bluuebunny/crossref_metadata_2025 huggingface dataset:
Customizable Self-Microemulsifying Rectal Suppositories by Semisolid Extrusion 3D Printing
Authors: Park Hye Jin , Kim Dong Wuk
Published: October 2024

Objectives: This study aims to create an innovative self-microemulsifying drug delivery system (SMEDDS) suppository for ibuprofen (IBU) using semisolid extrusion (SSE) three-dimensional (3D) printing technology. Methods: Based on solubility studies and the ability to form a transparent microemulsion upon dilution, a selected oil, surfactant, and co-surfactant were utilized to prepare SMEDDS-3DPS containing IBU. The optimal formulation consisted of 10% Triacetin, 80% Gelucire 48/16, and 10% Tetraethylene glycol. SSE 3D printing was employed to create three different-sized suppositories with varying drug contents. These suppositories were assessed for their physicochemical properties, content uniformity, and dissolution profiles. Results: The prepared mixture exhibited suitable physical properties for printing, with nano-sized emulsion droplets providing a large surface area for improved drug absorption in the rectum. Characterization techniques such as differential scanning calorimetry, powder X-ray diffraction, and Fourier transform infrared spectroscopy indicated that IBU was present in the formulation in an amorphous state. Additionally, in vitro dissolution tests demonstrated that SMEDDS-3DPS had a significantly higher initial dissolution rate compared with IBU powder. Conclusions: This research suggests that SMEDDS-3DPS, as a rectal IBU dosage form, can enhance the rectal bioavailability of IBU. It demonstrates the versatility of 3D printing as a novel manufacturing method for lipid-based suppositories and highlights the simplicity and adaptability of SSE 3D printing technology in producing customized suppositories tailored to individual patient needs, surpassing traditional methods.
RrWRKY1, a Transcription Factor, Is Involved in the Regulation of the Salt Stress Response in Rosa rugosa
Authors: Zang Fengqi , Wu Qichao , Li Zhe , Li Ling , Xie Xiaoman , Tong Boqiang , Yu Shuhan , Liang Zhaoan , Chu Chunxue , Zang Dekui , Ma Yan
Published: October 2024

Salt stress has become a major environmental problem affecting plant growth and development. Some WRKY transcription factors have been reported to be involved in the salt stress response in plants. However, there are few studies on the involvement of WRKYs in the salt stress response in Rosa rugosa. In this study, we isolated a salt tolerance gene, RrWRKY1, from R. rugosa. RrWRKY1 was found to belong to Group I of the WRKY family, and it was specifically expressed in leaves and petals. RrWRKY1 expression was upregulated under NaCl stress in rose leaves. After silencing RrWRKY1 in R. rugosa, transgenic plants showed dry leaves and black and brown veins, indicating sensitivity to salt stress. At the same time, the transcription levels of the salt tolerance-related genes RrNHX1, RrABF2, RrRD22, RrNCED1, and RrHKT1 also changed significantly. The superoxide dismutase (SOD) and peroxidase (POD) activities decreased, the proline content decreased, and the malondialdehyde (MDA) content in the gene-silenced plants increased, indicating that RrWRKY1 regulates the salt tolerance of R. rugosa. In addition, the overexpression of RrWRKY1 in Arabidopsis thaliana improved the germination rate and the average of the main root and lateral root lengths, and the transgenic plants had a larger number of lateral roots than the WT plants under salt stress. This study provides candidate gene resources for salinity tolerance breeding and a theoretical basis for analyzing the salinity tolerance mechanism of the WRKY gene.
PETG as an Alternative Material for the Production of Drone Spare Parts
Authors: Baltić Marija Z. , Vasić Miloš R. , Vorkapić Miloš D. , Bajić Danica M. , Piteľ Ján , Svoboda Petr , Vencl Aleksandar
Published: October 2024

Material selection is the main challenge in the drone industry. In this study, hardness, abrasive wear, impact resistance, tensile strength, and durability (frost resistance and accelerated ageing) were identified as important characteristics of drone materials. The additive manufacturing technology was used to produce the drone leg specimens and prototype. The suitability of PETG as a primary filament material in the design of the drone leg was investigated. Nine series were printed with different raster lines (0.1, 0.2 and 0.3 mm) and infill densities (30, 60 and 90%). Printed specimens were annealed in salt and alabaster, as well as immersed in liquid nitrogen. Series with raster line-infill densities of 0.1–30, 0.3–30, 0.1–90 and 0.3–90 were identified as the most interesting ones. Thermally treated specimens had better mechanical and durability properties, and infill density was found to be the most important printing parameter. Specimen annealed in salt with a raster line of 0.1 mm and infill density of 90% had the best results. Since ABS is the most common material used for drone leg production, its properties were compared with the PETG specimen, which showed the best properties. The potential of PETG as an alternative material was proven, while the flexibility, productivity and suitability of the leg drone design were additionally confirmed.
The Influence of Polymer Impregnating Materials on Structural Strengthening of 3D Printed Sand Molds Produced by Binder Jetting Method
Authors: Rybak Andrzej , Javora Radek , Sekula Robert , Kmita Grzegorz
Published: October 2024

