bluuebunny/crossref_metadata_2025 huggingface dataset:
Gemstones from the Medicean Collection of the Natural History Museum of Florence (Italy): New Insights from Micro-Raman and PIXE-PIGE Analyses
Authors: Fabrizi Lucilla , Chiari Massimo , Moggi Cecchi Vanni , Manca Rosarosa , Benvenuti Marco
Published: January 2025

The initial nucleus of gemstones at the Natural History Museum of the University of Florence (Italy) is linked to the significant collection of the Medici family, who began it as early as the 15th century. The present research aims to study this collection in order to (1) comprehensively review the archival and catalogue information available; (2) identify the mineralogical species correctly; and (3) gather information on the potential provenance of the gem deposits. To address these objectives, fifty gems were investigated using entirely non-invasive methods, ensuring the preservation of the collection’s precious and historical value. All specimens underwent autoptic observation and micro-Raman analysis, while a selection was further examined using PIXE-PIGE to characterise their chemical composition, including trace elements. The gems were attributed to seven mineral species: emerald, topaz, grossular, cordierite, quartz, orthoclase, and tourmaline. One gem was identified as a fake, made of glass and likely produced in the 17th century. Twenty-nine of the historical attributions in the catalogue were found to be incorrect and were subsequently revised. In some cases, the trace elements and mineral inclusions identified in the gems enabled the determination of potential provenance deposits, which were then compared with the available archival information.
The Interfacial Dilational Rheology of Surfactant Solutions with Low Interfacial Tension
Authors: Ma Guoxuan , Gong Qingtao , Xu Zhicheng , Jin Zhiqiang , Zhang Lei , Ma Guiyang , Zhang Lu
Published: January 2025

In this paper, the spinning drop method was used to measure the oil–water interfacial dilational modulus of four different types of surfactants with low interfacial tension (IFT), including the anionic surfactant sodium dodecyl sulfate (SDS), the nonionic surfactant Triton X-100 (TX100), the zwitterionic surfactant alkyl sulfobetaine (ASB), and the extended surfactant alkyl polyoxypropyl ether sodium sulfate (S-C13PO13S). Based on the experimental results, we found that the spinning drop method is an effective means of measuring the interfacial dilational modulus of the oil–water interface with an IFT value of lower than 10 mN/m. For common surfactants SDS and TX100, the interfacial dilational modulus decreases rapidly to near zero with an increase in concentration when the IFT is lower than 1 mN/m. On the other hand, ASB has the highest interfacial dilatation modulus of 50 mN/m, which comes from the flatness of its unique hydrophilic group structure. The interfacial dilational modulus of S-C13PO13S showed a moderate plateau value of 30 mN/m with a broader concentration change. This is due to the fact that the main relaxation process dominating the interfacial film properties comes from the long helical polyoxypropyl chain. Through the large-size hydrophilic groups in betaine molecules and the long PO chains in the extended surfactant molecules, an interfacial film with controllable strength can be formed in a low IFT system to obtain a higher interfacial dilational modulus. This is of great significance in improving the emulsification and oil displacement of chemical flooding in reservoir pores.
Effect of TiO2 Morphology on the Properties and Photocatalytic Activity of g-C3N4/TiO2 Nanocomposites Under Visible-Light Illumination
Authors: Roškarič Matevž , Žerjav Gregor , Zavašnik Janez , Finšgar Matjaž , Pintar Albin
Published: January 2025

This study focused on the preparation and investigation of g-C3N4/TiO2 photocatalysts using different TiO2 morphologies (anatase nanoparticles (TPs), poorly crystalline nanotubes (aTTs), and well-crystalline anatase nanorods (TRs)) and self-synthesized g-C3N4 (CN). The synthesis of the g-C3N4/TiO2 composites was carried out using a mortar mixing technique and a g-C3N4 to TiO2 weight ratio of 1:1. In addition, the g-C3N4/TiO2 composites were annealed in a muffle furnace at 350 °C for 2 h in air. The successful formation of a g-C3N4/TiO2 composite with a mesoporous structure was confirmed using the results of XRD, N2 physisorption, and FTIR analyses, while the results of microscopic analysis techniques confirmed the preservation of TiO2 morphology in all g-C3N4/TiO2 composites investigated. UV-Vis DR measurements showed that the investigated g-C3N4/TiO2 composites exhibited visible-light absorption due to the presence of CN. The results of solid-state photoluminescence and electrochemical impedance spectroscopy showed that the composites exhibited a lower charge recombination compared to pure TiO2 and CN. For example, the charge transfer resistance (RCT) of the CNTR/2 composite of TR and CN calcined in air for 2 h was significantly reduced to 0.4 MΩ, compared to 0.9 MΩ for pure TR and 1.0 MΩ for pure CN. The CNTR/2 composite showed the highest photocatalytic performance of the materials tested, achieving 30.3% degradation and 25.4% mineralization of bisphenol A (BPA) dissolved in water under visible-light illumination. In comparison, the pure TiO2 and CN components achieved significantly lower BPA degradation rates (between 2.4 and 11.4%) and mineralization levels (between 0.6 and 7.8%). This was due to (i) the presence of Ti3+ and O-vacancies in the TR, (ii) enhanced heterojunction formation, and (iii) charge transfer dynamics enabled by a dual mixed type-II/Z scheme mechanism.
Facile Preparation of Flexible Phenolic-Silicone Aerogels with Good Thermal Stability and Fire Resistance
Authors: Su Zengyue , Zheng Zhenrong , Zuo Xiaobiao , Luo Lijuan , Guo Yaxin
Published: January 2025

