bluuebunny/crossref_metadata_2025 huggingface dataset:
Encapsulation of Nanocrystals in Mannitol-Based Inhalable Microparticles via Spray-Drying: A Promising Strategy for Lung Delivery of Curcumin
Authors: Casula Luca , Craparo Emanuela Fabiola , Lai Eleonora , Scialabba Cinzia , Valenti Donatella , Schlich Michele , Sinico Chiara , Cavallaro Gennara , Lai Francesco
Published: December 2024

Background/Objectives: Curcumin is well known for its great anti-inflammatory and antioxidant efficacy, representing a potential strategy for the treatment of respiratory disorders. However, several drawbacks, such as chemical instability, poor water solubility and rapid metabolism, result in low bioavailability, limiting its clinical applications. In this study, curcumin nanocrystals were incorporated into mannitol-based microparticles to obtain an inhalable dry powder. Methods: A curcumin nanosuspension was produced by wet-ball media milling and thoroughly characterized. Spray drying was then used to produce mannitol microparticles incorporating curcumin nanocrystals. In vitro release/dissolution tests were carried out in simulated lung fluids, and the aerosolization properties were evaluated using a Next-Generation Impactor (NGI, Apparatus E Ph. Eu.). Results: The incorporation of curcumin nanocrystals into mannitol-based microparticles influenced their morphological properties, such as geometric diameters, and flowability. Despite these changes, nebulization studies confirmed optimal MMAD values (<5 µm), while multi-step dissolution/release studies evidenced the influence of mannitol. Conclusions: The developed curcumin nanocrystals-loaded mannitol microparticles show promise as an inhalable treatment for respiratory diseases, combining effective aerodynamic properties with controlled drug release.
Isolation, Characterization, and Proteomic Analysis of Crude and Purified Extracellular Vesicles Extracted from Fusarium oxysporum f. sp. cubense
Authors: Ahmad Mudassar , Liu Yushan , Huang Shiyi , Huo Yile , Yi Ganjun , Liu Chongfei , Jamil Wajeeha , Yang Xiaofang , Zhang Wei , Li Yuqing , Xiang Dandan , Huoqing Huang , Liu Siwen , Wang Wei , Li Chunyu
Published: December 2024

Extracellular vesicles (EVs) produced by Fusarium oxysporum f. sp. cubense (Foc) play vital roles in plant–pathogen interactions; however, the isolation of purified Foc TR4-EVs and their pathogenicity and proteomic profiles are not well studied. This study aims to isolate and characterize purified Foc TR4-EVs and compare their pathogenic effects and protein profiles with crude TR4-EVs. Foc TR4-EVs were isolated using ultracentrifugation and purified by iodixanol gradient centrifugation. After characterization and evaluation of the pathogenicity effects on banana leaves, LC-MS/MS was performed to conduct the proteomics assay. Results indicated that Fraction 2 EVs exhibited clearer spherical structures (TEM), excessive abundance (1.70 × 109 particles/mL), greater intensity (400 a.u), mean size (154.5 nm), moderate protein content (333.16 ng/µL), and protein profile (25–77 kDa), which were superior to Fractions 1, 3, and crude EVs. Crude EVs displayed significant background interference with EV structures (TEM), highest abundance (2.11 × 109 particles/mL), lower intensity (7.0 a.u), higher protein content (528.33 ng/µL), and higher molecular weight proteins (55–70 kDa) compared to gradient EVs. A non-significant biocontrol effect of Foc-EVs on the growth of TR4 spores was observed. Pathogenicity assays revealed that crude EVs caused the largest (2.805 cm2), while Fraction 2 (1.386 cm2) and Fraction 3 (1.255 cm2) resulted in moderate lesions on banana leaves. Proteomic analysis identified 807 unique proteins in Fraction 2, enriched in pathways related to EV trafficking and signaling. In comparison, crude EVs contained 179 unique non-EV proteins related to metabolism and secondary metabolites, indicating that non-EV proteins of crude EVs also influence the pathogenicity observed in banana leaves. This study emphasizes the importance of EV purification, with Fraction 2 being a critical focus for future research on Foc EV pathogenicity.
The Agronomic Potential of the Invasive Brown Seaweed Rugulopteryx okamurae: Optimisation of Alginate, Mannitol, and Phlorotannin Extraction
Authors: Rincón-Cervera Miguel A. , de Burgos-Navarro Irene , Chileh-Chelh Tarik , Belarbi El-Hassan , Álvarez-Corral Miriam , Carmona-Fernández Minerva , Ezzaitouni Mohamed , Guil-Guerrero José L.
Published: December 2024