Additive manufacturing offers great potential for various industrial solutions; in particular, the binder jetting method enables the production of components from various materials, including sand molds for casting. This work presents the results of an extensive set of experiments aimed at enhancing the structural strengthening of 3D-printed sand molds. Structural strengthening was achieved by impregnating the sand-printed structures with two polymer materials: epoxy resin and silicone varnish. Impregnation was performed with variable parameters, such as temperature, pressure, and time. Structural strengthening using polymers was investigated by analyzing the flexural strength and impact resistance of the impregnated products and comparing these obtained values with the reference material in terms of impregnation parameters and the polymer used. Microstructural observations and an analysis of the pore filling were also performed. This approach allowed for a full assessment of the influence of processing parameters and the type of polymer used for impregnation on the properties of sand-printed structures, which allowed for identifying the most optimal method to be used to strengthen the sand molds for casting the components for electrical devices. As a direct proof of concept, it was shown that impregnation with polymeric materials could effectively strengthen the sand mold, increasing its flexural strength and impact resistance by over 20 times and 5 times, respectively. A full-scale mold was printed using binder jetting, impregnated with epoxy resin at 65 °C, and used to successfully fabricate a fully functional electrification device.
The Evaluation of Sandwich Composite Materials with Vegetable Fibers in a Castor Oil Polyurethane Matrix with Their Faces and Honeycomb Core Made in a 3D Printer
Authors: Pino Gilberto Garcia del , Bezazi Abderrezak , Kieling Antonio Claudio , Neto José Costa de Macedo , Garcia Sofia Dehaini , Rivera José Luis Valin , Valin Fernández Meylí , Torres Aristides Rivera , Valenzuela Diaz Francisco Rolando
Published: October 2024

Sandwich panels are widely used in the naval and aerospace industries to withstand the normal tensile, compressive, and shear stresses associated with bending. The faces of sandwich composites are usually made of metals such as aluminum and, in some studies with composites, using a polymeric matrix, but there are no studies in the literature using a castor oil polyurethane matrix. The core of the panel must keep the faces apart and be rigid perpendicular to them. To begin the work, a study was carried out on the influence of alkaline treatment on sisal fibers to increase the fibers’ adhesion to castor oil polyurethane. There are no relevant studies worldwide on the use of this resin and the adhesion of vegetable fibers to this polyurethane. In this work, a study was carried out through a three-point bending test of sandwich panels using faces of composite material with sisal fibers subjected to an alkaline treatment of 10% by weight of sodium hydroxide and an immersion time of 4 h in the dissolution, which was the best chemical treatment obtained initially in a castor oil polyurethane matrix. The honeycomb cores were made by 3D printer and in this study two different printing filament materials, PETG and PLA, and two different core heights were compared. As a result of a traction test, it was observed that sisal fibers with chemical treatment in a castor oil polyurethane matrix can be used in composites, although the stress levels obtained are 50% lower than the stresses obtained in other matrixes such as epoxy resin. The combination of sisal faces in a castor oil polyurethane matrix and honeycomb cores made in a 3D printer showed good properties, which allows the use of renewable, sustainable and less aggressive materials for the environment. In all tests, PETG was 21% to 32% stronger than PLA. Although there was no rupture in the test specimens, the PETG cores deformed 0.5% to 3.6% less than PLA. The composites with PLA were lighter, because the core density was 13.8% lower than the PETG cores. Increasing the height of the honeycomb increased its strength.
Bridging the Shakespearean and Jataka Narratives: A Narratological Analysis of Othello and Sambulā Jātaka (519)
Authors: Dilani Nipunika
Published: October 2024

This study explores the thematic and structural parallels between William Shakespeare’s Othello and the Sambulā Jātaka (519) from ancient Buddhist literature. Through a detailed narratological analysis, this study examines the narrative structure, narrator and narrative perspectives, focalization, temporal aspects, and narrative techniques employed in both texts. By investigating how each narrative addresses themes of sexual jealousy, trust, and human frailty, this paper highlights the universal nature of these emotions and their impact across two cultural contexts. This study employs the qualitative approach of research analyzing the texts, Othello and the Sambulā Jātaka, as a sample representing two larger canons. The analysis reveals that both genres utilize the narratological aspects to reveal the destructive nature of most of the above underlying emotions, bringing them to the surface and creating a powerful resonance that transcends time and geography. This comparative study underscores the timeless relevance of these narratives and their shared exploration of the complexities of human relationships and the destructive power of irrational suspicions.
The Rising Tide of Hindu Nationalism: Threats and Opportunities for Peace
Authors: Riddle Karie Cross
Published: October 2024

