bluuebunny/crossref_metadata_2025 huggingface dataset:
Research Progress on Land Use and Analysis of Green Transformation in China Since the New Century
Authors: He Wei , Gong Jianzhou , Zeng Xiaobin
Published: November 2024

The optimization of land use structure is a key measure to promote the allocation of land resources, ensure sustainable land development, and address the human-land conflict. Since the 21st century, land use in China has exhibited spatiotemporal dynamic development characteristics in response to socio-economic growth and changes in regional geographical conditions. The academic community, both domestically and internationally, has enriched and refined the research system on China’s land use, driven by the need to optimize its land use structure. This study systematically reviews relevant land use research literature from 2000 to 2024, utilizing bibliometric analysis and visual mapping to conduct phased evaluations and an overall review. The existing LUCC research framework in China is extensive, with a strong focus on land use issues in the context of rapid development. Building on this review and incorporating practical needs, theoretical innovation, interdisciplinary integration, and expansion across multiple fields, we aim to propose a framework for future land resource research. This framework includes: (i) Establishing a Multi-functional Land Use System: This approach promotes the coordinated development of ecological and social benefits of land use. (ii) Enhancing Effective Assessment and Management of Ecological Risks: Such efforts contribute to optimizing spatial planning and ensuring land security. (iii) Addressing Low Land Use Efficiency: Focusing on this issue will enable more precise management aligned with regional characteristics. (iv) Exploring the Application of Multi-disciplinary and Cross-field Technologies in Land Use Efficiency Assessment: This integration will advance spatial planning research. (v) Expanding Research on Multi-functional Land Use and Multi-element Integration: This direction fosters coordination across various planning frameworks, promoting synergies in land use research.
Analysis of the Impact of Digital Inclusive Finance on the Development of Green Agriculture
Authors: Ma Zhuoya , Liu Zhentao , Zhang Pan , Wei Xue , Chen Wenhui
Published: November 2024

Agricultural green development plays a crucial role in addressing the conflict between agricultural production and ecological environmental protection. This study aims to analyze the impact and mechanisms through which digital inclusive finance influences agricultural green development, providing empirical evidence to support the role of digital inclusive finance in promoting sustainable agricultural practices. Using panel data from 30 provinces (cities and districts) in China spanning from 2011 to 2020, this study measures regional agricultural green development levels using the entropy power method. By clarifying the theoretical mechanisms behind the relationship between digital inclusive finance and agricultural green development, this research employs panel fixed effects, mediation effects, and threshold regression models to empirically examine the impact of digital inclusive finance, specifically its coverage breadth, usage depth, and digitization level, on agricultural green development. Furthermore, this study explores the threshold effects of digital inclusive finance on agricultural green development. The findings from this study indicate that digital inclusive finance significantly contributes to agricultural green development, with a double-threshold effect observed as follows: when digital inclusive finance surpasses critical thresholds, its impact on agricultural green development intensifies. This result remains robust after conducting a series of endogeneity and robustness tests. The mechanism analysis reveals that digital inclusive finance drives agricultural green development by fostering technological innovation and increasing farmers’ income. Heterogeneity analysis further demonstrates that digital inclusive finance has a substantial impact on agricultural green development in eastern China compared to the central and western regions. Consequently, this study suggests that digital inclusive financial services should be further expanded and deepened to foster the integration of financial services with agriculture, creating a sustainable development model that promotes shared prosperity and effectively supports the green development of agriculture.
Long-Term Agricultural Management Alters Soil Fungal Communities and Soil Carbon and Nitrogen Contents in Tea Plantations
Authors: Luo Ying , Zhang Shaobo , Hu Qiang , Huang Fuyin , Bao Demeng , Li Xin , Dong Chunwang , Zhu Shuixing , Fu Jianyu , Yan Peng
Published: November 2024

Soil carbon (C) and nitrogen (N) are vital for enhancing tea production and ensuring the sustainability of tea plantation ecosystems. However, research on the dynamics of soil C and N pools and their associated microbial mechanisms in tea plantations with varying cultivation durations is scarce. We compared soil samples from a forest and two tea plantations—young established (YTP) and century-old (OTP)—to assess changes in soil C and N concentrations and the impact of fungal community structure on these elements. Soil organic carbon (SOC) and total nitrogen (TN) were markedly higher in OTP than in the YTP and forest (65.9% and 30.1%, respectively, relative to YTP). Eurotiomycetes in the YTP group accounted for a relatively higher proportion at 51.6%, surpassing its presence in both the forest (14.3%) and OTP (4.78%) groups and it can be the main microbial factor affecting the C cycle in tea plantation soils and facilitating SOC mineralization. Enhancing planting years or changing land use patterns improves fertilizer and biomass sedimentation and increases the relative abundance of Eurotiomycetes in the soil and the C sink potential of tea plantations. This study provides valuable insights into the role of soil C and N dynamics and fungal communities in tea plantation ecosystems, highlighting the importance of managing these factors for sustainable tea production.
Using Social Network Analysis to Assess ‘Groupness’ in a Mixed-Species Zoo Exhibit of Tufted Capuchins (Sapajus apella) and Squirrel Monkeys (Saimiri sciureus)
Authors: Daoudi-Simison Sophia , Lee Phyllis , Buchanan-Smith Hannah
Published: November 2024