Rugulopteryx okamurae is an invasive brown macroalga that has recently proliferated in the western Mediterranean Sea, causing significant environmental challenges. This alga, however, contains valuable bioactive compounds—alginate, mannitol, and phlorotannins—that can serve as biofertilizers to promote plant growth and aid in bioremediation of degraded or contaminated soils. This study focused on optimizing the extraction of these compounds from R. okamurae, transforming an ecological issue into a beneficial resource. Algae samples collected from the Spanish Mediterranean coast were processed through a randomized factorial response surface design. Extraction conditions varied by time, temperature, algae-to-solvent ratio, and ethanol-to-water ratio to determine optimal yields. The highest yields achieved were 29.4, 11.9, and 0.35 g/100 g for alginate, mannitol, and phlorotannin’s under extraction conditions of 6, 6, and 3 h; 58.8, 60.0, and 60.0 °C; and an algae:solvent ratio of 1:50, 2:45, and 1.40 g/mL, respectively. Characterization of the extracted sodium alginate using 1H-NMR, FTIR, and high-resolution electron microscopy confirmed its high purity and typical morphological features. This study highlights a sustainable approach to mitigating the invasive spread of R. okamurae while supporting soil health and sustainable agriculture. Harnessing this invasive species’ biofertilizer potential provides a dual solution, aiding marine ecosystem conservation and developing eco-friendly agricultural practices.
Achieving 3-D Structural Uniformity in Cellulose Gel Beads via Salt Screening
Authors: Garnett Matthew T. , Seyed Esfahani Seyed Armin , Yingst Andrew P. , May Luke T. , Alexander Symone L. M.
Published: December 2024

Cellulose microgel beads fabricated using the dropping technique suffer from structural irregularity and mechanical variability. This limits their translation to biomedical applications that are sensitive to variations in material properties. Ionic salts are often uncontrolled by-products of this technique, despite the known effects of ionic salts on cellulose assembly. In this study, the coagulation behavior of cellulose/salt solutions was explored as a way to combat these challenges. An ionic salt (NaCl) was added to a cellulose solution (cellulose/NaOH/urea) prior to coagulation in a hydrochloric acid bath. Quantification of the bead geometry and characterization of the pore architecture revealed that balancing the introduction of salt with the resultant solution viscosity is more effective at reducing structural variability and diffusion limitations than other pre-gelling techniques like thermal gelation. Three-dimensional visualization of the internal pore structure of neat cellulose, thermo-gel, and salt-gel beads revealed that adding salt to the solution is the most effective way to achieve 3-D structural uniformity throughout the bead. Coupled with nanoindentation, we confirmed that the salt produced during coagulation plays a critical role in mechanical variability, and that adding salt to the solution before dropping into the coagulation bath completely screens this effect, producing uniform microgel beads with reproducible mechanical properties.
Light-Powered Self-Translation of an Asymmetric Friction Slider Using a Liquid Crystal Elastomer String Oscillator
Authors: Ge Dali , Duan Jiangtao , Bao Wu , Liang Haiyi
Published: December 2024

In recent years, there have been many studies focused on improving the performance of active materials; however, applying these materials to active machines still presents significant challenges. In this study, we introduce a light-powered self-translation system for an asymmetric friction slider using a liquid crystal elastomer (LCE) string oscillator. The self-translation system was composed of a hollow slide, two LCE fibers, and a mass ball. Through the evolution of photothermal-induced contraction, we derived the governing equations for the system. Numerical simulations revealed two distinct motion modes: the static mode and the self-translation mode. As the mass ball moved, the LCE fibers alternated between illuminated and non-illuminated states, allowing them to effectively harvest light energy to compensate for the energy dissipation within the system. Unlike traditional self-oscillating systems that oscillate around a fixed position, the asymmetric friction enabled the slider to advance continuously through the oscillator’s symmetric self-sustained oscillation. Furthermore, we explored the critical conditions necessary for initiating self-translation as well as key system parameters that influence the frequency and amplitude of the oscillator and average speed of the slider. This self-translation system, with its simple design and ease of control, holds promising potential for applications in various fields including soft robotics, energy harvesting, and active machinery.
Nitrogen-Doped Diamond-like Coatings for Long-Term Enhanced Cell Adhesion on Electrospun Poly(ε-caprolactone) Scaffold Surfaces
Authors: Goreninskii Semen , Yuriev Yuri , Runts Artem , Prosetskaya Elisaveta , Melnik Evgeniy , Tran Tuan-Hoang , Sviridova Elizaveta , Golovkin Alexey , Mishanin Alexander , Bolbasov Evgeny
Published: December 2024

Electrospun poly(ε-caprolactone) (PCL)-based scaffolds are widely used in tissue engineering. However, low cell adhesion remains the key drawback of PCL scaffolds. It is well known that nitrogen-doped diamond-like carbon (N-DLC) coatings deposited on the surface of various implants are able to enhance their biocompatibility and functional properties. Herein, we report the utilization of the pulsed vacuum arc deposition (PVAD) technique for the fabrication of thin N-DLC coatings on the surface of electrospun PCL scaffolds. The effect of N-DLC coating deposition under various nitrogen pressures on the morphological, mechanical, physico-chemical, and biological properties of PCL scaffolds was investigated. It was established that an increase in nitrogen pressure in the range from 5 × 10−3 to 5 × 10−1 Pa results in up to a 10-fold increase in the nitrogen content and a 2-fold increase in the roughness of the PCL fiber surface. These factors provided the conditions for the enhanced adhesion and proliferation of human mesenchymal stem cells (MMSCs) on the surface of the modified PCL scaffolds. Importantly, the preservation of N-DLC coating properties determines the shelf life of a coated medical device. The elemental composition, tensile strength, and surface human MMSC adhesion were studied immediately after fabrication and after 6 months of storage under normal conditions. The enhanced MMSC adhesion was preserved after 6 months of storage of the modified PCL-based scaffolds under normal conditions.
Closing Editorial: Research Progress on Chitosan Applications
Authors: Facchinatto William M. , Campana-Filho Sérgio Paulo
Published: December 2024