A huge challenge is how to prepare flexible silicone aerogel materials with good flame retardancy, thermal stability, and hydrophobic properties. In this paper, resorcinol–formaldehyde was introduced into the silicone network composed of methyltrimethoxysilane (MTMS), phenyltriethoxysilane (PTES), and dimethyldimethoxysilane (DMDMS). Flexible hybrid aerogels with excellent thermal insulation, flame retardant, and hydrophobic properties were prepared by the sol–gel method and ambient pressure drying (APD), and the preparation process does not require long-term solvent exchange, only about 3 h of soaking and washing of the wet gel. The results show that the prepared phenolic-silicone aerogel has low density (0.093 g/cm3), low thermal conductivity (0.041 W/m·K), high flexibility, and compression fatigue resistance. The phenolic microspheres are bonded to the silicone skeleton to maintain the original flexibility. After 50% compression deformation, it returns to the original size normally, and there is no significant change in the stress of the sample after 50 compression cycles. Compared with pure silicone aerogels, the hybrid aerogels doped with phenolic have better char yield (65.28%) and higher decomposition temperature (609 °C). The hybrid aerogel sample has good flame-retardant properties, which can withstand alcohol lamp burning without being ignited. The micron-sized phenolic beads give the hybrid aerogels better hydrophobic properties, showing a higher static water contact angle (152°). The excellent thermal and mechanical properties mean that the hybrid aerogels prepared in this paper have good application prospects for aerospace, outdoor equipment, and other fields.
Intention to Work with Social Robots: The Role of Perceived Robot Use Self-Efficacy, Attitudes Towards Robots, and Beliefs in Human Nature Uniqueness
Authors: Giger Jean-Christophe , Piçarra Nuno , Pochwatko Grzegorz , Almeida Nuno , Almeida Ana Susana
Published: January 2025

Recent studies have enlightened the crucial role of perceived robot use self-efficacy in human robot interaction. This paper investigates the interplay between perceived robot use self-efficacy, attitudes towards robots, and beliefs in human nature uniqueness (BHNU) on the intention to work with social robots. Participants (N = 117) first filled out a questionnaire measuring their BHNU and attitudes towards robots. Then, they were randomly exposed to a video displaying a humanoid social robot (either humanlike or mechanical). Finally, participants indicated their robot use self-efficacy and their intention to work with the displayed social robot. Regression and serial mediation analyses showed the following: (1) the intention to work with social robots was significantly predicted by robot use self-efficacy and attitudes towards robots; (2) BHNU has a direct influence on attitudes towards robots and an indirect influence on the intention to work with social robots through attitudes towards robots and robot use self-efficacy. Our findings expand the current research on the impact of perceived robot use self-efficacy on intention to work with social robots. Implications for human robot interaction and human resource management are discussed.
Surface Functionalization of Nanocarriers with Anti-EGFR Ligands for Cancer Active Targeting
Authors: Spada Alessandra , Gerber-Lemaire Sandrine
Published: January 2025

Active cancer targeting consists of the selective recognition of overexpressed biomarkers on cancer cell surfaces or within the tumor microenvironment, enabled by ligands conjugated to drug carriers. Nanoparticle (NP)-based systems are highly relevant for such an approach due to their large surface area which is amenable to a variety of chemical modifications. Over the past decades, several studies have debated the efficiency of passive targeting, highlighting active targeting as a more specific and selective approach. The choice of conjugation chemistry for attaching ligands to nanocarriers is critical to ensure a stable and robust system. Among the panel of cancer biomarkers, the epidermal growth factor receptor (EGFR) stands as one of the most frequently overexpressed receptors in different cancer types. The design and development of nanocarriers with surface-bound anti-EGFR ligands are vital for targeted therapy, relying on their facilitated capture by EGFR-overexpressing tumor cells and enabling receptor-mediated endocytosis to improve drug accumulation within the tumor microenvironment. In this review, we examine several examples of the most recent and significant anti-EGFR nanocarriers and explore the various conjugation strategies for NP functionalization with anti-EGFR biomolecules and small molecular ligands. In addition, we also describe some of the most common characterization techniques to confirm and analyze the conjugation patterns.
Distinguishing Early from Late Mild Cognitive Impairment Using Magnetic Resonance Free-Water Diffusion Tensor Imaging
Authors: Bergamino Maurizio , McElvogue Molly M. , Stokes Ashley M. ,   Alzheimer’s Disease Neuroimaging Initiative
Published: January 2025