Mixed-species groups have been recorded in various primates, including tufted capuchin and squirrel monkeys. Measures of their ‘groupness’ are typically based on factors such as group stability, social interactions, proximity, or behavioural coordination. Social network analysis has become a useful tool for quantifying relationships among group-living individuals. Here, we apply social network analysis to two captive mixed-species groups of tufted capuchins and squirrel monkeys housed at the Living Links to Human Evolution Research Centre, Royal Zoological Society of Scotland, Edinburgh Zoo, UK. We conducted 183 h of focal observations (three hours per individual, excluding co-observations) and calculated association rates using a simple index ratio. Permutation t-tests were used to assess differences in the overall mixed-species network and network metrics according to species. While the two species exhibited some level of association, they formed separate clusters in the mixed-species networks; however, the East group had more balanced group sizes and showed some signs of closer inter-specific social ties compared to the West group. Our data indicate that, in captivity at least, while these groups co-exist in a small, shared space, they do not form cohesive mixed-species groups. We suggest caution in the assumption of mixed-species groups based on shared space only.
Oral Paraneoplastic Pemphigus: A Scoping Review on Pathogenetic Mechanisms and Histo-Serological Profile
Authors: De Falco Domenico , Messina Sabrina , Petruzzi Massimo
Published: November 2024

Paraneoplastic pemphigus (PNP) is a rare autoimmune disorder associated with underlying neoplasms, predominantly Non-Hodgkin Lymphomas, affecting adults aged 45 to 70. This review analyzed 87 articles from MEDLINE/PubMed, Ovid and Scopus focusing on patients with oral manifestations of PNP, emphasizing histological and serological aspects and discussing recent updates on pathogenetic options. Key findings revealed that PNP is often diagnosed before the neoplasm, with Follicular variant Non-Hodgkin Lymphoma and Castleman Disease being the most common associations. Histopathological analysis showed suprabasal acantholysis and inflammation, and serological tests identify a comprehensive autoantibody panel, underscoring the need for standardized diagnostic criteria and improved serological testing.
Enhanced Effect of Patient Room Disinfection Against Carbapenem-Resistant Enterobacter cloacae and Methicillin-Resistant Staphylococcus aureus Using UV-C Irradiation in Conjunction with UV-C Containment Unit
Authors: Kitaya Shiori , Takei Kentarou , Honda Yoshitomo , Kakuta Risako , Kanamori Hajime
Published: November 2024

Background/Objectives: In environments with high-frequency contact surfaces, drug-resistant bacteria, such as carbapenem-resistant Enterobacterales and methicillin-resistant Staphylococcus aureus (MRSA), can survive for extended periods, contributing to healthcare-associated infections. Ultraviolet (UV)-C irradiation often fails to adequately disinfect shadowed areas, leading to a persistent contamination risk. We evaluated the effectiveness of using a UV-C containment unit (UVCCU) in conjunction with UV-C irradiation to improve the sterilization effects on both direct and indirect surfaces, including shadowed areas, and to assess the leakage of UV radiation to the surroundings. Methods: In a model patient room, agar media inoculated with carbapenem-resistant Enterobacter cloacae and MRSA were placed at multiple locations on direct and indirect surfaces around the bed. We used the UV-C irradiation system, UVDI-360, to irradiate the bedroom-environment surfaces with and without a UVCCU. The reduction in bacterial colony counts with and without the UVCCU was measured by counting colony-forming units and calculating the log reduction values, and the UV radiation leakage outside the UVCCU was measured. Results: The use of the UVCCU led to a significant reduction in MRSA colony counts, even in shadowed areas that had previously been inadequately disinfected (with the UVCCU: 2.7 [2.7–2.8]; without the UVCCU: 0.6 [0.5–0.7]; p < 0.01). Additionally, the use of the UVCCU kept the UV radiation leakage to the surrounding environment within regulated limits. Conclusions: These findings suggest that a UVCCU can enhance the disinfection efficacy for multidrug-resistant organisms on healthcare environmental surfaces. The portability and ease of use of the UVCCU indicate its promise as an auxiliary device for UV-C disinfection in healthcare settings.
Antimicrobial Effectiveness of Ribes nigrum L. Leaf Extracts Prepared in Natural Deep Eutectic Solvents (NaDESs)
Authors: Solcan Maria-Beatrice , Vlase Ana-Maria , Marc Gabriel , Muntean Dana , Casian Tibor , Nadăș George Cosmin , Novac Cristiana Ștefania , Popa Daniela-Saveta , Vlase Laurian
Published: November 2024

