bluuebunny/crossref_metadata_2025 huggingface dataset:
Network Pharmacology Approach and Experimental Verification to Explore the Anti-NSCLC Mechanism of Grifolic Acid
Authors: Cuan Xiangdan , Wang Jinxian , Zhao Yue , Yan Jingyun , Sheng Jun , Huang Yanping
Published: January 2025

Lung cancer is the leading cause of cancer-related death. Non–small cell lung cancer (NSCLC) accounts for 85% of all lung cancers and over 60% express wild-type EGFR (WT-EGFR); however, EGFR tyrosine kinase inhibitors (TKIs) have limited effect in most patients with WT-EGFR tumors. In this study, we applied network pharmacology screening and MTT screening of bioactive compounds to obtain one novel grifolic acid that may inhibit NSCLC through the EGFR-ERK1/2 pathway. Through the PPI network and machine learning, we identified two hub genes, EGFR and AKT1, as potential therapeutic targets. Molecular docking confirmed that the grifolic acid could effectively bind to the key target, EGFR. Using the NSCLC cell line NCI-H1781 as an in vitro model, we evaluated the effect of the drugs’ combination on viability, apoptosis, and clonogenicity capacity. In vitro studies showed that combined treatment decreased cell viability, increased activation PARP, and caused cell cycle redistribution and significantly greater inhibition of pEGFR and pAKT. This study not only provides new insights into the mechanism of grifolic acid against NSCLC but also important information and new research ideas for the discovery of anti-NSCLC compounds from natural products.
The Bogomolny–Carioli Twisted Transfer Operators and the Bogomolny–Gauss Mapping Class Group
Authors: Lecian Orchidea Maria
Published: January 2025

The twisted reflection operators are defined on the hyperbolic plane. They are then specialized in hyperbolic reflections, according to which the desymmetrized PSL (2,Z) group is rewritten. The Bogomolny–Carioli transfer operators are newly analytically expressed in terms of the Dehn twists. The Bogomolny–Gauss mapping class group of the desymmetrized PSL (2,Z) domain is newly proven. The paradigm to apply the Hecke theory on the CAT spaces on which the Dehn twists act is newly established. The Bogomolny–Gauss map is proven to be one of infinite topological entropy.
Perioperative Risk: Short Review of Current Approach in Non Cardiac Surgery
Authors: Boghean Andreea , Guțu Cristian , Firescu Dorel
Published: January 2025

The rate of major surgery is constantly increasing worldwide, and approximately 85% are non-cardiac surgery. More than half of patients over 45 years presenting for non-cardiac surgical interventions have cardiovascular risk factors, and the most common: chronic coronary syndrome and history of stroke. The preoperative cardiovascular risk is determined by the comorbidities, the clinical condition before the intervention, the urgency, duration or type. Cardiovascular risk scores are necessary tools to prevent perioperative cardiovascular morbidity and mortality and the most frequently used are Lee/RCRI (Revised Cardiac Risk Index), APACHE II (Acute Physiology and Chronic Health Evaluation), POSSUM (Physiological and Operative Severity Score for the enumeration of Mortality and Morbidity), The American University of Beirut (AUB)-HAS2. To reduce the perioperative risk, there is a need for an appropriate preoperative risk assessment, as well as the choice of the type and timing of surgical intervention. Quantification of surgical risk as low, intermediate, and high is useful in identifying the group of patients who are at risk of complications such as myocardial infarction, thrombosis, arrhythmias, heart failure, stroke or even death. Currently there are not enough studies that can differentiate the risk according to gender, race, elective versus emergency procedure, the value of cardiac biomarkers.
The Intra-Examiner Variability in and Accuracy of Traditional Manual Diagnostics of Benign Paroxysmal Positional Vertigo: A Prospective Observational Cohort Study
Authors: Hentze Malene , Hougaard Dan Dupont , Kingma Herman
Published: January 2025