Chitosan has attracted significant attention due to its versatile properties, which make it an ideal candidate for varied biomedical and industrial applications [...]
Study of Water Resistance of Polyurethane Coatings Based on Microanalytical Methods
Authors: Xie Chao , Shi Yufeng , Si Zhuozhuo , Wu Ping , Sun Binqiang , Ma Wenzhe
Published: December 2024

This study investigates the effect of microstructural changes in polyurethane coatings on their water resistance properties. Polyurethane coatings with varying diluent contents were prepared and tested for water penetration resistance and mechanical property retention. The time-dependent behavior of water within the coatings at different immersion durations was analyzed using low-field nuclear magnetic resonance (NMR). Furthermore, the free volume and characteristic molecular groups of each coating were analyzed using microscopic techniques, including positron annihilation lifetime spectroscopy (PALS) and attenuated total reflectance Fourier-transform infrared spectroscopy (ATR−FTIR). Results indicate that diluent content significantly alters the microstructure of the coatings. With increasing diluent content, both the average pore volume and free volume fraction initially decrease and then increase, while characteristic molecular groups, including hydrophilic groups, gradually decline. The water resistance performance of the coatings was significantly influenced by the combined effects of free volume and characteristic molecular groups. Among the five tested coating formulations, coatings with diluent contents of 20% and 25% showed a superior water penetration resistance, higher retention of mechanical properties after immersion, and relatively low total content of bound and free water at all immersion ages. The entropy weight method and the equal weight method were used to assess the overall water resistance, with the following ranking of scores: f20 > f25 > f30 > f15 > f10. This study offers theoretical support to guide the design and practical application of polyurethane coatings in real-world engineering projects.
Advances in Geoarchaeology and Cultural Heritage: Editorial
Authors: Liritzis Ioannis
Published: December 2024

The non-linear trend of evolution of ancient cultures is decisively affected by climatic change, landscape changes, and more [...]
The Usages of the Homage to the Five Supreme Entities in the Romance Poems (8th–12th Centuries)
Authors: Chojnacki Christine
Published: December 2024

Used to mark devotion to the main propagators of Jainism, namely the Jina (arhat), the Liberated Souls (siddha), the Teachers (ācārya), the spiritual Guides (guru), the Preceptors (upādhyāya), and the monks (muṇi), the formula of homage to the five supreme entities (pañcanamaskāra) underwent a significant development in the medieval period where it became a mantra protecting against all evils and violence and symbolising Jainism in its entirety and its respect for life in all its forms amidst the various Indian religions. In the present paper, I intend to investigate how the formula was used in largely unknown romance poems composed in the Prakrit language by Jaina scholar monks in medieval North India between the 8th and 12th centuries. Particular attention will be paid to how the writer monks used the formula of homage in the narrative to avoid the use of violence. The analysis will also focus on the development of the formula in the hymns of praise of the romance poems and study its significance in the context of the spread of Jainism at the turn of the first millennium, a period that led to the advent of King Kumārapāla, who has remained famous in history not only for the imposing monuments he left behind, but also for his conversion to Jainism and his governance according to principles of non-violence.
Use Self-Training Random Forest for Predicting Winter Wheat Yield
Authors: Shen Yulin , Mercatoris Benoît , Liu Qingzhi , Yao Hongxun , Li Zongpeng , Chen Zhen , Wang Wensheng
Published: December 2024

The effectiveness of supervised ML heavily depends on having a large, accurate, and diverse annotated dataset, which poses a challenge in applying ML for yield prediction. To address this issue, we developed a self-training random forest algorithm capable of automatically expanding the annotated dataset. Specifically, we trained a random forest regressor model using a small amount of annotated data. This model was then utilized to generate new annotations, thereby automatically extending the training dataset through self-training. Our experiments involved collecting data from over 30 winter wheat varieties during the 2019–2020 and 2021–2022 growing seasons. The testing results indicated that our model achieved an R2 of 0.84, RMSE of 627.94 kg/ha, and MAE of 516.94 kg/ha in the test dataset, while the validation dataset yielded an R2 of 0.81, RMSE of 692.96 kg/ha, and MAE of 550.62 kg/ha. In comparison, the standard random forest resulted in an R2 of 0.81, RMSE of 681.02 kg/ha, and MAE of 568.97 kg/ha in the test dataset, with validation results of an R2 of 0.79, RMSE of 736.24 kg/ha, and MAE of 585.85 kg/ha. Overall, these results demonstrate that our self-training random forest algorithm is a practical and effective solution for expanding annotated datasets, thereby enhancing the prediction accuracy of ML models in winter wheat yield forecasting.
Damage Localization and Severity Assessment in Composite Structures Using Deep Learning Based on Lamb Waves
Authors: Azad Muhammad Muzammil , Munyaneza Olivier , Jung Jaehyun , Sohn Jung Woo , Han Jang-Woo , Kim Heung Soo
Published: December 2024