Observers of Indian politics have noted rising acts of violence against Muslims in an atmosphere of increasing Hindu nationalism during Prime Minister Narendra Modi’s tenure. Hinduism, however, like all religions, also contains many resources for peace. Looking to both theory and practice, this piece examines how we can theorize Hinduism and religion in general as a source of protection for peace and human rights. It also looks for peaceful practices that may be of use in the contemporary climate of violence. I conclude that we can only get to peace through the acknowledgement of religious motivations within politics and a renewed commitment to the truth.
Dialogue Between Theology and Science: Present Challenges and Future Perspectives
Authors: Tanzella-Nitti Giuseppe
Published: October 2024

In order to consider the natural sciences as a contemporary locus theologicus, I here examine the meaning and implications of the “dialogue between theology and the sciences”. Although widely used, this expression has different meanings. I try to clarify who the interlocutors of the dialogue are, where the dialogue takes place, and what the goals of the dialogue itself are. A coherent agenda to encourage the use of the sciences in theological work should include (a) the design and implementation of interdisciplinary curricula to help those scholars who are seriously interested to be trained in this field; (b) an emphasis on the role of philosophy and philosophical sources in the study of the sciences and theology; (c) going beyond the epistemological level and developing the dialogue also at the anthropological level; (d) the identification of a number of key issues for theological and religious studies that are expected to become more urgent in the coming years. Finally, the use of the sciences as a locus theologicus is expected to bear two main fruits: first, to offer a positive, speculative insight to the work of theologians and, second, to contribute to a responsible development of the dogmatic teachings of the Church.
Feature Extraction and Identification of Rheumatoid Nodules Using Advanced Image Processing Techniques
Authors: Mubeen Azmath , Dulhare Uma N.
Published: October 2024

Background/Objectives: Accurate detection and classification of nodules in medical images, particularly rheumatoid nodules, are critical due to the varying nature of these nodules, where their specific type is often unknown before analysis. This study addresses the challenges of multi-class prediction in nodule detection, with a specific focus on rheumatoid nodules, by employing a comprehensive approach to feature extraction and classification. We utilized a diverse dataset of nodules, including rheumatoid nodules sourced from the DermNet dataset and local rheumatologists. Method: This study integrates 62 features, combining traditional image characteristics with advanced graph-based features derived from a superpixel graph constructed through Delaunay triangulation. The key steps include image preprocessing with anisotropic diffusion and Retinex enhancement, superpixel segmentation using SLIC, and graph-based feature extraction. Texture analysis was performed using Gray-Level Co-occurrence Matrix (GLCM) metrics, while shape analysis was conducted with Fourier descriptors. Vascular pattern recognition, crucial for identifying rheumatoid nodules, was enhanced using the Frangi filter. A Hybrid CNN–Transformer model was employed for feature fusion, and feature selection and hyperparameter tuning were optimized using Gray Wolf Optimization (GWO) and Particle Swarm Optimization (PSO). Feature importance was assessed using SHAP values. Results: The proposed methodology achieved an accuracy of 85%, with a precision of 0.85, a recall of 0.89, and an F1 measure of 0.87, demonstrating the effectiveness of the approach in detecting and classifying rheumatoid nodules in both binary and multi-class classification scenarios. Conclusions: This study presents a robust tool for the detection and classification of nodules, particularly rheumatoid nodules, in medical imaging, offering significant potential for improving diagnostic accuracy and aiding in the early identification of rheumatoid conditions.
A Novel ISAR Image Feature Suppression Method Based on Arbitrary Phase Encoding
Authors: Wang Yanfeng , Wu Qihua , Liu Xiaobin , Xu Zhiming , Zhao Feng , Xiao Shunping
Published: October 2024

Compared with the amplitude modulation of conventional interrupted sampling repeater jamming (ISRJ), the image feature control method based on phase modulation exhibits greater energy efficiency and, therefore, has received wide attention recently. In this paper, an Inverse Synthetic Aperture Radar (ISAR) image feature suppression method based on arbitrary phase encoding (APE) is proposed. The parameter design criterion is further analyzed. Through the nonperiodic segmented coding and modulation of the imaging signal in fast and slow time domains, the modulated signal produces a two-dimensional suppression region with uniform energy distribution in the ISAR image. Simulations via the measured Yak-42 aircraft data have verified the effectiveness of the proposed method for target feature control. Compared to binary phase modulation jamming, the APE method with a phase modulation accuracy of 1 degree can achieve the same jamming effect while reducing the jamming power requirement by 3 dB. By optimizing with the proposed method, the image entropy of the interfered image increases by 1.1 to 1.5 compared to the original image.
A Comprehensive Technical, Environmental, Economic, and Bibliometric Assessment of Hydrogen Production Through Biomass Gasification, Including Global and Brazilian Potentials
Authors: Tavares Borges Pedro , Silva Lora Electo Eduardo , Venturini Osvaldo José , Errera Marcelo Risso , Yepes Maya Diego Mauricio , Makarfi Isa Yusuf , Kozlov Alexander , Zhang Shu
Published: October 2024