Background/Objectives: Accurate head positioning is essential for diagnostics of benign paroxysmal positional vertigo (BPPV). This study aimed to quantify the head angles and angular velocities during traditional manual BPPV diagnostics in patients with positional vertigo. Methods: A prospective, observational cohort study was conducted at a tertiary university hospital outpatient clinic. One trained examiner performed the Supine Roll Test (SRT) and the Dix–Hallpike test (DHT) on 198 adults with positional vertigo. The primary outcomes included head angle variability and accuracy and angular velocity variability. The secondary outcomes examined the relationship between the head angle accuracy and participant-reported limitations. Results: The absolute variability for all head angles ranged from ±8.7° to ±11.0°. The yaw axis head angles during the DHT, particularly on the left side, had the highest relative variability (left DHT: coefficient of variance 0.29). Systematic errors included the yaw axis head angles undershooting the target (90°) by 19.7–23.8° during the SRT and the pitch axis head angles undershooting the target (120°) by 7.8–8.7° during the DHT. The left-sided yaw axis in the DHT was undershot by 11.8°, while the right-sided DHT angle was slightly overshot (2.5°). Right-sided yaw axis angles in the SRT and DHT were more accurate than the left-sided ones (right SRT: 19.9°; left SRT: 23.9°; p < 0.0001) (right DHT: 7.0°; left DHT: 13.2°; p < 0.0001). The regression analysis found no association between the participant-reported limitations and head angle accuracy. Conclusions: This study highlights the substantial variability and inaccuracies in head positioning during traditional manual BPPV diagnostics, supporting the relevance of a guidance system to improve BPPV diagnostics. Level of evidence: III. Trial registration: ClinicalTrials.gov identifier: NCT05846711.
Muscle Strength Loss in Women with COVID-19 and the Restorative Role of Physiotherapy
Authors: Baykan Çopuroğlu Özge , Çopuroğlu Mehmet
Published: January 2025

Objective: This study aimed to evaluate the effects of an 8-week physiotherapy program on muscle strength, functional capacity, respiratory function, and quality of life in women recovering from COVID-19. Methods: A prospective cohort study was conducted with 42 women aged 18–65 who experienced muscle strength loss and functional impairments post-COVID-19. Participants underwent personalized physiotherapy interventions, including resistance training, respiratory therapy, and functional mobility exercises, for 8 weeks. Data were collected at baseline and post-intervention, including handgrip strength, 6-Minute Walk Test (6MWT), forced vital capacity (FVC), Fatigue Severity Scale (FSS), and SF-36 scores. Statistical analyses were performed using paired t-tests and Wilcoxon signed-rank tests. Results: Significant improvements were observed in muscle strength, with right-handgrip strength increasing from 18.5 ± 4.2 kg to 22.8 ± 4.6 kg (p < 0.001) and left-handgrip strength from 17.2 ± 4.1 kg to 21.1 ± 4.5 kg (p < 0.001). Functional capacity improved, as evidenced by a 6MWT distance increase from 382 ± 62 m to 438 ± 57 m (p < 0.001). Respiratory function parameters, including FVC and FEV1, also showed significant gains (p < 0.01). Quality of life scores improved significantly, particularly in physical functioning and vitality domains, while fatigue levels decreased markedly (p < 0.001). Conclusions: The results demonstrate the effectiveness of physiotherapy in addressing the physical and functional consequences of COVID-19 in women. These findings emphasize the importance of incorporating physiotherapy into post-COVID-19 rehabilitation protocols to enhance recovery and quality of life.
Stress and Displacement Dynamics in Surgically Assisted Rapid Maxillary Expansion: A Comprehensive Finite Element Analysis of Various Osteotomy Techniques
Authors: Gürsu Müjde , Şimşek Mehmet Barış
Published: January 2025

Objectives: This study aimed to compare the effects of surgically assisted rapid palatal expansion (SARPE) techniques and their combinations on the stresses (von Mises, maximum principal, and minimum principal) and displacements that occur in the maxilla, facial bones, and maxillary teeth using three-dimensional finite element analysis (FEA). Methods: SARPE was simulated using seven different osteotomy techniques. The FEA models were simulated with a combination of various osteotomies, including midpalatal and lateral osteotomies, lateral osteotomy with a step, and separation of the pterygomaxillary junction. For each osteotomy variant, the instantaneous displacements and stresses resulting from forces applied by a 1 mm expansion of a tooth-borne appliance were evaluated. Results: Midpalatal osteotomy increased lateral displacement in the alveolar bone margins and intermaxillary suture while significantly reducing stresses around the intermaxillary suture. The addition of a pterygomaxillary osteotomy to the midpalatal and lateral osteotomies effectively reduced stresses in the posterior maxilla and cranial structures while enhancing lateral displacement. Although lateral osteotomy significantly reduced stresses in the midface, its effect on maxillary expansion was limited. Stepped lateral osteotomy had minimal effects on transverse displacement and stress reduction. Conclusions: Increasing the number of osteotomies reduced stress levels in the maxilla while enhancing lateral displacement. These results highlight the importance of selecting the most appropriate osteotomy technique to achieve optimal outcomes.
Fusion MRI/Ultrasound-Guided Transperineal Biopsy: A Game Changer in Prostate Cancer Diagnosis
Authors: Giannakodimos Ilias , Kaltsas Aris , Moulavasilis Napoleon , Kratiras Zisis , Mitropoulos Dionysios , Chrisofos Michael , Stravodimos Konstantinos , Fragkiadis Evangelos
Published: January 2025