Background: Blackcurrant (Ribes nigrum L.) leaves are valuable sources of bioactive compounds, including phenolic acids, flavonoids, and tannins, which contribute to their potent antioxidant, anti-inflammatory, and antimicrobial properties. Objectives: The overall aim of this study was to investigate the antimicrobial potential of extracts rich in bioactive compounds from blackcurrant leaves prepared in natural deep eutectic solvents (NaDESs). The objectives included the optimization of polyphenols extraction in NaDESs, characterization of the phytochemical composition by liquid chromatography–mass spectrometry (LC-MS), explanation of the chemical interactions between solvent systems and the main bioactive compound (chlorogenic acid) by molecular dynamics simulations, and evaluation of biological efficacy through antimicrobial tests. Methods: Two hydrogen-bond acceptors (HBAs) and three hydrogen-bond donors (HBDs) were tested. The experimental design included variables such as the HBA:HBD molar ratio, water percentage, extraction time, and extraction techniques used, specifically ultrasound-assisted extraction (UAE) and ultra-turrax extraction (UTE). The evaluated responses included the total polyphenol content, total flavonoid content, and total antioxidant activity. Antimicrobial assays were performed on four Gram-positive and three Gram-negative bacterial species, as well as one fungus, Candida albicans. Results: The extracts obtained by UAE showed higher concentrations of polyphenols and increased antioxidant potential. LC-MS analysis revealed the predominant presence of chlorogenic acid. The extracts showed significant activities against Gram-positive bacteria and Candida albicans. Conclusions: This study highlights the antioxidant and antimicrobial potentials of blackcurrant leaves extracts prepared in NaDESs, confirming that this type of solvent enhances polyphenols extraction and offers perspectives for new therapeutic formulations.
Healthier Lipid Profiles of Japanese Adults, Especially in Women with Elevated High-Density Lipoprotein Cholesterol (HDL-C), Are Associated with Low HDL-C Peroxide Content
Authors: Berkowitz-Fiebich Loni , Flaherty Shelby M. , Kitayama Shinobu , Karasawa Mayumi , Kawakami Norito , Rigotti Attilio , Coe Christopher L.
Published: November 2024

Japanese adults typically have healthier lipid profiles than American and European adults and a lower prevalence and later onset of atherosclerotic cardiovascular disease (ASCVD). Many Japanese also have uniquely elevated levels of high-density lipoprotein cholesterol (HDL-C). The following analysis examined the relationship between HDL-C level and HDL-C peroxide content, a bioindicator of unhealthy lipid metabolism in Japanese adults. Blood samples were collected from 463 participants, 31–84 years of age, who lived in Tokyo. A second blood sample was collected 5 years later from 241 of the participants, allowing us to evaluate the temporal stability of the inverse correlation between HDL-C level and HDL-C peroxide content. Glucoregulation and inflammatory activity were assessed because both can be associated with dyslipidemia and HDL-C dysfunction. Obesity and central adiposity were also considered. Overall, women had healthier HDL-C profiles than men. Elevated HDL-C (>90 mg/dL) was common (16.6%) and found more often in women. Higher HDL-C peroxide content was associated with older age and central adiposity and incremented further when HA1c and CRP were higher. When assessed 5 years later, lower HDL-C peroxide content continued to be evident in adults with higher HDL-C. While similar associations have been described for other populations, most Japanese adults typically had healthier levels of HDL-C with lower HDL-C peroxide content than previously reported for American adults.
A Comprehensive Study of Reactive Oxygen Species Explicit Dosimetry for Pleural Photodynamic Therapy
Authors: Sun Hongjing , Ong Yihong , Kim Michele M. , Dimofte Andreea , Singhal Sunil , Cengel Keith A. , Yodh Arjun G. , Zhu Timothy C.
Published: November 2024

Photodynamic therapy (PDT) relies on the interactions between light, photosensitizers, and tissue oxygen to produce cytotoxic reactive oxygen species (ROS), primarily singlet oxygen (1O2) through Type II photochemical reactions, along with superoxide anion radicals (O2•−), hydrogen peroxide (H2O2), and hydroxyl radicals (•OH) through Type I mechanisms. Accurate dosimetry, accounting for all three components, is crucial for predicting and optimizing PDT outcomes. Conventional dosimetry tracks only light fluence rate and photosensitizer concentration, neglecting the role of tissue oxygenation. Reactive oxygen species explicit dosimetry (ROSED) quantifies the reacted oxygen species concentration ([ROS]rx) by explicit measurements of light fluence (rate), photosensitizer concentration, and tissue oxygen concentration. Here we determine tissue oxygenation from non-invasive diffuse correlation spectroscopy (DCS) measurement of tumor blood flow using a conversion factor established preclinically. In this study, we have enrolled 24 pleural PDT patients into the study. Of these patients, we are able to obtain data on 20. Explicit dosimetry of light fluence, Photofrin concentration, and tissue oxygenation concentrations were integrated into the ROSED model to calculate [ROS]rx across multiple sites inside the pleural cavity and among different patients. Large inter- and intra-patient heterogeneities in [ROS]rx were observed, despite identical 60 J/cm2 light doses, with mean [ROS]rx,meas of 0.56 ± 0.26 mM for 13 patients with 21 sites, and [ROS]rx,calc1 of 0.48 ± 0.23 mM for 20 patients with 76 sites. This study presented the first comprehensive analysis of clinical ROSED in pleural mesothelioma patients, providing valuable data on future ROSED based pleural PDT that can potentially produce uniform ROS and thus improve the PDT efficacy for Photofrin-mediated pleural PDT.
Treatment with Pterostilbene Ameliorates the Antioxidant Status of Bovine Spermatozoa and Modulates Cell Death Pathways
Authors: Chavas Christos , Sapanidou Vasiliki G. , Feidantsis Konstantinos , Lavrentiadou Sophia N. , Mavrogianni Despoina , Zarogoulidou Ioanna , Fletouris Dimitrios J. , Tsantarliotou Maria P.
Published: November 2024