In composite structures, the precise identification and localization of damage is necessary to preserve structural integrity in applications across such fields as aeronautical, civil, and mechanical engineering. This study presents a deep learning (DL)-assisted framework for simultaneous damage localization and severity assessment in composite structures using Lamb waves (LWs). Previous studies have often focused on either damage detection or localization in composite structures. In contrast, this study aims to perform damage detection, severity assessment, and localization using independent DL models. Three DL models, namely the artificial neural network (ANN), convolutional neural network (CNN), and gated recurrent unit (GRU), are compared. To assess their damage detection and localization capabilities. Moreover, zero-mean Gaussian noise is introduced as a data augmentation technique to address the variability and noise inherent in LW signals, improving the generalization capability of the DL models. The proposed framework is validated on a composite plate with four piezoelectric transducers, one at each corner, and achieves high accuracy in both damage localization and severity assessment, offering an effective solution for real-time structural health monitoring. This dual-function approach provides a scalable data-driven method to evaluate composite structures, with applications in predictive maintenance and reliability assurance in critical engineering systems.
Signal Detection by Sensors and Determination of Friction Coefficient During Brake Lining Movement
Authors: Hrabovský Leopold , Molnár Vieroslav , Fedorko Gabriel , Mikusova Nikoleta , Blata Jan , Fries Jiří , Jachowicz Tomasz
Published: December 2024

This article presents a laboratory device by which the course of two signals can be detected using two types of sensors—strain gauges and the DEWESoft DS-NET measuring apparatus. The values of the coefficient of friction of the brake lining when moving against the rotating shell of the brake drum were determined from the physical quantities sensed by tensometric sensors and transformed into electrical quantities. The friction coefficient of the brake lining on the circumference of the rotating brake disc shell can be calculated from the known values measured by the sensors, the design dimensions of the brake, and the revolutions of the rotating parts system. The values of the friction coefficient were measured during brake lining movement. A woven asbestos-free material, Beral 1126, which contained brass fibers and resin additives, showed slightly higher values when rotating at previously tested speeds compared to the friction coefficient values obtained when the brake drum rotation was uniformly delayed. The methodology for determining the friction coefficient of the brake lining allowed the laboratory device to verify its magnitude for different friction materials under various operating conditions.
Modelling, Analysis and Validation of Hydraulic Self-Adaptive Bearings for Elevated Floating Bridges
Authors: Zhang Lianpeng , Liu Yuan , Yang Tailai , Wang Ruichen , Feng Jie , Crosbee David
Published: December 2024

Conventional floating bridge systems used during emergency repairs, such as during wartime or after natural disasters, typically rely on passive rubber bearings or semi-active control systems. These methods often limit traffic speed, stability, and safety under dynamic conditions, including varying vehicle loads and fluctuating water levels. To address these challenges, this study proposes a novel Hydraulic Self-Adaptive Bearing System (HABS). The system integrates real-time position closed-loop control and a flexible support compensation method to enhance stability and adaptability to environmental changes. A modified three-variable controller is introduced to optimise load response, while a multi-state observer control strategy effectively reduces vibrations and improves traffic smoothness. A 1:15 scale prototype was constructed, and a co-simulation model combining MATLAB/Simulink and MSC Adams was developed to simulate various operational conditions. Results from both experiments and simulations demonstrate the HABS’s ability to adapt to varying loads and environmental disturbances, achieving a 72% reduction in displacement and a 54% reduction in acceleration. These improvements enhance traffic speed, stability, and safety, making the system a promising solution for emergency and floating bridges, providing superior performance under challenging and dynamic conditions.
A Comprehensive Dataset of Surface Electromyography and Self-Perceived Fatigue Levels for Muscle Fatigue Analysis
Authors: Cerqueira Sara M. , Vilas Boas Rita , Figueiredo Joana , Santos Cristina P.
Published: December 2024

Muscle fatigue is a risk factor for injuries in athletes and workers. This brings relevance to the study of this biochemical process to allow for its identification and prevention. This paper presents a novel dataset for muscle fatigue analysis comprising surface electromyography data from upper-limbs and the subject’s self-perceived fatigue level. This dataset contains 13 h and 20 min of data from 13 participants performing a total of 12 upper-limb dynamic movements (8 uni-articular and 4 complex/compound). This dataset may contribute to the testing of new fatigue detection algorithms and analysis of the underlying mechanisms.
Knowledge Graph-Based In-Context Learning for Advanced Fault Diagnosis in Sensor Networks
Authors: Xie Xin , Wang Junbo , Han Yu , Li Wenjuan
Published: December 2024