It is well known that the widespread utilization of fossil fuels contributes to climate change, so exploring new sustainable energy sources is more important than ever for energy transition pathways. The variability and intermittency of solar and wind sources are of concern. Hydrogen (H2) utilization as an energy carrier can address this issue. The technology for producing hydrogen from biomass gasification has not yet reached a high level of technological maturity. The main novelty of this work is to evaluate the state of the art of the technologies for producing H2 from solid biomass, taking into account technological, economic, and environmental indicators and the results of a bibliometric study, and also the calculation of the technical potential for hydrogen production through biomass gasification on a worldwide and Brazilian scale. The most frequently mentioned technology to boost H2 production efficiency is the addition of catalysts to the gasifier. Primary catalyst utilized in biomass gasification for hydrogen enhancing enhancement, such as olivine, CaO, and CeO2-Ni-CaO are reviewed in the article. As a result, the syngas had an H2 content rise of 511%, 659.6%, and 853.4%, respectively. According to the reviewed literature, the levelized cost of hydrogen production can reach an average value of USD3.15/kg of H2, and the average yield is 0.1 kg-H2/kg-biomass. The worldwide potential for hydrogen production from solid biomass in an optimal trends scenario for 2050 is estimated to be 45.03 EJ, and Brazil’s potential is 6.5 EJ.
Not Exactly Jumping on the Green Bandwagon: The Lithuanian Hospitality Scene
Authors: Belhaj Monika , Lankauskienė Rita , Gedminaitė-Raudonė Živilė
Published: October 2024

In recent years, sustainability has become a key focus in the global tourism and hospitality industry, with hotels increasingly adopting waste reduction strategies, resource optimization, and sustainable supply chain practices. However, the extent of adoption varies due to strategic decisions, resistance to change, and other contextual factors. This paper, grounded in a comprehensive sustainability framework, explores the Lithuanian context through a diagnostic investigation of 37 hotels in Vilnius. Employing a mixed-method approach, it aims to examine their current corporate social responsibility (CSR) practices. The findings reveal that while hotels in Vilnius voluntarily adopt sustainability practices across environmental, economic, and social domains, significant gaps remain, including a lack of formal sustainability policies and limited transparency. Despite these challenges, there is a growing need to improve and adopt more structured sustainability practices, which could notably enhance the sector’s overall performance. This paper offers valuable insights for policymakers, industry stakeholders, and researchers aiming to promote sustainable development in Lithuania and beyond.
Fusion Technology-Based CNN-LSTM-ASAN for RUL Estimation of Lithium-Ion Batteries
Authors: Li Yanming , Qin Xiaojuan , Ma Furong , Wu Haoran , Chai Min , Zhang Fujing , Jiang Fenghe , Lei Xu
Published: October 2024

Accurately predicting the remaining useful life (RUL) of lithium-ion batteries (LIBs) not only prevents battery system failure but also promotes the sustainable development of the energy storage industry and solves the pressing problems of industrial and energy crises. Because of the capacity regeneration phenomenon and random interference during the operation of lithium-ion batteries, the prediction precision and generalization performance of a single model can be poor. This article proposes a novel RUL prediction based on data pre-processing methods and the CNN-LSTM-ASAN framework. The model is based on a fusion technique for optimizing the tandem fusion of the Convolutional Neural Network (CNN) and the Long Short-Term Memory Network (LSTM). Firstly, the improved adaptive noise fully integrates empirical mode decomposition (ICEEMDAN) and the Pearson correlation coefficient (PCC), which are used to estimate the global deterioration tendency component and the local capacity restoration component, to reconstruct the dataset and eliminate the noise. Then, the Adaptive Sparse Attention Network (ASAN) is added in the model construction stage to improve the training efficiency of the model. The reconstructed degraded data are features extracted by the CNN-LSTM-ASAN model. Finally, the proposed method is validated against models such as DCLA, using the NASA public datasets, the CALCE public datasets, and the self-use datasets. And the results show that the root mean square error (RMSE) of the model is below 1.5%.
Design and Analysis of a Three-Phase High-Frequency Transformer for Three-Phase Bidirectional Isolated DC-DC Converter Using Superposition Theorem
Authors: Dira Yasir S. , Ramli Ahmad Q. , Ungku Amirulddin Ungku Anisa , Tan Nadia M. L. , Buticchi Giampaolo
Published: October 2024