Reactive Oxygen Species (ROS) play an important role in sperm physiology. They are required in processes such as capacitation and fertilization. However, the exposure of spermatozoa to ROS generated from internal or external sources may create a potentially detrimental redox imbalance. Antioxidant supplementation in semen is now a rather common approach to protect spermatozoa from oxidative stress (OS) during their handling and/or cryopreservation. Supplementation with pterostilbene, a potent antioxidant, protects spermatozoa from OS and ameliorates their post-thawing characteristics and viability. In the present study, we used freezing/thawing as a model of natural ROS overproduction and investigated the molecular mechanisms modulated by pterostilbene. Specifically, bovine frozen/thawed spermatozoa were incubated with 10 or 25 μM pterostilbene for 60 min. Results have shown that in a dose-independent manner, pterostilbene decreased lipid peroxidation and increased intracellular GSH levels. Moreover, pterostilbene ameliorated energy production, as ATP and AMP/ATP levels were restored, and increased autophagy levels through AMP-activated protein kinase (AMPK) activation, which finally resulted in the inhibition of apoptotic cell death in bovine spermatozoa when exposed to OS. This study sheds light on spermatozoa redox state, the crosstalk between apoptotic and autophagic pathways, and its role in determining the beneficial or detrimental effect of ROS in spermatozoa.
Enrichment of Breadsticks with Flavoured Oils: Chemical Composition, Antioxidant Activity and Technological and Sensory Properties
Authors: Sicari Vincenzo , Mincione Antonio , Custureri Irene Maria Grazia , Pino Roberta , Loizzo Monica Rosa
Published: November 2024

The present work compares the physical–chemical, organoleptic and antioxidant characteristics of breadsticks (Bs) prepared in the traditional way (BCs) with extra virgin olive oil (EVOO), and with mace (BMs), ginger (BGs) and turmeric (BTs) flavoured olive oil (FOO). Breadsticks’ water activity (aw), pH, moisture content (U.R.), total phenol (TPC) and total flavonoid (TFC) content, colorimetric analysis and texture and sensory analysis were used to evaluate the impact of the new recipes on consumer acceptance. The radical scavenging activity was also assessed by using 1,1-diphenyl-2-picryl hydrazine (DPPH) and 2,2′-azinobis-3-ethylbenzothiazoline-6-sulfonate (ABTS). The use of FOO influenced breadsticks’ colour with reference to the BG and BT enriched breadsticks, and some variability in free acidity values emerged from the comparison between EVOO and FOO. As expected, peroxide values increased in all enriched breadsticks. Moreover, all flavoured breadsticks were more resistant to lipid oxidation than BCs with an IP value of 92.44, 91.26 and 60.07 h, respectively, for BMs, BGs and BTs. The cooking process of the breadsticks at 180 °C for 25 min did not significantly impact the content of bioactive compounds. BMs showed the highest TPC and TFC with values of 996.32 and 534.41 mg/kg, respectively. Moreover, BMs showed the highest DPPH radical scavenging potential with a value of 393.91 µM TEAC/100 g extract, whereas BGs showed the highest ABTS radical scavenging activity (160.13 µM TEAC/100 g extract). Sensory quantitative descriptive analysis showed the most interesting parameters to be the intensity of toasting for BGs and the intensity of spiciness in BMs. Furthermore, BGs and BTs were found to have a slightly more pungent odour. From the texture assessment, the BC was the crumbliest breadstick, while greater crunchiness was found in the BG and BM samples.
Privacy-Preserving Data Sharing in Telehealth Services
Authors: Odeh Ammar , Abdelfattah Eman , Salameh Walid
Published: November 2024

In today’s healthcare industry, safeguarding patient data is critical due to the increasing digitization of medical records, which makes them vulnerable to cyber threats. Telehealth services, while providing immense benefits in terms of accessibility and efficiency, introduce complex challenges in maintaining data privacy and security. This paper proposes a privacy-preserving framework for secure data sharing within telehealth services, employing blockchain technology and advanced cryptographic techniques. The framework ensures that all patient health data are encrypted using homomorphic encryption before storage on the blockchain, guaranteeing confidentiality and protecting data from unauthorized access. Secure multi-party computation (SMPC) is integrated for encrypted data computations, maintaining data confidentiality even during operations. Smart contracts enforce access control, ensuring that patient preferences and regulatory requirements such as the HIPAA and the GDPR are met. Furthermore, the framework includes auditing and verifying data integrity mechanisms, making it resilient against cyber threats such as impersonation, replay, and Man-In-The-Middle attacks. The analysis demonstrates the framework’s superior performance in addressing these challenges compared to that of existing systems. Future work suggests integrating AI-driven threat detection and quantum-resistant cryptographic techniques to enhance security further and adapt to the evolving telehealth landscape.
Chemical Compounds, Bioactivities, and Applications of Chlorella vulgaris in Food, Feed and Medicine
Authors: Mendes Ana R. , Spínola Maria P. , Lordelo Madalena , Prates José A. M.
Published: November 2024