Background/Objectives: Multiparametric-Magnetic Resonance Imaging(mp-MRI) presents the ability to detect clinically significant cancer, aiming to avoid biopsy if the results are negative or target an abnormal lesion if a suspected lesion of the prostate is found. Recent guidelines recommend the performance of 12 standard biopsies along with 3 to 5 targeted biopsies in suspected prostate lesions, depending on the size of the prostate lesion. In addition, prostate biopsy can be performed by either the transperineal or the transrectal approach. The aim of this comprehensive review is to highlight the role of both standard and targeted MRI/Ultrasound (US) fusion transperineal biopsy (TPB) in the diagnostic approach of prostate cancer cases, to report its diagnostic efficacy and complication rates and to suggest the promising usage of MRI/US fusion TPB in the future. Methods: A comprehensive review of the existing literature, including systematic reviews, meta-analyses, and clinical guidelines, was conducted to compare the efficacy and safety of transperineal and transrectal approaches in prostate cancer detection. Special emphasis was placed on mp-MRI-guided targeted biopsy and its combination with systematic sampling. Results: Prostate biopsy via the transperineal approach is related to increased detection rates, especially for anterior lesions, and decreased infection risk compared to the transrectal approach, while complication rates (hematuria, hemospermia, etc.) remain similar. Due to lower infection rates via the transperineal route, the performance of prostate biopsy using the transperineal approach is strongly recommended. Finally, transperineal fusion MRI/US biopsy can be valuable for repeat biopsies in patients who had an initial negative biopsy or for the follow-up of patients that undergo active surveillance. Conclusions: MRI/US fusion-guided TPB represents a significant advancement in prostate cancer diagnostics, combining improved precision with reduced infection risks. Although TPB presents higher detection rates for anterior prostatic lesions and lower post-biopsy infection rates, there is no significant difference in cancer detection rates compared to TRB. Targeted training and investment may reduce long-term expenses of TPB by lowering hospitalizations, antibiotic usage, and related costs. Future research should further refine this approach and explore its integration with emerging technologies like artificial intelligence for enhanced lesion targeting and diagnostic accuracy.
How Reproducible Are the Ultrasound Features of Adenomyosis Defined by the Revised MUSA Consensus?
Authors: Kadam Nikit , Khalid Somia , Jayaprakasan Kanna
Published: January 2025

Background/Objectives: The aim of this study is to assess the inter- and intra-observer reproducibility of the identification of direct and indirect ultrasonographic features of adenomyosis as defined by the revised Morphological Uterus Sonographic Assessment (MUSA) consensus (2022). Methods: A cohort of 74 women, aged 18 to 45, were recruited from the recurrent miscarriage and general gynaecology clinic at a university-based fertility centre. All the participants underwent 2D and 3D transvaginal Ultrasound scan (TVS) examination in the late follicular and early luteal phase. Conventional grey scale and power Doppler image volumes were acquired and stored. Subsequently, the stored 3D ultrasound images were independently re-evaluated offline by the two observers for the direct and indirect features of adenomyosis as outlined by the revised MUSA group. The intra- and the inter-observer reproducibility was estimated using Cohen’s Kappa coefficient. Results: The intra- and interobserver reproducibility (K −0.27, 95% CI 0.06–0.48 and K 0.13, 95% CI −0.10–0.37, respectively) for at least one direct feature of adenomyosis was only modest. Amongst the individual direct features, the interobserver variability of identifying myometrial cysts was fair (K 0.21, 95% CI −0.00–0.42), whereas the intra-observer variability was moderate (K 0.44, 95% CI 0.26–0.63). While hyperechogenic islands identification achieved a fair level of intra- (K 0.31, 95% CI 0.09–0.53) and interobserver (K 0.24, 95% CI 0.01–0.47) agreement, the reproducibility of reporting sub-endometrial lines/buds was fair for the intra-observer (K 0.22, 95% CI −0.02 0.47) and poor for the interobserver (K 0.00, 95% CI −0.20–0.19). The interobserver agreement for indirect features varied from poor to moderate, while the intra-observer agreement ranged between poor to good. Conclusions: The reporting of adenomyosis using direct features suggested by the revised MUSA group consensus showed only modest interobserver and intra-observer agreement. The definitions of ultrasound features for adenomyosis need further refining to enhance the reliability of diagnosis criteria of adenomyosis.
Strategies for Early Keratoconus Diagnosis: A Narrative Review of Evaluating Affordable and Effective Detection Techniques
Authors: Gideon Abou Said Arige , Gispets Joan , Shneor Einat
Published: January 2025