Mild Cognitive Impairment (MCI) is a transitional stage between normal aging and Alzheimer’s disease. Differentiating early MCI (EMCI) from late MCI (LMCI) is crucial for early diagnosis and intervention. This study used free-water diffusion tensor imaging (fw-DTI) to investigate white matter differences and voxel-based correlations with Mini–Mental State Examination (MMSE) scores. Data from the Alzheimer’s Disease Neuroimaging Initiative included 476 healthy controls (CN), 137 EMCI participants, and 62 LMCI participants. Significant MMSE differences were found between the CN and MCI groups, but not between EMCI and LMCI. However, distinct white matter changes were observed: LMCI showed a higher f-index and lower fw-fractional anisotropy (fw-FA) compared to EMCI in several white matter regions. These findings indicate specific white matter tracts involved in MCI progression. Voxel-based correlations between fw-DTI metrics and MMSE scores further supported these results. In conclusion, this study provides crucial insights into white matter changes associated with EMCI and LMCI, offering significant implications for future research and clinical practice.
Unravelling the Neuroprotective Effects of a Novel Formulation Based on Plant Extracts, Mg, and Vitamin B6
Authors: Di Simone Simonetta Cristina , Acquaviva Alessandra , Libero Maria Loreta , Nilofar Nilofar , Tunali Fatma , Angelini Paola , Angeles Flores Giancarlo , Cusumano Gaia , Recinella Lucia , Leone Sheila , Orlando Giustino , Zengin Gokhan , Menghini Luigi , Ferrante Claudio , Chiavaroli Annalisa
Published: January 2025

The aim of the present study was to investigate the phenolic composition and the efficacy of an innovative formulation based on Mg, Vitamin B6, and water extracts from Vitex agnus-castus, Crocus sativus, Melissa officinalis, Betula pendula, and Betula pubescens developed as an effective tool to face neuroinflammation and depression symptoms occurring in premenstrual syndrome (PMS). The formulation was analyzed through colorimetric and liquid chromatography methods for determining the content in phenols and flavonoids. Additionally, scavenging/reducing properties were investigated via 2,2-diphenyl-1-picrylhydrazyl (DPPH,) 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS), and horseradish peroxidase assays. The biocompatible limits were determined via allelopathy, the brine shrimp lethality test, and Daphnia magna cardiotoxicity assay. The formulation was then assayed in an experimental model constituted by isolated mouse cortex specimens exposed to K+ 60 mM Krebs–Ringer buffer, a toxic depolarizing stimulus able to reproduce the burden of inflammation/oxidative stress and the increased serotonin (5-hydroxytryptamine, 5-HT) impoverishment occurring in different neurological and psychiatric conditions, including depression. The results of the phytochemical analysis showed that the formulation is rich in benzoic acids, namely gentisic acid (155.31 µg/mL) and phenylethanoid compounds, namely hydroxytyrosol (39.79 µg/mL) that support the antioxidant effects measured via DPPH (IC50: 1.48 mg/mL), ABTS (IC50: 0.42 mg/mL), and horseradish peroxidase (IC50: 2.02 mg/mL) assays. The ecotoxicological models indicated the formulation as non-toxic, permitting the identification of a biocompatible concentration (1000 µg/mL) to be used in isolated mouse cortex exposed to K+ 60 mM Krebs–Ringer buffer. In this model, the gene expression of cyclooxygenase-2 (COX-2), interleukin-6 (IL-6), estrogen receptor-1 (ESR1), prolactin receptor (PRLR), brain-derived neurotrophic factor (BDNF), and serotonin transporter (SERT) was determined by real-time PCR. In the isolated mouse cortex, the formula reduced COX-2, IL-6, SERT, ESR1, and PRLR gene expression and increased BDNF and IL-10 gene expression. Overall, the study corroborated the use of the formulation as an innovative tool to contrast inflammation, oxidative stress, and neurotransmitter impairment associated with PMS.
Genomic and Drug Resistance Profile of Bovine Multidrug-Resistant Escherichia coli Isolated in Kazakhstan
Authors: Alexyuk Pavel G. , Bogoyavlenskiy Andrey P. , Moldakhanov Yergali S. , Akanova Kuralay S. , Manakbayeva Adolat N. , Kerimov Timur , Berezin Vladimir E. , Alexyuk Madina S.
Published: January 2025

While studying the prevalence and profile of antibiotic resistance among E. coli isolated from the feces of calves with signs of colibacillosis, a strain with a wide spectrum of drug resistance was isolated. Whole-genome sequencing, followed by bioinformatic processing and the annotation of genes of this strain, showed that the genome has a total length of 4,803,482 bp and contains 4986 genes, including 122 RNA genes. A total of 31% of the genes are functionally significant and represent 26 functional groups. Additionally, 55 antibiotic resistance genes were revealed. A phenotypic drug-resistance study was performed according to CASFM and CLSI guidelines, which showed that the investigated strain was resistant to eight antibacterial drugs of different classes, including colistin. This is the first report on the AMR profile of an E. coli isolate obtained from a sick calf with evidence of escherichiosis in Kazakhstan. The provided information on the genome will be valuable in studying the evolution and development of antibiotic-resistant forms of E. coli and increase our knowledge of pathogenicity. It may also be a source for future comparative studies of the virulence and drug resistance of E. coli isolates.
The Role of Pathogens in Bumblebee Decline: A Review
Authors: Chen Huanhuan , Bashir Nawaz Haider , Li Qiang , Liu Chao , Naeem Muhammad , Wang Haohan , Gao Wenrong , Corlett Richard T. , Liu Cong , Vidal Mayra C.
Published: January 2025