Battery energy storage systems based on bidirectional isolated DC-DC converters (BIDCs) have been employed to level the output power of intermittent renewable energy generators and to supply power to electric vehicles. Moreover, BIDCs use high-frequency transformers (HFTs) to achieve voltage matching and galvanic isolation. Various studies have recently been conducted using soft magnetic materials, such as nanocrystalline, amorphous solids, and ferrite, to develop more compact and effective transformers with superior power densities. The HFTs in three-phase BIDCs are composed of three magnetic cores. However, this leads to low power density and high cost. Besides, the three-phase (3P) ferrite core has not been investigated for high-power converters such as 3P-BIDCs. This paper presents the design and development of a 3P-EE ferrite magnetic core for 3P-BIDCs. The area product design method was used to determine the core and winding design. The paper also proposes the use of the superposition theorem in conducting a magnetic circuit analysis to predict the flux density and magnetising inductance of the transformer core. Moreover, the use of the superposition theorem allowed the required air-gap length for balancing the distribution of flux density and magnetizing inductance in the transformer core to be determined. The balanced flux distribution and magnetizing inductance resulted in a uniform core loss and temperature in the transformer. This paper also presents the experimental results of the designed HFT operated in a 300-V, 3-kW 3P-BIDC. The experimental results showed that the proposed HFT achieved a balanced flux density and magnetizing inductance with a high power density and low cost. Moreover, the transformer performed at a maximum efficiency of 98.67%, with a decrease of 3.33 °C in the overall temperature of the transformer as compared to the transformer without air gaps.
Landscape Perception in Cultural and Creative Industrial Parks: Integrating User-Generated Content (UGC) and Electrodermal Activity Insights
Authors: Wang Xuefei , Zhu Baoyao , Chen Zhiqi , Ma Dawei , Sun Chuanhao , Wang Mo , Jiang Xing
Published: October 2024

As economic growth and societal shifts reshape urban environments, cultural and creative industrial parks are emerging as vital contributors to sustainable urban development. The design of these landscapes plays a pivotal role in enhancing user satisfaction, increasing spatial attractiveness, and promoting eco-friendly urban practices. This study examines visitor landscape perception preferences in the Textile and Garment Cultural and Creative Industrial Park, located in Haizhu District, Guangzhou, through a novel methodology combining user-generated content (UGC), deep learning models, outdoor electrodermal activity (EDA) measurements, and questionnaire surveys. The UGC-based landscape recognition model achieved an accuracy of 86.8% and was validated against user preferences captured through questionnaires. Results demonstrate that visitors prefer areas featuring cultural landmarks and natural elements, while spaces dominated by human activity and transportation infrastructure are less favored. Key landscape elements, such as signage, thematic sculptures, brand logos, and trees, were identified as highly preferred features within the park. While EDA experiments revealed significant variations in physiological responses across different spatial settings, no strong correlation was observed between EDA indicators and subjective questionnaire scores. This integrative approach enables a comprehensive, objective assessment of landscape perception, providing a data-driven, user-centered framework for improving landscape design in cultural and creative industrial parks.
Quantitative Tracking of Seasonal River Pollution Sources and Integration of Sustainable Development Goals in Hilly Regions
Authors: Zhang Wanping , Gao Dongdong , Wang Chun , Shi Hongle , Tian Xiaogang , Ren Xingnian , Liu Siyao , Guo Mingkun , He Peng
Published: October 2024

In line with the Sustainable Development Goals, a comprehensive understanding and precise quantification of the temporal and spatial characteristics of water quality is essential to identify sources of pollution in basins and to protect river headwaters to maintain water safety throughout basins. However, there is a lack of systematic quantitative tracking of seasonal river pollution sources in hilly areas in southwest China. In this study, the spatial and temporal characteristics of the water environmental factors in the Yaoshi River basin, the causes of pollution, and the main sources of nitrogen pollution were systematically investigated using geographic information systems and statistics. The results showed that the main pollutants in the river as a whole included five-day biological oxygen demand (BOD5), oxygen demand (COD), ammonium (NH4+), total phosphorus (TP), and total nitrogen (TN). Nitrogen pollution was the most serious, and various environmental factors caused seasonal variations and different spatial distributions in this pollutant. Temporally, the TP and COD concentrations were highest during the wet season, while the NH4+, TN, and BOD5 concentrations were highest during the dry season. Spatially, BOD5, COD, and TP concentrations were ranked upstream < downstream < midstream, while TN and NH4+ concentrations were ranked downstream < midstream < upstream. The main sources of pollution in the study area were domestic activities (34.94%), agricultural activities (40.12%), and mixed organic and natural sources (24.94%). Notably, manure effluent dominates nitrate nitrogen sources, while fertilizer inputs minimally contribute during mean-flow and dry seasons, and atmospheric deposition contributes during the wet season. These findings provide important data for improving water quality in the Yaosi River Basin, promoting sustainable agricultural practices, alleviating water scarcity, and advancing the region’s Sustainable Development Goals. In addition, this study can provide reference for the development of sustainable development management strategies for seasonal rivers in other hilly areas and promote broader environmental sustainability efforts.
Automation in Modular Construction Manufacturing: A Comparative Analysis of Assembly Processes
Authors: Ouda Enaam , Haggag Mahmoud
Published: October 2024