Keratoconus is a progressive corneal disorder that can lead to irreversible visual impairment if not detected early. Despite its high prevalence, early diagnosis is often delayed, especially in low-to-middle-income countries due to limited awareness and restricted access to advanced diagnostic tools such as corneal topography, tomography, optical coherence tomography, and corneal biomechanical assessments. These technologies are essential for identifying early-stage keratoconus, yet their high cost limits accessibility in resource-limited settings. While cost and portability are important for accessibility, the sensitivity and specificity of diagnostic tools must be considered as primary metrics to ensure accurate and effective detection of early keratoconus. This review examines both traditional and advanced diagnostic techniques, including the use of machine learning and artificial intelligence, to enhance early diagnosis. Artificial intelligence-based approaches show significant potential for transforming keratoconus diagnosis by improving the accuracy and sensitivity of early diagnosis, especially when combined with imaging devices. Notable innovations include tools such as SmartKC, a smartphone-based machine-learning application, mobile corneal topography through the null-screen test, and the Smartphone-based Keratograph, providing affordable and portable solutions. Additionally, contrast sensitivity testing demonstrates potential for keratoconus detection, although a precise platform for routine clinical use has yet to be established. The review emphasizes the need for increased awareness among clinicians, particularly in underserved regions, and advocates for the development of accessible, low-cost diagnostic tools. Further research is needed to validate the effectiveness of these emerging technologies in detecting early keratoconus.
Artificial Intelligence in Imaging for Personalized Management of Coronary Artery Disease
Authors: Bednarek Adrian , Gumiężna Karolina , Baruś Piotr , Kochman Janusz , Tomaniak Mariusz
Published: January 2025

The precision of imaging and the number of other risk-assessing and diagnostic methods are constantly growing, allowing for the uptake of additional strategies for individualized therapies. Personalized medicine has the potential to deliver more adequate treatment, resulting in better clinical outcomes, based on each patient’s vulnerability or genetic makeup. In addition to increased efficiency, costs related to this type of procedure can be significantly lower. Useful assistance in designing individual therapies may be assured by the adoption of artificial intelligence (AI). Recent years have brought essential developments in deep and machine learning techniques. Advances in technologies such as convolutional neural networks (CNNs) have enabled automatic analyses of images, numerical data, and video data, providing high efficiency in the creation of prediction models. The number of AI applications in medicine is constantly growing, and the effectiveness of these techniques has been demonstrated in coronary computed tomography angiography (CCTA), optical coherence tomography (OCT), and many others. Moreover, AI models may be useful in direct therapy optimization for patients with coronary artery disease (CAD), who are burdened with high risk. The combination of well-trained AI with the design of individual treatment pathways can lead to improvements in health care. However, existing limitations, such as non-adapted guidelines or the lack of randomized clinical trials to evaluate AI’s true accuracy, may contribute to delays in introducing automatic methods into practical use. This review critically appraises the developed tools that are potentially useful for clinicians in guiding personalized patient management, as well as current trials in this field.
Spectral Bidirectional Reflectance Distribution Function Simplification
Authors: Chitnis Shubham , Sole Aditya , Chandran Sharat
Published: January 2025

Non-diffuse materials (e.g., metallic inks, varnishes, and paints) are widely used in real-world applications. Accurate spectral rendering relies on the bidirectional reflectance distribution function (BRDF). Current methods of capturing the BRDFs have proven to be onerous in accomplishing quick turnaround time, from conception and design to production. We propose a multi-layer perceptron for compact spectral material representations, with 31 wavelengths for four real-world packaging materials. Our neural-based scenario reduces measurement requirements while maintaining significant saliency. Unlike tristimulus BRDF acquisition, this spectral approach has not, to our knowledge, been previously explored with neural networks. We demonstrate compelling results for diffuse, glossy, and goniochromatic materials.
Maritime Autonomous Surface Ships: Architecture for Autonomous Navigation Systems
Authors: Alamoush Anas S. , Ölçer Aykut I.
Published: January 2025