Bumblebees, the most important wild pollinators in both agricultural and natural ecosystems, are declining worldwide. The global decline of bumblebees may threaten biodiversity, pollination services, and, ultimately, agricultural productivity. Several factors, including pesticide usage, climate change, habitat loss, and species invasion, have been documented in the decline of bumblebee species, but recent studies have revealed the dominating role of pathogens and parasites over any of these causes. Unfortunately, there is a lack of a full understanding of the role of pathogens and parasites in the decline of bumblebee species. The current study provides a comprehensive review of how pathogens and parasites contribute to the decline of bumblebee species. The study also explores the prevalence of each pathogen and parasite within bumblebee populations. Furthermore, we address the synergistic effects of pathogens and other stressors, such as pesticides, climatic effects, and habitat loss, on bumblebee populations. To summarize, we propose possible conservation and management strategies to preserve the critical role of bumblebees in pollination services and thus to support ecosystem and agricultural health.
Cross-Linked Poly(methyl methacrylate) Nanocomposites’ Synthesis, Characterization, and Antibacterial Effects
Authors: Alkayal Nazeeha S. , Al Ghamdi Mashail A.
Published: January 2025

Polymer networks were synthesized using the condensation method between PMMA and melamine as cross-linkers. CuO nanoparticles (NPs) and activated carbon (AC) were used as a filler. The final products PMMA/Mel, PMMA/Mel-CuO, and PMMA/Mel-AC were tested for antibacterial activities against E.coli and S. aureus. The chemical structure and composition, thermal properties, and surface morphology of the new PMMA/Mel-based nanocomposites were investigated by various techniques. The XRD and EDX results showed the successful incorporation of CuO NPs and AC into the polymer matrix. Also, the thermal stability of the PMMA/Mel polymer was significantly enhanced after adding CuO nanoparticles. This finding showed that the PMMA/Mel-CuO and PMMA/Mel-AC nanocomposites have greater activity against both bacteria than PMMA/Mel. The PMMA/Mel-CuO and PMMA/Mel-AC polymers showed high activity against S. aureus bacteria, with inhibition zones of 22.6 mm and 11.3 mm, respectively. This confirms that small-sized nanoparticles have an effective role in killing bacterial cells.
Competitive Potential of Stable Biomass in Poland Compared to the European Union in the Aspect of Sustainability
Authors: Wyszomierski Rafał , Bórawski Piotr , Holden Lisa , Bełdycka-Bórawska Aneta , Rokicki Tomasz , Parzonko Andrzej
Published: January 2025

Biomass is the primary source of renewable energy in Poland. Its share in renewable energy production in Poland has decreased in recent years, but it still maintains a nearly 70% share. Poland has extensive forest and straw resources, such as pellets, which can be used for stable biomass production. The main objective of this research was to understand the potential of plant biomass production for energy purposes in Poland and other European Union (EU) countries in terms of sustainable development. The period of analysis covered 2000–2022. Secondary data from Statistical Poland and Eurostat were used. The primary research method was the Augmented Dickey–Fuller (ADF) test, which aimed to check the stationarity of stable biomass. Moreover, we calculated the Vector Auto-Regressive (VAR) model, which was used to develop the forecast. The indigenous production of solid biomass in 2022 decreased to 363,195 TJ, while in 2018, it was 384,914 TJ. Our prognosis confirms that biomass will increase. The prognosis based on the VAR model shows an increase from 365,395 TJ in 2023 to 379,795 (TJ) in 2032. Such countries as France, Germany, Italy, Spain, Sweden, and Finland have a bigger potential for solid biomass production from forests because of their higher area. As a result, Poland’s biomass production competitiveness is varied when compared to other EU nations; it is lower for nations with a large forest share and greater for those with a low forest cover. The two main benefits of producing solid biomass are its easy storage and carbon dioxide (CO2) neutrality. The main advantage is that solid biomass preserves biodiversity, maintains soil fertility, and improves soil quality while lowering greenhouse gas emissions and environmental pollutants. The ability to leave added value locally and generate new jobs, particularly in troubled areas, is the largest social advantage of sustained biomass production.
DVR: Towards Accurate Hyperspectral Image Classifier via Discrete Vector Representation
Authors: Li Jiangyun , Wang Hao , Zhang Xiaochen , Wang Jing , Zhang Tianxiang , Zhuang Peixian
Published: January 2025

In recent years, convolutional neural network (CNN)-based and transformer-based approaches have made strides in improving the performance of hyperspectral image (HSI) classification tasks. However, misclassifications are unavoidable in the aforementioned methods, with a considerable number of these issues stemming from the overlapping embedding spaces among different classes. This overlap results in samples being allocated to adjacent categories, thus leading to inaccurate classifications. To mitigate these misclassification issues, we propose a novel discrete vector representation (DVR) strategy for enhancing the performance of HSI classifiers. DVR establishes a discrete vector quantification mechanism to capture and store distinct category representations in the codebook between the encoder and classification head. Specifically, DVR comprises three components: the Adaptive Module (AM), Discrete Vector Constraints Module (DVCM), and auxiliary classifier (AC). The AM aligns features derived from the backbone to the embedding space of the codebook. The DVCM employs category representations from the codebook to constrain encoded features for a rational feature distribution of distinct categories. To further enhance accuracy, the AC correlates discrete vectors with category information obtained from labels by penalizing these vectors and propagating gradients to the encoder. It is worth noting that DVR can be seamlessly integrated into HSI classifiers with diverse architectures to enhance their performance. Numerous experiments on four HSI benchmarks demonstrate that our DVR scheme improves the classifiers’ performance in terms of both quantitative metrics and visual quality of classification maps. We believe DVR can be applied to more models in the future to enhance their performance and provide inspiration for tasks such as sea ice detection and algal bloom prediction in the marine domain.
The Development and Optimisation of a Urinary Volatile Organic Compound Analytical Platform Using Gas Sensor Arrays for the Detection of Colorectal Cancer
Authors: Arasaradnam Ramesh P. , Krishnamoorthy Ashwin , Hull Mark A. , Wheatstone Peter , Kvasnik Frank , Persaud Krishna C.
Published: January 2025