This review presents the chemical composition, bioactive properties, and diverse applications of Chlorella vulgaris, a green microalga widely recognized for its exceptional nutritional value and therapeutic potential. The study emphasizes the presence of key nutrients, including high-quality proteins, essential vitamins, minerals, and an array of bioactive compounds such as carotenoids, chlorophyll, and polysaccharides. These compounds have been shown to exhibit a wide spectrum of biological activities, including potent antioxidant, anti-inflammatory, immunomodulatory, antiviral, anticancer, antidiabetic, lipid-lowering, and detoxifying effects. The review explores the multifaceted applications of C. vulgaris in various sectors, including its growing role as a functional food ingredient, a nutraceutical supplement in animal feed, and a promising therapeutic agent for combatting chronic diseases. This paper also highlights its potential for enhancing immune responses, mitigating oxidative stress, promoting detoxification of heavy metals, and improving overall health outcomes. However, current limitations in clinical evidence surrounding its medicinal efficacy present challenges that need to be addressed. Furthermore, significant obstacles remain in scaling up C. vulgaris production, including optimizing cultivation techniques and improving bioavailability. Additionally, this review identifies crucial research gaps, particularly in optimizing cultivation techniques, improving bioavailability, and validating the clinical efficacy of C. vulgaris. By addressing these challenges, C. vulgaris holds significant promise in contributing to global health, sustainable nutrition, and environmental conservation efforts by serving as a source of protein and bioactive components for a growing population while simultaneously having a lower environmental impact and requiring fewer resources in production compared to traditional ingredients like soybean meal.
Digital Technology in Cultural Heritage: Construction and Evaluation Methods of AI-Based Ethnic Music Dataset
Authors: Chen Dayang , Sun Na , Lee Jong-Hoon , Zou Changman , Jeon Wang-Su
Published: November 2024

This study focuses on the construction and evaluation of a high-quality Chinese Manchu music dataset designed to facilitate Artificial Intelligence (AI) research and applications within cultural heritage and ethnomusicology. Through a systematic collection and organization of diverse Manchu music resources, including folk songs, dance music, and ceremonial pieces, this dataset effectively represents the cultural breadth of Manchu music. The dataset includes digitized and preprocessed audio data, with comprehensive metadata annotations, such as essential information, musical features, and cultural context, creating a robust foundation for AI-based analysis. Experimental evaluations highlight the dataset’s utility across various AI-driven applications: in music classification, using a CNN model, an accuracy of 90% was achieved in the “folk ensemble” category, with an overall accuracy of 85.7% and a precision of 82.3%. For music generation, a Generative Adversarial Network (GAN) model yielded a quality score of 7.8/10 and a Fréchet Audio Distance (FAD) of 0.32. In emotion recognition, the Random Forest model achieved 87% accuracy in identifying the emotion “joy”. These results underscore the dataset’s potential in supporting digital preservation and expanding AI applications in ethnic music classification, generation, and emotional analysis, contributing to both cultural heritage preservation and AI advancement in ethnomusicology.
Analysis of Delaminated Composite Plates Using 3D Degenerated Plate Element Considering Geometric Non-Linearity
Authors: Tiwari Pratik , Barman Swarup K. , Kong Changduk , Ahn Sungjin , Park Hyunbum
Published: November 2024

This paper presents a numerical investigation of delaminated composite plates using a 3D degenerated plate element, with a focus on geometric nonlinearity. An 8-noded degenerated element is used to model the composite plate, ensuring higher accuracy and computational efficiency. Delamination is modeled using Heaviside step functions, providing a clear representation of discontinuities. The Green–Lagrangian formulation is employed to incorporate geometric nonlinearity and to evaluate its effects on the deflection behavior of delaminated plates under load. The developed model is validated against existing literature, demonstrating its reliability. Subsequently, a comprehensive parametric study is conducted to evaluate the influence of various factors including lamina sequences, boundary conditions, load intensities, and the size and location of the delamination (considered at the center of the laminate). A uniformly distributed pressure load is applied across the entire plate to simulate realistic loading conditions. Additionally, the effects of multiple delaminations through the thickness of the laminate are explored, with key observations on their impact reported. The findings provide valuable insights into the structural performance of delaminated composite plates under nonlinear conditions.
Boosting EEG and ECG Classification with Synthetic Biophysical Data Generated via Generative Adversarial Networks
Authors: Venugopal Archana , Resende Faria Diego
Published: November 2024

This study presents a novel approach using Wasserstein Generative Adversarial Networks with Gradient Penalty (WGAN-GP) to generate synthetic electroencephalography (EEG) and electrocardiogram (ECG) waveforms. The synthetic EEG data represent concentration and relaxation mental states, while the synthetic ECG data correspond to normal and abnormal states. By addressing the challenges of limited biophysical data, including privacy concerns and restricted volunteer availability, our model generates realistic synthetic waveforms learned from real data. Combining real and synthetic datasets improved classification accuracy from 92% to 98.45%, highlighting the benefits of dataset augmentation for machine learning performance. The WGAN-GP model achieved 96.84% classification accuracy for synthetic EEG data representing relaxation states and optimal accuracy for concentration states when classified using a fusion of convolutional neural networks (CNNs). A 50% combination of synthetic and real EEG data yielded the highest accuracy of 98.48%. For EEG signals, the real dataset consisted of 60-s recordings across four channels (TP9, AF7, AF8, and TP10) from four individuals, providing approximately 15,000 data points per subject per state. For ECG signals, the dataset contained 1200 real samples, each comprising 140 data points, representing normal and abnormal states. WGAN-GP outperformed a basic generative adversarial network (GAN) in generating reliable synthetic data. For ECG data, a support vector machine (SVM) classifier achieved an accuracy of 98% with real data and 95.8% with synthetic data. Synthetic ECG data improved the random forest (RF) classifier’s accuracy from 97% with real data alone to 98.40% when combined with synthetic data. Statistical significance was assessed using the Wilcoxon signed-rank test, demonstrating the robustness of the WGAN-GP model. Techniques such as discrete wavelet transform, downsampling, and upsampling were employed to enhance data quality. This method shows significant potential in addressing biophysical data scarcity and advancing applications in assistive technologies, human-robot interaction, and mental health monitoring, among other medical applications.
Adaptive Position Control of Pneumatic Continuum Manipulator Based on MAML Meta-Reinforcement Learning
Authors: Hao Lina , Cheng Qiang , Liu Hongshuai , Zhang Ying
Published: November 2024