According to the UNHCR, 117.2 million people have been displaced in 2023, with the rate and scale of displacement surpassing the resources available to assist those impacted. Modular construction is favored over traditional methods to meet the urgent demand for affordable housing as it overcomes challenges like long project timelines, high costs, and safety and environmental issues. However, manual assembly is often slow and prone to errors, resulting in inefficiencies and higher costs. While advanced technologies could improve the process, there is limited research on automating assembly in modular construction. This research aims to assess how automation affects the time efficiency and cost of the modular construction process, aiming to improve affordable housing production by automating modular construction. The research follows a quantitative approach, collecting data through simulation to evaluate the effectiveness of integrating robotics in modular construction assembly processes. It compares the performance of automated and manual assembly processes, focusing on resource utilization, time savings, and cost implications. The results reveal that modular manufacturing automated assembly offers faster assembly times and improved cost efficiency, leading to higher productivity and lower overall construction costs. By conducting a detailed analysis, this research provides insights that can guide the integration of automation into modular construction manufacturing.
A Sustainability Study upon Manufacturing Thermoplastic Building Materials by Integrating Chicken Feather Fibers with Plastic Waste
Authors: Aradoaei Sebastian , Constantin Mirela Alina , Constantin Lucian Alexandru , Aradoaei Mihaela , Ciobanu Romeo Cristian
Published: October 2024

The article explains how to make thermoplastic construction materials by combining waste from chicken feathers with plastic waste. The initial phase focused on a new and environmentally friendly method of sterilizing raw feathers using microwave radiation inside sealed ovens with circulating air. Additionally, composites containing varying feather amounts using two different polymer matrices were fabricated through an injection process, followed by mechanical and physical tests on the samples. Because of their excellent characteristics, products made from a combination of chicken feather waste and plastic waste could effectively replace traditional wood–plastic composites that are polyvinyl chloride-based. The recycling technology was assessed for its environmental impact, and sustainability was proven economically and environmentally.
Mechanism Analysis and Path Study of Digital Transformation on Corporate Governance: Evidence from Chinese Listed Companies
Authors: Yang Songling , Tai Yafei , Liu Jianing
Published: October 2024

Corporate digital transformation, primarily driven by data and leveraging digital technologies and mathematical algorithms such as Internet+, big data, cloud computing, artificial intelligence, and blockchain, is a crucial enabler of sustainable development. This transformation integrates various aspects of corporate production and operations, enhancing the level of digital operations and ultimately contributing to high-quality and sustainable development. This paper, based on data from listed companies in China’s A-shares from 2007 to 2021, theoretically articulates the intrinsic mechanism between corporate digital transformation and corporate governance level, with a focus on sustainability. It empirically finds that a higher degree of digital transformation correlates with an improved level of corporate governance, fostering sustainable practices. Further investigation reveals that digital transformation elevates corporate governance by enhancing innovation capabilities, reducing information asymmetry, and promoting sustainable strategies. This paper provides policy insights for promoting corporate digital transformation as a means to achieve sustainability goals and optimizing management’s corporate governance level for long-term sustainable success.
Enhanced Looped Lyapunov Functional for Sampled-Data Control for T-S Fuzzy Systems with Time Delay
Authors: Yang Jin , Gao Wenke
Published: October 2024

This paper addresses the problem of sampled-data control in T-S fuzzy systems with time delays. Initially, a negative-definite criterion is developed for the matrix containing membership functions with the help of the idea of a switching mechanism. Building upon this criterion, a membership-function-based looped Lyapunov functional is introduced. Furthermore, a sampling-time-dependent looped Lyapunov functional is constructed, incorporating crucial information about the sampling instance. Notably, this functional matrix is not constrained to satisfy positive-definiteness, and it varies with each sampling point. By utilizing the enhanced looped Lyapunov functional, less conservative stability conditions and a new controller criterion for the T-S fuzzy system with time delays are derived. This demonstrates that our proposed stability conditions allow for a larger sampling interval compared to existing work. Finally, the proposed method’s effectiveness is demonstrated through the validation of two simulation examples.
Decoding Critical Targets and Signaling Pathways in EBV-Mediated Diseases Using Large Language Models
Authors: Yu Jingwen , Wang Yaohao , Wang Haidong , Wei Zhi , Pei Yonggang
Published: October 2024

Epstein–Barr virus (EBV), a member of the gamma herpesvirus, is the first identified human oncovirus and is associated with various malignancies. Understanding the intricate interactions between EBV antigens and cellular pathways is crucial to unraveling the molecular mechanisms in EBV-mediated diseases. However, fully elucidating EBV–host interactions and the associated pathogenesis remains a significant challenge. In this study, we employed large language models (LLMs) to screen 36,105 EBV-relevant scientific publications and summarize the current literature landscape on various EBV-associated diseases like Burkitt lymphoma (BL), diffuse large B-cell lymphoma (DLBCL), nasopharyngeal carcinoma (NPC), and so on. LLM-generated data indicate that the most-studied EBV-associated pathways are enriched in immune response, apoptosis, cell growth, and replication. The analyses of protein–protein interactions (PPIs) reveal three principal EBV-related protein clusters: TP53-centered apoptotic factors, EBV-associated transcription factors, and immune response elements. Utilizing our dataset and public databases, we demonstrated that BLLF3-targeted TLR2-associated factors are effective diagnostic markers for DLBCL. Next, we confirmed the co-expression of LMP1-targeted calcium pathway factors in BL. Finally, we demonstrated the correlation and co-expression of LMP1-induced PARP1, HIF1A, HK2, and key glycolysis-related factors, further suggesting that LMP1 actively regulates the glycolysis pathway. Therefore, our study presents a comprehensive functional encyclopedia of the interactions between EBV antigens and host signaling pathways across various EBV-associated diseases, providing valuable insights for the development of therapeutic strategies.
Coinfection with Dolphin Morbillivirus (DMV) and Gammaherpesvirus in a Spinner Dolphin (Stenella longirostris) Stranded in Sri Lanka
Authors: Pietroluongo Guido , Tucciarone Claudia Maria , Cecchinato Mattia , Si Haiyang , Spadotto Luca , Danyer Işil Aytemiz , Isuru Hewakottege , Wijesundera Kavindra , Ekanayake Lalith , Centelleghe Cinzia , Mazzariol Sandro
Published: October 2024