The profile of Volatile Organic Compounds (VOCs) may help prioritise at-risk groups for early cancer detection. Urine sampling has been shown to provide good disease accuracy whilst being patient acceptable compared to faecal analysis. Thus, in this study, urine samples were examined using an electronic nose with metal oxide gas sensors and a solid-phase microextraction sampling system. A calibration dataset (derived from a previous study) with CRC-positive patients and healthy controls was used to train a radial basis function neural network. However, a blinded analysis failed to detect CRC accurately, necessitating an enhanced data-processing strategy. This new approach categorised samples by significant bowel diseases, including CRC and high-risk polyps. Retraining the neural network showed an area under the ROC curve of 0.88 for distinguishing CRC versus non-significant bowel disease (without CRC, polyps or inflammation). These findings suggest that, with appropriate training sets, urine VOC analysis could be a rapid, low-cost method for early detection of precancerous colorectal polyps and CRC.
Novel MEMS Multisensor Chip for Aerodynamic Pressure Measurements
Authors: Lazić Žarko , Smiljanić Milče M. , Tanasković Dragan , Rašljić-Rafajilović Milena , Cvetanović Katarina , Milinković Evgenija , Bošković Marko V. , Andrić Stevan , Jokić Ivana , Poljak Predrag , Frantlović Miloš
Published: January 2025

The key equipment for performing aerodynamic testing of objects, such as road and railway vehicles, aircraft, and wind turbines, as well as stationary objects such as bridges and buildings, are multichannel pressure measurement instruments (pressure scanners). These instruments are typically based on arrays of separate pressure sensors built in an enclosure that also contains temperature sensors used for temperature compensation. However, there are significant limitations to such a construction, especially when increasing requirements in terms of miniaturization, the number of pressure channels, and high measurement performance must be met at the same time. In this paper, we present the development and realization of an innovative MEMS multisensor chip, which is designed with the intention of overcoming these limitations. The chip has four MEMS piezoresistive pressure-sensing elements and two resistive temperature-sensing elements, which are all monolithically integrated, enabling better sensor matching and thermal coupling while providing a high number of pressure channels per unit area. The main steps of chip development are preliminary chip design, numerical simulations of the chip’s mechanical behavior when exposed to the measured pressure, final chip design, fabrication processes (photolithography, thermal oxidation, diffusion, layer deposition, micromachining, anodic bonding, and wafer dicing), and electrical testing.
Hierarchical Resources Management System for Internet of Things-Enabled Smart Cities
Authors: Papaioannou Christoforos , Dimara Asimina , Papaioannou Alexios , Tzitzios Ioannis , Anagnostopoulos Christos-Nikolaos , Krinidis Stelios
Published: January 2025

The efficient management of IoT systems is fundamental to advancing smart cities while enabling the seamless integration of technologies that enhance urban sustainability and resilience. This paper introduces a Hierarchical Resource Management System (HRMS) tailored for IoT-enabled smart cities, emphasizing a decentralized architecture at the building level and scaling up to city-wide applications. At its core, the system integrates the Adaptive Resilient Node (ARN), designed to autonomously manage energy resources and ensure continuous operation through self-healing capabilities. This study outlines the HRMS architecture, operational workflows, and core functionalities, demonstrating how the hierarchical framework supports real-time decision-making, fault tolerance, and scalable resource allocation. The proposed system’s lightweight inter-node communication enhances workload balancing and system responsiveness, addressing critical challenges in urban energy management. Experimental evaluations show that the system achieves up to a 50% improvement in energy efficiency and a 30% reduction in downtime across various urban environments, highlighting its transformative potential for sustainable and resilient urban growth.
3D Metamaterials Facilitate Human Cardiac MRI at 21.0 Tesla: A Proof-of-Concept Study
Authors: Nurzed Bilguun , Saha Nandita , Millward Jason M. , Niendorf Thoralf
Published: January 2025

The literature reports highlight the transmission field (B1+) uniformity and efficiency constraints of cardiac magnetic resonance imaging (MRI) at ultrahigh magnetic fields (UHF). This simulation study proposes a 3D Metamaterial (MM) to address these challenges. The study proposes a 3D MM consisting of unit cells (UC) with split ring resonator (SRR) layers immersed in dielectric material glycerol. Implementing the proposed MM design aims to reduce the effective thickness and weight of the dielectric material while shaping B1+ and improving the penetration depth. The latter is dictated by the chosen array size, where small local UC arrays can focus B1+ and larger UC arrays can increase the field of view, at the cost of a lower penetration depth. Designing RF antennas that can effectively transmit at 21.0 T while maintaining patient safety and comfort is challenging. Using Self-Grounded Bow-Tie (SGBT) antennas in conjunction with the proposed MM demonstrated enhanced B1+ efficiency and uniformity across the human heart without signal voids. The study employed dynamic parallel transmission with tailored kT points to homogenize the 3D flip angle over the whole heart. This proof-of-concept study provides the technical foundation for human cardiac MRI at 21.0 T. Such numerical simulations are mandatory precursors for the realization of whole-body human UHF MR instruments.
Predicting and Mitigating Delays in Cross-Dock Operations: A Data-Driven Approach
Authors: Altaf Amna , Mehmood Adeel , El Amraoui Adnen , Delmotte François , Lecoutre Christophe
Published: January 2025