Reinforcement learning algorithms usually focus on a specific task, which often performs well only in the training environment. When the task changes, its performance drops significantly, with the algorithm lacking the ability to adapt to new environments and tasks. For the position control of a pneumatic continuum manipulator (PCM), there is a high degree of similarity between tasks, and the training speed of new tasks can be accelerated by utilizing the training experience from other tasks. To increase the adaptability of control policies to new tasks, this paper proposes an adaptive position control algorithm of the PCM based on the Model-Agnostic Meta-Learning (MAML) meta-reinforcement learning algorithm. The MAML meta-reinforcement learning algorithm is used to train the control strategy of PCM, and the information and experience collected during the training process across multiple tasks are used to quickly learn the control policy for new tasks, improving the ability of PCM to quickly adapt to new tasks. The experimental results demonstrate that after training with the MAML meta-reinforcement learning algorithm, the PCM can significantly reduce the training time when faced with new tasks and obtain the control policies suitable for these new tasks.
From Single Shot to Structure: End-to-End Network-Based Deflectometry for Specular Free-Form Surface Reconstruction
Authors: Sepanj M.Hadi , Moradi Saed , Nazemi Amir , Preston Claire , Lee Anthony M. D. , Fieguth Paul
Published: November 2024

Deflectometry is a key component in the precise measurement of specular (mirrored) surfaces; however, traditional methods often lack an end-to-end approach that performs 3D reconstruction in a single shot with high accuracy and generalizes across different free-form surfaces. This paper introduces a novel deep neural network (DNN)-based approach for end-to-end 3D reconstruction of free-form specular surfaces using single-shot deflectometry. Our proposed network, VUDNet, innovatively combines discriminative and generative components to accurately interpret orthogonal fringe patterns and generate high-fidelity 3D surface reconstructions. By leveraging a hybrid architecture integrating a Variational Autoencoder (VAE) and a modified U-Net, VUDNet excels in both depth estimation and detail refinement, achieving superior performance in challenging environments. Extensive data simulation using Blender leading to a dataset which we will make available, ensures robust training and enables the network to generalize across diverse scenarios. Experimental results demonstrate the strong performance of VUDNet, setting a new standard for 3D surface reconstruction.
Evaluating Petrophysical Properties Using Digital Rock Physics Analysis: A CO2 Storage Feasibility Study of Lithuanian Reservoirs
Authors: Malik Shruti , Makauskas Pijus , Sharma Ravi , Pal Mayur
Published: November 2024

As the global concern over greenhouse gas emissions grows, CO2 storage in deep saline aquifers and depleted reservoirs has become crucial for climate change mitigation. This study evaluates the feasibility of Lithuanian deep saline aquifers, specifically, Syderiai and Vaskai, for effective CO2 storage. Unlike previous theoretical analyses, it provides experimental data on static and dynamic reservoir parameters that impact CO2 injection and retention. Using micro X-ray computed tomography (MXCT) and multi-resolution scanning at 8 µm and 22 µm, digital rock volumes (DRVs) from core samples were created to determine porosity and permeability. The method, validated against analogous samples, identified a representative element volume (REV) within sub-volumes, showing a homogeneous distribution of petrophysical properties in the Lithuanian samples. The results show that DRVs can accurately reflect pore-scale properties, achieving 90–95% agreement with lab measurements, and offer a rapid, efficient means for analyzing storage potentials. These insights confirm that Lithuanian aquifers are promising for CO2 sequestration, with recommendations for further long-term monitoring and applications of this technique across the region.
CFD Study of the Impact of an Electrical Power Transformer on a Historical Building: Assessment and Solutions
Authors: Nardecchia Fabio , Gugliermetti Luca , Pompei Laura , Cinquepalmi Federico
Published: November 2024

Historical building reuse is aimed at preservation, where buildings are recovered for new uses connected to cultural activities. This paper presents the analysis of the impact of thermo-fluid dynamics due to a 500 kW electrical power transformer installed inside a historical building. The analysis is performed using computational fluid dynamics simulations validated through measurement campaigns carried out during the summer period. High temperatures and wide humidity variations can damage building plasters and cause malfunctions in power equipment. To avoid these situations, two different installation layouts were studied. One consists of the power transformer directly installed in the environment and cooled by an inlet fan, and the other consists of the power transformer being insulated from the external environment by an enclosure connected to a forced ventilation system. The second layout showed better results both inside and outside the transformer enclosure. The maximum indoor condition was about 4.3 °C, with a −7.2% RH and an airflow rate of 1100 m3/h, and the maximum outdoor air condition was 3.3 °C, with a −1.39% RH and a flow rate of 2200 m3/h. However, the temperatures and humidity inside the building and outside the transformer enclosure were almost the same.
Design and Multi-Objective Optimization of Auxetic Sandwich Panels for Blastworthy Structures Using Machine Learning Method
Authors: Andika  , Santosa Sigit Puji , Widagdo Djarot , Pratomo Arief Nur
Published: November 2024