The development of Maritime Autonomous Surface Ships (MASS) has seen significant advancements in recent years, yet there remains a lack of comprehensive studies that holistically address the architecture of autonomous navigation systems and explain the complexity of their individual elements. This paper aims to bridge this gap by conducting a literature review that consolidates key research in the field and presents a detailed architecture of autonomous navigation systems. The results of this study identify several major clusters essential to MASS navigation architecture, including (1) autonomous navigation architecture, (2) decision-making and action-taking system, (3) situational awareness and associated technologies, (4) sensor fusion technology, (5) collision avoidance subsystems, (6) motion control and path following, and (7) mooring and unmooring. Each cluster is further dissected into sub-clusters, highlighting the intricate and interdependent nature of the components that facilitate autonomous navigation. The implications of this study are vital for multiple stakeholders. Ship captains and seafarers must be prepared for new navigation technologies, while managers and practitioners can use this architecture to better understand and implement these systems. Researchers will find a foundation for future investigations, particularly in filling knowledge gaps related to autonomous ship operations. This study makes a substantial contribution by filling a critical gap in the maritime literature, offering a detailed explanation of the elements within autonomous navigation systems.
A Physics-Based Simulation of Fluid–Solid Coupling Scenarios in an Ocean Visual System
Authors: Wang Yiding , Ren Hongxiang , Yang Xiao , Wang Delong
Published: January 2025

In the domain of ocean engineering, the authenticity of visual systems is a major challenge in developing marine simulators. A simulation strategy based on the smoothed particle hydrodynamics (SPH) simulation method is proposed in this study to enhance the realism of fluid–solid coupling scenes in a marine simulator visual system. Based on the SPH method, the water particles are constrained in each iteration according to the two physical fields of velocity divergence and density by setting an intermediate velocity. In the simulation of the fluid–structure interaction scenario, the contribution of the volume of the rigid model to the water particles is represented by a spatial map and then incorporated into the calculation of the pressure from the water particles according to the positional relationship between the water particles and the boundary. This strategy can effectively ensure the realism of the interaction between the rigid body and the waves on the one hand and significantly improve the speed of the marine simulator visual system on the other. The experiments show that this strategy can effectively save a significant amount of time and provide theoretical and technical references for enhancing the realism of a marine simulator visual system.
Enhancing Underwater Video from Consecutive Frames While Preserving Temporal Consistency
Authors: Hu Kai , Meng Yuancheng , Liao Zichen , Tang Lei , Ye Xiaoling
Published: January 2025

Current methods for underwater image enhancement primarily focus on single-frame processing. While these approaches achieve impressive results for static images, they often fail to maintain temporal coherence across frames in underwater videos, which leads to temporal artifacts and frame flickering. Furthermore, existing enhancement methods struggle to accurately capture features in underwater scenes. This makes it difficult to handle challenges such as uneven lighting and edge blurring in complex underwater environments. To address these issues, this paper presents a dual-branch underwater video enhancement network. The network synthesizes short-range video sequences by learning and inferring optical flow from individual frames. It effectively enhances temporal consistency across video frames through predicted optical flow information, thereby mitigating temporal instability within frame sequences. In addition, to address the limitations of traditional U-Net models in handling complex multiscale feature fusion, this study proposes a novel underwater feature fusion module. By applying both max pooling and average pooling, this module separately extracts local and global features. It utilizes an attention mechanism to adaptively adjust the weights of different regions in the feature map, thereby effectively enhancing key regions within underwater video frames. Experimental results indicate that when compared with the existing underwater image enhancement baseline method and the consistency enhancement baseline method, the proposed model improves the consistency index by 30% and shows a marginal decrease of only 0.6% in enhancement quality index, demonstrating its superiority in underwater video enhancement tasks.
Evaluating the Progress of the EU Countries Towards Implementation of the European Green Deal: A Multiple Criteria Approach
Authors: Ottomano Palmisano Giovanni , Rocchi Lucia , Negri Lorenzo , Piscitelli Lea
Published: January 2025