Cross-docking operations are highly dependent on precise scheduling and timely truck arrivals to ensure streamlined logistics and minimal storage costs. Predicting potential delays in truck arrivals is essential to avoiding disruptions that can propagate throughout the cross-dock facility. This paper investigates the effectiveness of deep learning models, including Convolutional Neural Networks (CNN), Multilayer Perceptrons (MLPs), and Recurrent Neural Networks (RNNs), in predicting late arrivals of trucks. Through extensive comparative analysis, we evaluate the performance of each model in terms of prediction accuracy and applicability to real-world cross-docking requirements. The results highlight which models can most accurately predict delays, enabling proactive measures for handling deviations and improving operational efficiency. Our findings support the potential for deep learning models to enhance cross-docking reliability, ultimately contributing to optimized logistics and supply chain resilience.
Impact of a Phytogenic Feed Additive on Diarrhea Incidence, Intestinal Histomorphology and Fecal Excretion of F4-Fimbriated Enterotoxigenic Escherichia coli in Post-Weaning Piglets
Authors: Alberto Torres-Pitarch , Keiner Anja , Le Gall Maud , Molist Francesc , Guan Xiaonan , Middelkoop Anouschka , Jiménez-Moreno Encarnación , Balfagón Aitor , Mantovani Graziano , Nofrarías Miquel , Aumiller Tobias
Published: January 2025

This study investigated the effects of a phytogenic feed additive (PFA) containing a blend of herbs, plant extracts and essential oils from the Lamiaceae, Schisandraceae, Zingiberaceae and Fabaceae families on the fecal score, intestinal histomorphology and fecal excretion of F4-fimbriated enterotoxigenic Escherichia coli (F4-ETEC) in post-weaning piglets. Thirty 31-day-old weaned piglets were randomly allocated to three treatment groups. The positive control (PC) group received colistin via drinking water from d 8 to 14 post-weaning and the same basal diet as the negative control (NC) group; the treatment group received the basal diet with PFA supplementation (1 g/kg of feed). The experiment lasted 21 days. At day 9 post-weaning, all piglets were orally administered 3.0 × 1010 CFU/piglet of the F4-ETEC strain. The PC piglets had higher fecal consistency than the NC and PFA piglets. PFA supplementation resulted in a lower percentage of piglets excreting F4-ETEC in the feces on days 4–7 post-challenge than in the NC group (p < 0.05) but a higher percentage versus the PC group on day 3–7 post-challenge (p < 0.05). The number of goblet cells (GCs) in the jejunum of the PFA piglets was higher than the NC and PC piglets (p < 0.01). The GC density in the jejunum of the PFA piglets was larger than in the PC piglets (p < 0.05) and similar to the NC piglets (p > 0.10). Mucus thickness in the jejunum of the PFA piglets was similar to the NC piglets and PC piglets (p > 0.10). In conclusion, PFA supplementation to the F4-ETEC-challenged piglets reduced the prevalence of fecal E. coli excretion and improved jejunal histomorphology.
Energy Cane Ash: Property Assessment for Its Valorization in Sustainable Cementing Systems
Authors: Lyra Gabriela Pitolli , Brichi Lisiane , Roselló Josefa , Borrachero María Victoria , Soriano Lourdes , Payá Jordi , Rossignolo João Adriano
Published: January 2025

Cogeneration with energy cane, a highly productive variety compared to conventional sugarcane, significantly increases ash generation, presenting waste management challenges for the sugar and ethanol industries. This study evaluates the potential of energy cane ash as a sustainable alternative material for partial cement replacement in construction, contributing to circular economy practices. A productivity analysis was conducted for planted areas, and the different parts of sugarcane and energy cane were dried and examined using scanning electron microscopy. These parts were calcined at 450 °C and 600 °C and analyzed using scanning electron microscopy, X-ray fluorescence, particle size distribution, and thermal analysis. The reactivity of the ashes was tested in cement mortars with 5%, 10%, and 20% cement replacement using washed ash. The results revealed that energy cane produces approximately four times more ash per hectare than sugarcane, with leaf ash containing up to 60% silica and stalk ash being rich in potassium. The highest compressive strength was observed in a mortar with 10% cement replacement using washed energy cane ash, achieving 102.43% of the reference value after 28 days of curing, indicating excellent pozzolanic reactivity. These findings highlight the potential of energy cane ash to enhance sustainability in cementitious systems by reducing Portland cement use and promoting waste valorization. Furthermore, the reuse of ash can mitigate waste accumulation and support the development of more sustainable construction materials, contributing to a circular economy and a low-carbon society.
Waste Management of Wind Turbine Blades—A Review of Recycling Methods and Applications in Cementitious Composites
Authors: Jasińska Daria , Dutkiewicz Maciej
Published: January 2025