This paper introduces a novel approach for enhancing fault diagnosis in industrial equipment systems through the application of sensor network-driven knowledge graph-based in-context learning (KG-ICL). By focusing on the critical role of sensor data in detecting and isolating faults, we construct a domain-specific knowledge graph (DSKG) that encapsulates expert knowledge relevant to industrial equipment. Utilizing a long-length entity similarity (LES) measure, we retrieve relevant information from the DSKG. Our method leverages large language models (LLMs) to conduct causal analysis on textual data related to equipment faults derived from sensor networks, thereby significantly enhancing the accuracy and efficiency of fault diagnosis. This paper details a series of experiments that validate the effectiveness of the KG-ICL method in accurately diagnosing fault causes and locations of industrial equipment systems. By leveraging LLMs and structured knowledge, our approach offers a robust tool for condition monitoring and fault management, thereby improving the reliability and efficiency of operations in industrial sectors.
Energy-Efficient Wireless Multimedia Sensor Nodes for Plant Proximal Monitoring
Authors: Trinchero Daniele , Colucci Giovanni Paolo , Filipescu Elena , Zafar Ussama Syed Muhammad , Battilani Paola
Published: December 2024

The paper presents a double-radio wireless multimedia sensor node (WMSN) with a camera on board, designed for plant proximal monitoring. Camera sensor nodes represent an effective solution to monitor the crop at the leaf or fruit scale, with details that cannot be retrieved with the same precision through satellites or unnamed aerial vehicles (UAVs). From the technological point of view, WMSNs are characterized by very different requirements, compared to standard wireless sensor nodes; in particular, the network data rate results in higher energy consumption and incompatibility with the usage of battery-powered devices. Avoiding energy harvesters allows for device miniaturization and, consequently, application flexibility, even for small plants. To do this, the proposed node has been implemented with two radios, with different roles. A GPRS modem has been exclusively implemented for image transmission, while all other tasks, including node monitoring and camera control, are performed by a LoRaWAN class A end-node that connects every 10 min. Via the LoRaWAN downlink, it is possible to efficiently control the camera settings; the shooting times and periodicity, according to weather conditions; the eventual farming operations; the crop growth stages and the season. The node energy consumption has been verified in the laboratory and in the field, showing that it is possible to acquire one picture per day for more than eight months without any energy harvester, opening up further possible implementations for disease detection and production optimization.
Trust in Healthcare, Medical Mistrust, and Health Outcomes in Times of Health Crisis: A Narrative Review
Authors: Souvatzi Elisavet , Katsikidou Magdalini , Arvaniti Aikaterini , Plakias Spyridon , Tsiakiri Anna , Samakouri Maria
Published: December 2024

Background/Objectives: The concepts of trust and distrust in health systems during health crises are significantly related to public adoption of health behaviors and health outcomes. The aim of this review is to examine trust and mistrust during times of health crisis, such as periods of viral pandemics and epidemics, and how these concepts relate to public health behaviors and, by extension, affect health outcomes. Methods: A focused search was conducted in PubMed and Scopus using a Boolean expression to identify relevant articles written in the English language and published between 2003 and 2023. The research methods comprised content analysis, thematic analysis, and a word cloud visualization to identify frequent themes related to trust and mistrust in healthcare systems. Results: The analysis included 57 studies and revealed that trust in healthcare systems, institutions, and professionals plays a significant role in shaping public health behaviors during health crises. The study also highlighted how mistrust leads to negative health outcomes, such as increased belief in conspiracy theories, vaccine hesitancy, and non-compliance with public health measures. Conclusions: The review emphasizes the importance of building and maintaining trust in healthcare systems to ensure better public health outcomes during crises. It calls for further research to better understand the nuances of trust and mistrust, aiming to inform public health strategies and interventions that could lead to more effective crisis management and improved health outcomes.
Subverting Racialized Mobility Regimes: Ethical Research with Migrant Youth in an Age of Securitization
Authors: Shirazi Roozbeh
Published: December 2024

In France, minoritized migrant youth—a term encompassing various legal statuses and migration trajectories—are subject to systems of surveillance that include racialized policing, school securitization policies, and programs to counter extremism. These institutional practices are complemented by hostility within everyday public spaces and broader systems of representation. Together, institutional and everyday forms of surveillance constitute racialized mobility regimes for migrant youth within and beyond educational spaces. For researchers who work with migrant youth, such landscapes pose ethical demands—what forms of critical awareness, anticipatory planning, and improvisatory practices are necessary to mitigate harms resulting from participation in their projects? Drawing upon an autoethnographic revisiting of a 16-month digital storytelling engagement with newcomer migrant and refugee youth in two French high schools, I discuss the creation of a “youth researcher” pass in anticipation of the racialized surveillance confronting migrant youth in France. Informed by the works of Walter Benjamin and Michel de Certeau on mobility, storytelling, and facsimiles, as well as political developments in France, I argue that in settings in which migrant presence is deemed a threat, researchers must unapologetically opt for an ethical stance that takes protection of participants’ humanity—rather than legality—as its core aim.
The Potential Impact of the European Green Deal on Farm Production in Poland
Authors: Pawłowski Krzysztof Piotr , Sołtysiak Gabriela
Published: December 2024