Following the X-Press Pearl maritime disaster off the coast of Sri Lanka, a stranded spinner dolphin (Stenella longirostris) was recovered, and the cause of death was investigated. Post-mortem examinations revealed evidence of by-catch, but a natural coinfection with dolphin morbillivirus (DMV) and gammaherpesvirus was detected by further analyses, marking the first documented case of a dual viral infection in this species within the region. Molecular diagnostics, including PCR and sequencing, were performed on tissue imprints collected on FTA® cards, confirming the presence of DMV in the prescapular lymph node and gammaherpesvirus in the lesions in the oral cavity. The concurrent detection of DMV and gammaherpesvirus raises significant concerns regarding the potential impacts of environmental stressors, such as chemical pollutants from the X-Press Pearl maritime disaster, on exacerbating susceptibility to viral infections in marine mammals. These findings highlight the need for ongoing surveillance of cetacean populations in the Indian Ocean to better understand pathogen circulation and health and conservation implications of anthropogenic activities on the marine ecosystem.
Preparation of Slow-Release Potassium Persulfate Microcapsules and Application in Degradation of PAH-Contaminated Soil
Authors: Wu Hao , Yang Yuting , Sun Lina , Wang Yinggang , Wang Hui , Wang Xiaoxu
Published: October 2024

Due to potassium persulfate’s excessive reaction speed and severe impact on the soil environment, slowing down the reaction rate and reducing its environmental impact is an important but challenging matter. Hence, microencapsulation technology was taken to modify potassium persulfate, and potassium persulfate microcapsules were used to remediate the PAHs-contaminated soil. The results of XRD and an infrared spectrum identified that the core material (potassium persulfate) exists after being encapsulated by the wall material (stearic acid), and there was no chemical reaction between the core material and wall material. The results of the sustained release effect and kinetic equation showed that the release rate of the potassium persulfate microcapsules was close to 60% after 48 h, and it had a good sustained-release effect compared with previous studies. The results of the radical probe revealed that the free radicals produced from potassium persulfate microcapsules activated by Fe2+ were the main reasons for the degradation of PAHs, and SO4−· played the most important major role in the degradation of PAHs, followed by ·OH, and the reducing substances also played an auxiliary role. The results also suggested that potassium persulfate microcapsules not only degraded PAHs in soil (53.6% after 72 h) but also had fewer negative effects on the environment, and they even promoted the growth and development of microorganisms and increased the germination rate of seeds due to the slow-release effect of the microcapsules. This work reveals the degradation mechanism of potassium persulfate microcapsules and provides a new amendment of potassium persulfate in the remediation of PAHs-contaminated soil.
Impacts of Missing Buoy Data on LSTM-Based Coastal Chlorophyll-a Forecasting
Authors: Zhang Caiyun , Ding Wenxiang , Zhang Liyu
Published: October 2024

Harmful algal blooms (HABs) pose significant threats to coastal ecosystems and public health. Accurately predicting the chlorophyll-a (Chl) concentration, a key indicator of algal biomass, is crucial for mitigating the impact of algal blooms. Long short-term memory (LSTM) networks, as deep learning tools, have demonstrated significant potential in time series forecasting. However, missing data, a common occurrence in environmental monitoring systems, can significantly degrade model performance. This study examines the impact of missing input parameters, particularly the absence of Chl data, on the predictive performance of LSTM models. To evaluate the model’s performance and the effectiveness of different imputation techniques under various missing data scenarios, we used data collected from 2008 to 2018 for training and data from 2020 and 2021 for testing. The results indicated that missing Chl data can significantly reduce predictive accuracy compared to other parameters such as temperature or dissolved oxygen. Edge-missing data had a more pronounced negative effect on the model than non-edge missing data, and the model’s performance declined more steeply with longer periods of missing data. The prediction of high Chl concentrations was relatively more negatively affected by missing data than by low Chl concentrations. Although LSTM imputation methods help mitigate the impact of missing data, ensuring data completeness remains critical. This study underscores the importance of reliable data collection and improved imputation strategies for accurate forecasting of algal blooms.
Triple Collocation-Based Model Error Estimation of VIC-Simulated Soil Moisture at Spatial and Temporal Scales in the Continental United States in 2010–2020
Authors: Li Yize , Lu Jianzhong , Huang Pingping , Chen Xiaoling , Jin Heping , Zhu Qiang , Luo Huiheng
Published: October 2024