The design and multi-objective optimization of auxetic sandwich panels (ASPs) are performed to enhance the blastworthiness of armored fighting vehicles (AFVs). Various metastructures in the form of four auxetic geometries are proposed as the sandwich core: re-entrant honeycomb (REH), double-arrow honeycomb (DAH), star honeycomb (SH), and tetra-chiral honeycomb (CH). This paper employs a combination of finite element and machine learning methodologies to evaluate blastworthiness performance. Optimization is carried out using the nondominated sorting genetic algorithm II (NSGA-II) method. The optimization results show significant improvements in blastworthiness performance, with notable reductions in permanent displacement and enhancements in specific energy absorption (SEA). Global sensitivity analysis using SHapley Additive exPlanations (SHAP) reveals that cell thickness is the most critical factor affecting blastworthiness performance, followed by the number of cells and corner angle or radius for CH. The application of optimized ASP on AFVs shows promising results, with no failure occurring in the occupant floor. Furthermore, AFVs equipped with the optimized ASP DAH significantly reduce maximum displacement and acceleration by 39.00% and 43.56%, respectively, and enhance SEA by 48.30% compared to optimized aluminum foam sandwich panels. This study concludes that ASPs have potential applications in broader engineering fields.
Enhanced Wide-Area Glacier Velocity Monitoring in Svalbard via Synthetic Aperture Radar Offset Tracking Noise Suppression
Authors: Yang Honglei , Zhao Songxue , Wang Zeping , Yan Ao , Shi Zhenhan
Published: November 2024

Glacier movement is an important indicator of climate change, reflecting the quality and state changes in glacier migration and mass balance in the context of global warming. Although accurately estimating glacier surface flow velocity is crucial for various applications, achieving this is challenging due to factors such as low temporal correlation and high noise effects. This paper presents the pixel offset tracking (POT) technology based on Synthetic Aperture Radar (SAR) data for glacier velocity monitoring, with enhanced cross-correlation matching window and noise suppression approaches. In particular, a noise suppression optimization method and a matching window optimization index suitable for wide-area glacier velocity monitoring are proposed. The inter-annual wide-area two-dimensional plane flow velocity of glaciers in the Svalbard archipelago was obtained by using a total of seven Sentinel-1 data sets from two orbits covering the entire Svalbard archipelago in 2021. The results indicate that 25 large glaciers in Svalbard destabilized in 2021, with a peak flow velocity of 6.18 m/day. At the same time, the influence of climate, topography, and other factors on glacier surface velocity is discussed. The wide-area glacier velocity monitoring method and its application demonstrated in this paper will serve as a valuable reference for studying glacier migration in the Arctic Svalbard archipelago and for other large-scale wide-area deformation monitoring efforts.
Prediction of Corrosion Rate for Carbon Steel Using Regression Model with Commercial LPR Sensor Data
Authors: Jung Kwang-Hu , Lee Jung-Hyung
Published: November 2024

In this study, a model was proposed to predict the corrosion rate (Mils per Year, MPY) of carbon steel in a 3.5% NaCl solution, with the objective of comparing the effectiveness of a commercial LPR sensor against traditional electrochemical methods, using potentiostat-based LPR techniques. The primary factors considered in the experiments were temperature, flow velocity, and pH, tested through a full factorial design to identify the most influential variables. Statistical analysis showed that temperature and flow velocity had a significant effect on corrosion rate, with their interaction having the most substantial impact. In contrast, pH had no statistically significant influence within the tested conditions, likely due to the dominant effects of temperature and flow velocity in the high-salinity environment. The MPY data were validated through Tafel plots, immersion coupon tests, and other electrochemical techniques to confirm the reliability of the measurements. A regression model trained on 54 MPY data points demonstrated high accuracy, achieving a coefficient of determination (R2) of 0.9733. The model also provided reliable predictions for factor combinations excluded from the training dataset. Additionally, scenario-based evaluations highlighted the model’s performance under simulated operating conditions, while revealing challenges related to sensor contamination during long-term use. These findings emphasize the potential of commercial LPR sensors as effective tools for real-time corrosion monitoring and demonstrate the utility of the regression model in marine environments.
NMR Analysis of Pulegone in Food Products
Authors: Yu Yifei , Kuballa Thomas , Lachenmeier Dirk W.
Published: November 2024

Pulegone is a monoterpene ketone found in a variety of mint species. It has been classified as possibly carcinogenic to humans (Group 2B) by the International Agency for Research on Cancer (IARC). In previous studies, pulegone in food was analyzed exclusively via GC-MS, while 1H NMR methods were limited to essential oils. The aim of this study was to develop an NMR method for the detection and quantification of pulegone in essential oils and foods. A mixture of methanol-d4/chloroform-d1 in a 1:1 ratio (v/v) was identified as the most effective solvent for separating pulegone signals. The essential oils were subjected to analysis at this solvent-mixture ratio. The extraction of pulegone was required for food analysis, and the steam distillation method proved to be more effective than the ultrasonic-assisted extraction method. The highest pulegone concentrations were identified in pennyroyal oil and muña oil, whereas lower levels were observed in other matrices, including corn mint oil and select food items. A toxicological assessment showed that the amount consumed did not exert any adverse effects on human health.
Computational Fluid Dynamics Analysis of Gas Suction in Coaxial Flow Venturi Injector: Impact of Gas–Liquid Interface Structure in Mixing Section
Authors: Zu Yihan , Zhong Wenchen , Xu Enle , Miao Zhenyong
Published: November 2024