The proposed changes in the European Green Deal require the restructuring of the agricultural sector throughout the European Union. Particularly crucial for the agri-food industry are “From Farm to Fork” strategies and new legislation “for biodiversity,” which are an integral part of the European Green Deal. From an environmental perspective, changes are required immediately, but at the same time, they may reduce agricultural production in Poland. Therefore, this study aims to assess the potential consequences of implementing the European Green Deal principles on Polish agriculture’s productivity. The study is based on two key assumptions which involve a 50% reduction in the use of plant protection products and a 20% reduction in fertilisation. The conducted analyses rely on data from the Farm Accountancy Data Network (FADN). The results were obtained by constructing a panel regression model for farms of different economic sizes. Although the most significant reduction in production value may concern the largest farms (using the most fertilisers and plant protection products), the smallest farms may experience the most critical difficulties. The potential decline in crop production in Polish agriculture could be stopped by implementing modern technologies enabling the development of precision and digital agriculture 4.0.
Advanced Research on Sustainable Performance Optimization in Electrical Systems: Editorial
Authors: Jodin Gurvan , Ben Ahmed Hamid , Crebier Jean-Christophe
Published: December 2024

The search for intrinsic usage-limited performance can lead to poor life cycle solutions in terms of resource consumption, pollution, greenhouse gas emissions and other environmental impacts [...]
Digital Capabilities and Business Performance: A Systematic Literature Review
Authors: Samsuden Nurul S. , Kohar Umar H. A. , Khatib Saleh F. A. , Abbas Alhamzah F.
Published: December 2024

The purpose of this paper is to enhance understanding of digital capabilities (DC) by examining various attributes and integrating findings from previous studies on the impact of DC on business performance (BP) using the balanced scorecard approach. This study employs qualitative methodologies to systematically review the literature, focusing on 131 studies from the Scopus database, categorizing research gaps, DC attributes, and the influence of DC on BP, and presenting these findings as a consolidated categorization alongside a future direction framework. The findings indicate that DC significantly impacts internal processes (BP2), enhancing firms’ ability to integrate value chains, improve efficiency, and add cost competitiveness to innovation. This influence on BP2 also interrelates with financial performance (BP1), where internal efficiency benefits economic outcomes. However, gaps exist in understanding DC’s effect on customer-related aspects, and findings vary across firm types, industries, and countries. The study identifies three key DC attributes: digital technology, digital agility, and digital marketing capabilities. To the author’s knowledge, this study is the first comprehensive evaluation of DC attributes relevant at the business level, providing a criterion-based view of DC’s impact on BP and contributing to broader research on business strategies.
What Determines Rural Residents’ Intention and Behavior Towards Clean Energy Use? Evidence from Northwest China
Authors: Li Hua , Zhao Wei , Wang Weijun , Zhang Yifan , Zhang Qin
Published: December 2024

Two United Nations Sustainable Development Goals highlight that energy supply, conversion, transmission, and consumption are primary contributors to climate change, accounting for 60% of global greenhouse gas emissions. Exploring the influencing factors on the intention and behavior of clean energy use in rural areas is a crucial step in achieving the “Dual Carbon” target and global sustainable development goals. The article constructed a theoretical analysis framework of “environmental knowledge—perceived value—use intention—use behavior”. Taking Gansu Province, a typical case area in northwest China, as a case study, data from 766 survey questionnaires were used to analyze the characteristics and impact mechanism of clean energy use behavior among residents. This article finds that rural household energy use is moving towards low-carbon goals, but traditional energy remains an important component, especially in winter heating scenarios. Only the use intention has a direct promoting effect on use behavior, with a regression coefficient of 0.108. Perceived value and use intention play a chain-mediating role between environmental knowledge and use behavior. Residents with higher income levels, higher education levels, and poorer health conditions are more likely to develop clean energy use intention and behavior. At the same time, government intervention measures also have a promoting effect. Finally, countermeasures and suggestions for improving the public’s level of clean energy utilization in underdeveloped areas were proposed.
Enhancing High School Students’ STEM Major Intention Through Digital Competence: A Large-Scale Cross-Sectional Survey
Authors: Liu Jinfang , Zhang Yi , Luo Heng , Zhang Xinxin , Li Wei
Published: December 2024

Faced with a shortage of college graduates with STEM degrees, many countries are seeking ways to attract more high school students to pursue STEM majors after graduation. This study aims to promote the sustainability of high school students in STEM fields by analyzing the effects of digital competence on the STEM major intentions of high school students. The survey collected data from 2415 participants comprising 1230 females and 1185 males from 16 high schools in China. Using hierarchical logistic regression, the study found that digital competence had significant positive effects on high school students’ STEM major intention. Also, computational thinking was the strongest predictor among the four areas of digital competence. Moreover, latent profile analysis identified two profiles of male students and four profiles of female students. Among male students, advanced male users had the strongest STEM major intention; among female students, low-level female novices had the weakest STEM major intention. Thus, digital competence can be considered an effective way to bridge the gender gap in STEM major selection. Based on the findings, strategies are discussed for improving high school students’ STEM major intentions and promoting digital competence, thereby ensuring the sustainable development of students in STEM fields in the digital era.
Identification of Aquatic Plant Species Suitable for Growing in Integrated Multi-Trophic Aquaculture Systems in Southwest Bangladesh
Authors: Bablee Alif Layla , Bashar Abul , Alam Md. Mehedi , Hasan Neaz A. , Haque Mohammad Mahfujul , Hansen Lars Hestbjerg , Jørgensen Niels O. G.
Published: December 2024