The model error is a direct reflection of the accuracy of the model simulation. However, it is challenging to estimate the model error due to the presence of numerous uncertainties inherent to the atmospheric and soil data, as well as the structure and parameters of the model itself. This paper addresses the fundamental issue of error estimation in the simulation of soil moisture by the Variable Infiltration Capacity (VIC) model, with a particular focus on the continental United States from 2010 to 2020. The paper develops a model error estimation method based on the Triple Collocation (TC) error estimation and in situ data validation of the VIC model at different temporal and spatial scales. Furthermore, it addresses the issue of failing to consider the variability of temporal and spatial scales in model error estimations. Furthermore, it generates the standard product data on soil moisture simulation errors for the VIC model in the continental United States. The mean of the simulation error variance of the VIC model, estimated using the TC method for spatially scaled soil moisture in the continental United States, is found to be 0.0045 (m3/m3)2, with a median value of 0.0042 (m3/m3)2. The mean time-scale error variance of the VIC model, validated using ground station data, is 0.0096 (m3/m3)2, with a median value of 0.0078 (m3/m3)2. Concurrently, the paper employs Köppen climate classification and land cover data as supplementary data, conducting a comprehensive investigation and analysis of the characteristics and alterations of the VIC model error in the study area from both temporal and spatial perspectives. The findings indicate a proclivity for reduced error rates during the summer months and elevated rates during the winter, with lower rates observed in the western region and higher rates in the eastern region. The objective of this study is twofold: firstly, to conduct a quantitative assessment and analysis of the VIC model’s simulation capabilities; secondly, to validate the accuracy and quality of the soil moisture products simulated by the model. The accurate estimation of model errors is a fundamental prerequisite for the numerical simulation and data assimilation of models, which has a vast range of applications in numerical meteorological and hydrological forecasting, natural environment monitoring, and other fields.
Investigation and Improvement of Centrifugal Slurry Pump Wear Characteristics via CFD-DEM Coupling
Authors: Wang Zengqiang , Peng Guangjie , Chang Hao , Hong Shiming , Ji Guangchao
Published: October 2024

Centrifugal slurry pumps are extensively applied in industrial industries such as power metallurgy, petrochemicals, deep-sea mining, and other industrial fields. The primary objective of this research is to assess how conveying settings and particle characteristics influence the 100SHL4147 slurry pump’s collision and erosion properties. Firstly, the computational fluid dynamics–discrete element method (CFD-DEM) coupling model fully coupled particle–fluid co-flow numerical simulation interface is built by utilizing the C++ language and the results are proven with tests. Subsequently, the simulation examines the wear properties of different sections through which the flow passes in the 100SHL4147 centrifugal slurry pump. In addition, following theoretical guidance, the slurry pump impeller’s wear resistance performance can be improved by adjusting design factors such as the intake edge location and the blade wrap angle. The results are as follows. It is recommended to replace the impeller promptly due to the findings that indicate that the entire blade’s pressure surface is vulnerable to different degrees of erosion under high-concentration situations. When the particle size increased from 0.4 to 0.8 mm, the wear rate decreased by up to 15%, as fewer particles were transported, lowering the collision frequency. Conversely, smaller particles intensify component wear. Adjusting the blade wrap angle from 66° to 96° reduced impeller and volute wear by an estimated 20%, enhancing the durability but slightly decreasing the delivery capacity. Extending the blade’s leading edge toward the intake improved the flow capacity, although it increased the wear frequency from one-third of the pressure surface to the trailing edge.
Application of Metal–Organic Framework-Based Composite Materials for Photodegradation of Dye Pollutants in Wastewater
Authors: Mahmoudi Farzaneh , Bachas Leonidas G.
Published: October 2024

Water pollution is one of the main challenges that severely affects human health and aquatic ecosystems. Chemical pollutants, including industrial waste, agricultural runoff, and clinical sources, can contaminate water. Photocatalytic processes present clean, renewable, and efficient techniques for degrading organic contaminants in wastewater. Metal–organic frameworks (MOFs) are one of the more efficient materials in wastewater remediation due to their significantly high surface area and tunable structures. This review summarizes the development of novel composite materials based on MOFs for the photocatalytic decomposition of dye contaminants in wastewater. Different synthesis methods of MOFs and composite materials are explored. Several strategies for enhancing the photocatalytic activity of MOFs are discussed. Photocatalytic reaction conditions and suggested mechanisms are summarized, particularly for eliminating dye contaminants using MOF-based composite materials. The designed composite materials demonstrate improved stability and photocatalytic activity. This review provides strategies for designing MOF-based composite materials and improving their efficiency and stability for the photocatalytic elimination of dye pollutants in wastewater. Additionally, the review addresses challenges in advancing MOF-based composite materials.