The gas–liquid Venturi injector has been widely applied in industrial production due to its advantages of high entrainment and low energy consumption. In this study, Computational Fluid Dynamics (CFD) was employed to investigate the effect of the gas–liquid interface structure within the mixing section on entrainment behavior by varying the geometry of the mixing section during gas–liquid coaxial flow. The simulation results indicate that along the jet direction, the gas–liquid interface generally transitions from a smooth cylindrical shape to a lobed structure in the mixing section. Surface waves mainly appear in the lobed region. Furthermore, lobed and surface wave structures reduce pressure loss and enhance entrainment. Additionally, the study found that longer mixing sections enhance entrainment under low flow resistance. This study provides valuable insights for achieving high jet entrainment and offers supplementary research on gas–liquid interface structures in jets constrained by solid boundaries.
Application of Active Soil Gas Screening for the Identification of Groundwater Contamination with Chlorinated Hydrocarbons at an Industrial Area—A Case Study of the Former Refrigerator Manufacturer Calex (City of Zlaté Moravce, Western Slovakia)
Authors: Tóth Roman , Hiller Edgar , Špirová Veronika , Jurkovič Ľubomír , Ševčíková Ľubica , Macek Juraj , Čičáková Claudia , Kovács Tibor , Auxt Anton
Published: November 2024

Background: Groundwater contamination with chlorinated hydrocarbons (CLHCs), particularly with tetrachloroethylene (PCE) and trichloroethylene (TCE), which are used in industry for degreasing and cleaning, can be considered a serious problem concerning the entire world. In addition to conventional groundwater monitoring from a network of wells, several screening methods have been proposed to identify and delineate groundwater contamination with volatile organic compounds (VOCs), such as soil gas measurement, bioindicators, direct-push technologies or geophysical techniques. The main objectives of this study were to confirm the feasibility of active soil gas screening for the characterisation of groundwater contamination with CLHCs under the wider area of the former refrigerator manufacturer (city of Zlaté Moravce, western Slovakia) and to evaluate the human health risks through exposure to CLHCs present in groundwater. Methods: a conventional site investigation based on concentration measurements using gas chromatography-mass spectrometry from monitoring wells and soil gas measurements using a portable photo-ionisation detector device were applied. Results: The chemical analyses showed the persistent contamination of groundwater, with PCE, TCE and other CLHCs, such as cis-1,2-dichloroethylene (cis-DCE) or 1,1,2-trichloroethane (TCA), being most severe in the zone of the former factory (up to 2690, 83,900, 6020 and 156 µg/L for PCE, TCE, cis-DCE and TCA, respectively), but also extended into the residential zone located 600 m along the groundwater flow line. Soil gas measurements of VOCs and other chemical parameters (methane (CH4), total petroleum (TP), carbon dioxide (CO2) and oxygen (O2)) from a densely designed network of sampling points (n = 300) helped trace the current state of groundwater contamination. Spatial distribution maps of VOCs concentrations in soil gas clearly marked the areas of the highest CLHCs concentrations in groundwater. Principal component analysis (PCA) confirmed a significant correlation of VOCs and CLHCs with the first principal component, PC1, explaining up to 84% of the total variability of the concentration data, suggesting that VOCs in soil gas were a suitable marker of the extent of groundwater contamination with CLHCs. Despite severe groundwater contamination with CLHCs reaching residential areas, local residents were not exposed to non-carcinogenic risks, but a potential carcinogenic risk was present. Conclusions: based on the results, it could be confirmed that soil gas screening is an efficient and quick tool for identifying the sources of groundwater contamination with CLHCs as well as the level of this contamination.
Determination of Polycyclic Aromatic Hydrocarbons from Atmospheric Deposition in Malva sylvestris Leaves Using Gas Chromatography with Mass Spectrometry (GC-MS)
Authors: Ianiri Giuseppe , Fratianni Alessandra , Avino Pasquale , Panfili Gianfranco
Published: November 2024

Plant leaves can be used to determine the atmospheric deposition of organic contaminants, including polycyclic aromatic hydrocarbons (PAHs), to assess the contamination status of an area. The purpose of this study was to develop an analytical method for the determination of PAHs deriving from atmospheric deposition using Malva sylvestris leaves. Analytes were recovered from the leaves of the plant using cyclohexane as an organic solvent and subsequent sonication. The percentage recoveries (R%) were good (from 65.8 ± 3.2 to 104.2 ± 16.9), together with the instrumental analytical parameters, including correlation coefficients (r) ≥ 0.995 for all PAHs. The instrumental analysis was carried out using GC-MS in total ion current and single ion monitoring at the same time. Real samples taken from urban environments have shown that they are not always the most contaminated. At the Palermo site, leaves were observed to have high amounts of PAHs due to the deposition of dust generated by combustion processes that occurred near the sampling site. Further studies are recommended to compare the use of plants and classical sampling systems for monitoring the atmospheric deposition of key contaminants toxic to human health.