Giant freshwater prawn (Macrobrachium rosenbergii) farming in Bangladesh began in the 1970s and has become a significant export industry. Despite its potential, there are concerns about the environmental sustainability of prawn farming due to its high greenhouse gas (GHG) footprint, but implementation of integrated multi-trophic aquaculture (IMTA) may help minimize the GHG emission. A key element in IMTA is using plants to take up inorganic nutrients released by the prawns, producing valuable plant products and cleaning the water. Using a quadrat sampling method, we conducted a field study in combined prawn and shrimp ponds, aquaculture fishponds, and non-aquaculture waters in south- west Bangladesh to characterize plant diversity and identify suitable species for IMTA in prawn farms. A total of 38 plant species were identified with densities ranging from 4.5–6.1 plants/m2 in the aquaculture ponds to 11.6–17.1 plants/m2 in the prawn/shrimp and the non-aquaculture ponds. Free-floating plants were the most abundant, followed by emergent, floating anchored, and submerged plants. Most plants have commercial values as food, fodder, fish feed, fertilizer, or medicines to local people. Our results suggest that species within the Oxalis, Ipomoea, Azolla, and Lemna genera are suitable extractive aquatic plants for the implementation of IMTA in prawn farms and may improve the sustainability of prawn production.
Fundamental Challenges and Opportunities for Textile Circularity
Authors: Thomas Kedron , Durrani Hira , Brady Julia , Ludwig Kendall , Yatvitskiy Michelle , Clarke-Sather Abigail R. , Cao Huantian , Cobb Kelly
Published: December 2024

The negative environmental impacts of the current linear system of textile and apparel production are well-documented and require urgent action. The sector lacks an effective recycling system, resulting in massive waste and environmental pollution. This paper presents the results of qualitative research involving textile and apparel industry stakeholders, including representatives from brands and retailers, waste collectors, recyclers, non-profit organizations, academic institutions, and government agencies. Our research focused on stakeholder perceptions of the significance and importance of textile circularity, the challenges that exist for transitioning the textile and apparel industry from a linear system to a circular economy (CE), and resources that exist to support this transition. The results of this study call attention to the following urgent requirements: a consistent definition of CE to promote transparency and accountability and prevent greenwashing; improved systems for materials identification, sorting, and pre-processing of post-consumer textile waste to enable recycling; innovations in mechanical recycling technologies to maintain the value of recycled materials; and new, materials-driven approaches to design and manufacturing that are responsive to feedstock variability and diverse consumer needs. The research findings also suggest the need for flexible, regional CEs that are rooted in community partnerships.
Ecological Restoration and Zonal Management of Degraded Grassland Based on Cost–Benefit Analysis: A Case Study in Qinghai, China
Authors: Wang Ziyao , Li Feng , Xie Donglin , Jia Jujie , Cheng Chaonan , Lv Jing , Jia Jianhua , Jiang Zhe , Li Xin , Suo Yuxia
Published: December 2024

The Qinghai–Tibetan Plateau (QTP) has the largest area of natural grassland in China, and continuous grassland degradation poses a serious threat to regional ecological security and sustainable resource management. It is essential to comprehensively evaluate the cost–benefit differences and drivers of grassland degradation across various zones to enhance sustainable management practices. This study presents a zonal management framework for the ecological restoration of degraded grasslands based on cost–benefit analysis, specifically applied to Qinghai in the Northeastern QTP. The results indicate: (1) Although the overall NDVI of grasslands shows an upward trend, some areas still exhibit significant degradation. (2) Cost–benefit analysis can divide degraded grasslands into four types of Ecological Management Zones (EMZs): high-cost–high-benefit zone, high-cost–low-benefit zone, low-cost–low-benefit zone, and low-cost–high-benefit zone. (3) The driving factors of grassland degradation show significant differences in different EMZs. Based on these research findings, differentiated spatial planning and management strategies for grassland ecological restoration were developed for each EMZ. This study not only provides a scientific methodology for grassland ecological restoration but also offers important insights for the sustainable management of grassland resources in the QTP and other ecologically sensitive areas.
Global Threats to Sustainability: Evolving Perspectives of Latvian Students (2016–2022)
Authors: Čekse Ireta , Alksnis Reinis
Published: December 2024

In an increasingly interconnected world facing global challenges such as climate change and social inequality, citizenship education plays a critical role in preparing young people for responsible democratic participation and sustainability. This study aims to develop a model to explain factors influencing Latvian students’ perceptions of global threats, comparing data from the International Association for the Evaluation of Educational Achievement (IEA)’s International Civic and Citizenship Study (ICCS) cycles in 2016 and 2022, to assess how these opinions have evolved and their implications for promoting sustainability through civic education. Confirmatory factor analysis is used to test the latent factor structure modeling the students’ perceptions of environmental and economic threats to the world’s future. A multi-group structural equation model is constructed and used with the corresponding descriptive statistics to analyze various background factor effects on students’ sustainability concerns. The results of the study indicate that citizenship knowledge, as well as various student-level background factors, have an impact on environmental and economic sustainability concerns among 13-year-old students. In some instances, these effects are mediated by students’ civic knowledge level, while in other instances, they are directly attributed to the background factors. The findings show that there may have been some shift in students’ perceptions of sustainability threats, and the role of civic education may have changed in this respect. Furthermore, the varying levels of knowledge across various levels of background factors may suggest that content in lessons must be differentiated according to the needs of groups to support their understanding of the importance of sustainability.
Complete Epoxy Phosphonate Conversion to Dimethyl (1E)-3-Hydroxyprop-1-Enylphosphonate with Photobiocatalysts’ Assistance
Authors: Samson Sunday Ocholi , Serafin-Lewańczuk Monika , Brzezińska-Rodak Małgorzata , Klimek-Ochab Magdalena , Żymańczyk-Duda Ewa
Published: December 2024