The decommissioned blades of wind turbines represent a contemporary challenge for waste management. The composites used in their construction, primarily thermosetting materials, as well as fiberglass and carbon fibers, present a range of challenges in terms of recycling these components. Depending on the region of the world, various legal regulations govern the disposal of these elements. One example of a ban is Germany, which, according to forecasts, is also expected to experience the highest accumulation of such waste in Europe. The article is based on a systematic review of the literature, including 59 sources, more than half of which were published in the last five years. The discussion covers the availability of common waste management methods, as well as examples of reusing these components in whole, in part, or after processing. The review emphasizes the need to explore solutions for utilizing wind turbine blades to minimize waste and reduce the consumption of natural resources by recycling waste material. Finally, the authors propose using mechanically shredded elements from wind turbine blades as an additive in cement mixtures.
Linking ESG Management to Corporate Success: The Influence of Board Composition
Authors: Kim Hyeon-Jae , Yang Oh-Suk
Published: January 2025

The main objective of this paper is to examine the impact of ESG management on corporate performance by focusing on board characteristics. To this end, this study uses financial data and empirical panel data of Fortune 300 firms from 2008 to 2021 and firm-specific ESG scores derived from the European Sustainability Reporting Standard (ESRS) to conduct an empirical analysis. Specifically, a panel model analysis was conducted to examine the relationship between ESG management and firm performance using alternative variables on board characteristics. In the basic model analysis, we adopted alternative variables for ESG management and board characteristics and conducted a panel model analysis to examine the relationship between these factors and corporate performance. In the basic model analysis that included board characteristics, only board size (+) and nationality diversity (−) had a statistically significant effect on corporate performance, while gender diversity had no statistically significant effect on corporate performance. However, in the full model analysis, where board characteristics and ESG management were combined, factors E (−) and S (+) had statistically significant effects on firm performance, confirming that the presence of a board of directors leads to better performance. We found that the effects of E and S on firm performance were reversed, indicating that there is a difference in the cost of ESG management by factor. Finally, G did not have a statistically significant relationship with firm performance, which was likely due to the fact that the characteristics of the board were already reflected in ESG, confirming the role of the board. As a result, the board of directors seems to help with the smooth implementation of ESG management by focusing on internal stabilization and communication, suggesting that future research should consider the impact of the board of directors rather than analyzing ESG management in isolation. The results also show that the board of directors in the G sector has a significant impact on ESG management, but it is not treated as an important factor in ESG evaluation criteria, suggesting that it is necessary to reflect factors on stakeholder communication. Finally, the practical implication is that a united board is necessary to implement ESG management in corporate operations.
Exploring Supply-Side Barriers for Commercialization of New Biopolymer Production Technologies: A Systematic Review
Authors: Possidónio Catarina , Farias Ana Rita , Domingos Samuel , Cruz Bernardo , Luís Sílvia , Loureiro Ana
Published: January 2025

The development of new biopolymer production technologies is becoming increasingly relevant for tackling the negative impact of linear plastics. Despite these potential benefits, their production and commercialization still face several obstacles that might hinder their widespread adoption. The present systematic review aimed to offer a thorough analysis of the multi-level supply-side barriers across researchers, policymakers, and industry professionals. Searches were performed in Web of Science, SCOPUS, PubMed, and IEEE Xplore between June and July 2023. Publications between 2019 and 2023 were considered for analysis (n = 176). Content was coded following a PICO structure and the results were reported following the PRISMA checklist. We found that technological and knowledge barriers were the most identified, followed by economic, regulatory, supply stability, and behavioral challenges. Moreover, we found that 82% of the documents identified more than one barrier, reflecting the complex interaction between the different challenges in the field. Fostering interdisciplinary collaboration, establishing clear regulatory frameworks, and enhancing communication strategies are relevant recommendations for overcoming these barriers. These findings draft a multifaceted roadmap of the key barriers in the commercialization of new, sustainable biopolymer production technologies, and carry significant implications for future research, policy development, and industry practices.
A Deep Learning-Based Ensemble Framework to Predict IPOs Performance for Sustainable Economic Development
Authors: Alahmadi Mazin
Published: January 2025

Addressing resource scarcity and climate change necessitates a transition to sustainable consumption and circular economy models, fostering environmental, social, and economic resilience. This study introduces a deep learning-based ensemble framework to optimize initial public offering (IPO) performance prediction while extending its application to circular economy processes, such as resource recovery and waste reduction. The framework incorporates advanced techniques, including hyperparameter optimization, dynamic metric adaptation (DMA), and the synthetic minority oversampling technique (SMOTE), to address challenges such as class imbalance, risk-adjusted metric enhancement, and robust forecasting. Experimental results demonstrate high predictive performance, achieving an accuracy of 76%, precision of 83%, recall of 75%, and an AUC of 0.9038. Among ensemble methods, Bagging achieved the highest AUC (0.90), outperforming XGBoost (0.88) and random forest (0.75). Cross-validation confirmed the framework’s reliability with a median AUC of 0.85 across ten folds. When applied to circular economy scenarios, the model effectively predicted sustainability metrics, achieving R² values of 0.76 for both resource recovery and waste reduction with a low mean absolute error (MAE = 0.11). These results highlight the potential to align financial forecasting with environmental sustainability objectives. This study underscores the transformative potential of deep learning in addressing financial and sustainability challenges, demonstrating how AI-driven models can integrate economic and environmental goals. By enabling robust IPO predictions and enhancing circular economy outcomes, the proposed framework aligns with Industry 5.0’s vision for human-centric, data-driven, and sustainable industrial innovation, contributing to resilient economic growth and long-term environmental stewardship.
Current Trends and Future Prospects in Onion Production, Supply, and Demand in South Korea: A Comprehensive Review
Authors: Imran Muhammad , Kang Hajeong , Lee Sang-Gu , Kim Eun-Ha , Park Hyun-Min , Oh Seon-Woo
Published: January 2025

