCEE) in Africa. It draws on insights into epistemic inclusivity to systematically assess journal articles that drew on primary studies and were published between 2015 and 2022. The findings of the review depict that there are persistent epistemic exclusion and alienation of Indigenous and local knowledge (ILK) in CCEE. This lack of recognition of ILK contributes to negatively affecting the quality of what is learnt in educational centres across Africa as learners’ lived experiences in their socio-cultural environments are not contextualised to enhance the relatability of the subjects of their learning. Decolonisation efforts must address exclusion and alienation and promote inclusion and epistemic agency. This paper captures various strategies to achieve these in the continent, as well as some opportunities and challenges. It maintains that multidimensional approaches to decolonisation are required to promote African-centred climate change and environment education. This includes the interrogation of existing theories and depictions of subjugation of ILK, as well as seeking ways to halt or mitigate the prevalence of ongoing epistemic exclusion in different educational contexts and locations. It also requires policymakers and education managers to commit to developing epistemically inclusive education policies, curricula, and learning frameworks that highlight the significance of place-based knowledge.
Exploring the Dynamic Relationships between Agricultural Production and Environmental Pollution: Evidence from a GMM-SYS Model in the Three Seas Initiative (3SI)
Authors: Suproń Błażej , Myszczyszyn Janusz
Published: April 2024

The Three Seas Initiative (3SI) is still an under-researched area and is particularly important due to historical circumstances and economic backwardness. A study was carried out to assess the impact of renewable energy and production made by the agricultural sector on CO2 emissions in 3SI countries between 2008 and 2020. The study used panel data analysis based on the two-step system’s generalized method of moments (GMM) and the Dumitrescu–Hurlin panel causality test. The results show that a 1% increase in the value added generated by agriculture increased CO2 emissions in the countries studied by 0.11%. In contrast, a 1% increase in GDP led to a 0.29% increase in CO2 emissions. Conversely, when renewable energy consumption increased by 1%, CO2 emissions fell by 0.25% in the countries studied. One way to reduce CO2 emissions from agricultural production in the short term is to increase the share of renewables, which incidentally is in line with EU action.