Phosphonates derivatives are compounds of interests and are applied as drugs of, e.g., antibacterial antiviral activities, connected with their inhibitory activity towards different enzymes, which is related to the configuration of particular compound isomers. The biological synthesis of such molecules is the method of choice and can be carried out using enzymes or whole cells from organisms. Photobiocatalysts employed in the bioconversion of epoxymethyl dimethyl phosphonate are able to convert this substrate into a pure geometric isomer of the unsaturated product, dimethyl (1E)-3-hydroxyprop-1-enylphosphonate, which is a rare and expensive compound of high added value. Six different strains were screened towards dimethyl epoxy phosphonate and in the case of Synechococcus bigranulatus, over 99% conversion was achieved. The product structure was confirmed with Mass Spectroscopy (MS); 1H, 13C, 31P, and 2D Nuclear Magnetic Resonance (NMR); and Infrared Spectroscopy (IR).
The Impact of Optimism Bias on Strategic Decision-Making and Efficiency in Online Retail Supply Chains
Authors: Li Jialu
Published: December 2024

This paper examines the effects of optimism bias within online retail supply chains. Here, optimism refers to a cognitive bias wherein the third-party seller and the e-commerce platform underestimate the likelihood of facing low market potential. The analysis begins by exploring the impacts of each party’s respective biases. The results indicate that while seller optimism generally leads to self-detrimental outcomes, it can also benefit both the platform and the overall system. Conversely, platform optimism does not permanently harm the platform itself but consistently disadvantages the seller and negatively impacts the supply chain. This work then investigates the combined effects of seller and platform optimism on overall system performance, revealing that the entire channel can, in fact, gain from optimism bias. This research offers insights into strategic approaches that may enhance the efficiency of online retail supply chains.
A System Dynamics Stability Model for Discrete Production Ramp-Up
Authors: Haller Julian , Kumar Bharath , Göppert Amon , Schmitt Robert H.
Published: December 2024

Manufacturing companies are increasingly challenged to deliver customizable products with shorter time to market and higher quality while adhering to sustainability requirements. To meet these challenges, the frequency and importance of production ramp-ups will increase in the future. However, most ramp-ups still fail to meet targets due to unpredictable equipment failures, operator errors, and system complexity. We propose a system dynamics model that captures the unique dynamics of ramp-up phases by integrating stability and disturbance factors that influence the key performance indicators overall equipment effectiveness, process capability, and production output. A systematic literature review informed the identification of stability factors, which were validated through expert interviews in the automotive industry. Our system dynamic simulation results indicate that control factors realistically influence production system behaviour during different ramp-up phases. Despite some limitations regarding the effects of maintenance personnel and engineering changes on key performance indicators, our model effectively simulates realistic ramp-up behaviour. The findings highlight the need for tailored models that consider specific ramp-up contexts and emphasize the importance of data acquisition for enhanced performance prognosis in future research.
Photodynamic Inactivation of Human Herpes Virus In Vitro with Ga(III) and Zn(II) Phthalocyanines
Authors: Vilhelmova-Ilieva Neli , Mantareva Vanya , Braikova Diana , Iliev Ivan
Published: December 2024

Photodynamic inactivation (PDI) has been revealed as a valuable approach against viral infections because of the fast therapeutic effect and low possibility of resistance development. The photodynamic inhibition of the infectivity of human herpes simplex virus type 1 (HSV-1) strain Victoria at different stages of its reproduction was studied. PDI activity was determined on extracellular virions, on the stage of their adsorption to the Madin-Darby bovine kidney (MDBK) cell line and inhibition of the viral replication stage by application of two tetra-methylpyridiloxy substituted gallium and zinc phthalocyanines (ZnPcMe and GaPcMe) upon 660 nm light exposure with a light-emitting diode (LED 660 nm). The PDI effect was evaluated on extracellular virions and virus adsorption by the terminal dilution method and the change in viral infectivity, which was compared to the untreated control group. The decrease in viral titer (Δlgs) was determined. The effect on the replicative cycle of the virus was determined using the cytopathic effect inhibition (CPE) assay. The direct influence on the virions showed a remarkable effect with a decrease in the viral titer more than 4 (Δlg > 4). The influence of the virus to the cell on the stage of adsorption was also significantly affected by the exposure time and the concentration of applied photosensitizers. A distinct inhibition was evaluated for ZnPcMe at the viral replication stage, which demonstrated a high photoinactivation index (PII = 33.0). This study suggested the high efficacy of PDI with phthalocyanines on HSV-1 virus, with full inhibition caused by the mechanism of singlet oxygen generation. These promising data are a good basis for further investigations on the PDI application against pathogenic viruses.