Onion cultivation in South Korea faces a range of interconnected challenges, shaped by fluctuating supply and demand dynamics, the dominance of imported seed varieties, and the growing issue of fungal pathogens affecting stored onions. In recent years, significant shifts occurred within the onion industry, such as export volumes in 2023 declining to 106 tons compared to 99,506 tons in 2022, while import volumes surged to 113,902 tons to meet domestic demand through the Tariff Rate Quota (TRQ) system. Concurrently, domestic production onion supply in 2023 estimates a total of 1.347 million tons, a 5.2% increase compared to the previous year, due to a 6.3% rise in domestic production. Despite this growth, South Korea’s onion seed market remains heavily dependent on imports, particularly from Japan, underscoring the need for the development of competitive domestic cultivars. Furthermore, environmental conditions such as microclimates in regions like Muan have proven to be critical, as they produce onions with superior nutritional profiles and storability. However, fungal diseases pose persistent threats to storage, resulting in substantial economic losses. However, the country’s reliance on imported varieties and the climate’s effects on cultivation call for more investment in domestic breeding programs and adaptive farming practices. To address these challenges, this review synthesizes historical data, current trends, and the future prospects of onion production, supply, and demand in South Korea. Comprehensive strategies are proposed, including the promotion of adaptive farming practices, investment in domestic breeding programs, and enhanced storage techniques to mitigate fungal pathogens. This work emphasizes the importance of integrated efforts among policymakers, researchers, and industry stakeholders to improve productivity, reduce reliance on imports, and secure a sustainable future for the South Korean onion industry. The findings offer actionable insights for enhancing market competitiveness and achieving agricultural sustainability.
Circular Economy on a Small Scale: The Sustainable Use of Olive Tree Biomass Residues as Feed for Lactating Cows in the Sorrento Peninsula
Authors: Masucci Felicia , Serrapica Francesco , De Luca Lucia , Romano Raffaele , Garofalo Francesca , Di Francia Antonio
Published: January 2025

To enhance the sustainability of marginal olive and dairy farms in the Sorrento peninsula, two separate crossover trials were conducted on two farms in the area to evaluate olive pruning residue (OlPr) and olive mill leaves (OlLes) as forage sources for lactating cows. Each trial lasted six weeks and consisted of two treatment periods, each including a 15-day adaptation phase followed by a 6-day measurement phase. During the measurement phase, milk production, feed intake, and olive residue consumption were assessed for two homogeneous cow groups: one receiving a ration supplemented with olive by-products and the other receiving a control diet. The olive-supplemented groups exhibited higher dry matter intake and roughage consumption (hay + olive residue) compared to the control groups. The intake of OlLes was about 30% higher than that of OlPr. Compared to the respective control, milk from OlLe-fed cows a had higher fat content and a higher fat-to-protein ratio, a more favorable fatty acid composition in terms of higher monounsaturated and polyunsaturated fatty acids and conjugated linoleic acid contents, a reduced atherogenic index, and a saturated-to-unsaturated ratio. Likely due to the lower level of olive by-product ingestion, only marginal differences were observed in milk fatty acid composition of cows fed OlPr compared to the control. We conclude that the use of OlLes in dairy cow diets may represent a promising strategy for improving milk quality, promoting a more circular agricultural system, reducing reliance on external feed inputs, and mitigating the environmental impact of both olive and milk production.
Sustainable Management of Nitrile Butadiene Rubber Waste Through Pyrolysis
Authors: Pathiraja Kasun , Nilmalgoda Helitha , Wijethunga Isuru , Koswattage Kaveenga
Published: January 2025

Many industries use synthetic rubber for various industrial purposes; thus, disposal of synthetic waste rubber into the environment causes huge environmental problems. A feasibility study to convert synthetic Nitrile Butadiene Rubber (NBR) waste into valuable products using batch-type slow pyrolysis will benefit small- to medium-scale industries in their waste handling. The main objective of this research was to find sustainable waste management and energy solutions for synthetic NBR waste using pyrolysis technology. This study employed a two-phase experimental approach where the first five preliminary experiments were conducted to assess the thermal decomposition behavior of NBR waste. In the second phase, three experiments were conducted to quantify the yields of pyrolysis products: pyrolysis oil, solid char, and syngas. The results reveal that the weight distribution of pyrolysis oil, solid char, and syngas was 39.00%, 42.91%, and 18.09%, respectively. Moreover, density, heating value, flash point, and viscosity were analyzed to investigate the quality of the pyrolysis oil, where it was found to be 972.50 kg/m3, 42.50 MJ/kg, 36.50 °C, and 25.44 cP, respectively. Analysis of the syngas composition revealed that carbon monoxide, carbon dioxide, methane, hydrogen, oxygen, and CnHm were 14.14%, 5.04%, 18.69%, 11.08%, 0.02%, and 10.00%, respectively. The heating value of syngas was 3873.70 Kcal/m3. The carbon footprint analysis indicated that a significant reduction is possible in greenhouse gas emissions compared to conventional incineration. Additionally, a cost benefit analysis highlighted the superior cost effectiveness of pyrolysis over incineration of NBR waste. These findings underscore the potential of pyrolysis as an effective tool for sustainable waste management and energy recovery solutions.