The European Green Deal (EGD) is a package of policy initiatives launched by the European Commission in December 2019, which aims to set the European Union (EU) on the path to a green transition with the final goal of achieving climate neutrality by 2050. The package includes interlinked initiatives covering the climate, the environment, energy, transport, industry, agriculture, and sustainable finance. It is thus evident that holistic and scientifically sound decision support systems are crucial to help EU policymakers and stakeholders in monitoring the progress of countries towards the implementation of the EGD. Indeed, the multidimensionality of this policy initiative lends itself well to its integration into a Multiple Criteria Decision Aiding (MCDA) approach to the identification of priorities for action. Therefore, this research aims to evaluate the progress of the EU countries towards the implementation of the European Green Deal, using MCDA. The PROMETHEE II method was applied to the data for EU countries, using 26 key indicators collected from the Eurostat database and organized into three thematic clusters. The results enabled us to calculate overall scores measuring the degree of implementation of the EGD by the EU countries, and their profiles with respect to the key indicators and thematic clusters. By analyzing these profiles, strengths and weaknesses were identified. Thus, the fundamental novelty of this research consists of the first concrete application of a holistic and ‘ready-to-use’ decision-making tool that can be adopted by EU policymakers and stakeholders to draw up a roadmap towards climate neutrality.
Exploring Bare Ownership Supply of Housing in Urban Environments
Authors: Guarini Maria Rosaria , Segura-de-la-Cal Alejandro , Sica Francesco , Núñez-Guerrero Yilsy
Published: January 2025

Europe faces a situation where housing represents the main savings for most of the population, while the majority of homeowners are seniors aged over 65. The desire to supplement pensions has led to a growing interest in generating income from these savings, with bare ownership emerging as a notable option. This solution makes it possible to transfer the ownership of the home while maintaining usufruct rights for the duration of the owner’s lifetime. This paper examines the status of bare ownership in the city of Rome by web scraping the house offers published on web portals and segmenting those offered as bare ownership. Machine learning analysis based on neural networks and binary logit regression allows for the observation of the particular behavior of the housing supply in bare ownership; it shows the different intrinsic and extrinsic characteristics that determine this Real Estate segment. The findings highlight the development of a growing market strongly influenced by the location of assets. These findings provide valuable insights for both investors and urban planners regarding changes in urban dynamics processes.
Preparation and Tribological Performance of the Ag/BN Nanocomposite as Additives for Lithium-Based Grease
Authors: Chen Yijun , Li Chuan , Wang Xiaodong , Zhang Li , Tan Xu , Peng Yubin , Xu Xiaoyong
Published: January 2025

This study synthesized a nanocomposite composed of silver nanoparticles and boron nitride (Ag/BN nanocomposite) by depositing Ag nanoparticles on BN surfaces. The chemical composition, structure, micromorphology, and tribological properties of the Ag/BN nanocomposite were investigated using transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), Raman spectroscopy, and a high-speed reciprocating tribometer. Under a 10 N load, 30 min test duration, 50 mm/s sliding speed, and 2 wt% additive concentration, lithium-based grease (LBG) containing Ag/BN nanocomposite exhibited the lowest average friction coefficient of 0.33 and a wear rate of 1.08 × 10−14 m3/(N × m), representing reductions of 35.2% and 41.6%, respectively, compared to pure LBG. A further analysis of the friction mechanism was conducted using 3D laser scanning microscopy, scanning electron microscopy (SEM), and XPS. The results indicate that the Ag/BN nanocomposite effectively reduced friction and wear on the friction pair surfaces through repair mechanisms, the formation of lubricating films, and micro-bearing effects.
Quantifying Interdisciplinarity in Scientific Articles Using Deep Learning Toward a TRIZ-Based Framework for Cross-Disciplinary Innovation
Authors: Douard Nicolas , Samet Ahmed , Giakos George , Cavallucci Denis
Published: January 2025

Interdisciplinary research (IDR) is essential for addressing complex global challenges that surpass the capabilities of any single discipline. However, measuring interdisciplinarity remains challenging due to conceptual ambiguities and inconsistent methodologies. To overcome these challenges, we propose a deep learning approach that quantifies interdisciplinarity in scientific articles through semantic analysis of titles and abstracts. Utilizing the Semantic Scholar Open Research Corpus (S2ORC), we leveraged metadata field tags to categorize papers as either interdisciplinary or monodisciplinary, establishing the foundation for supervised learning in our model. Specifically, we preprocessed the textual data and employed a Text Convolutional Neural Network (Text CNN) architecture to identify semantic patterns indicative of interdisciplinarity. Our model achieved an F1 score of 0.82, surpassing baseline machine learning models. By directly analyzing semantic content and incorporating metadata for training, our method addresses the limitations of previous approaches that rely solely on bibliometric features such as citations and co-authorship. Furthermore, our large-scale analysis of 136 million abstracts revealed that approximately 25% of the literature within the specified disciplines is interdisciplinary. Additionally, we outline how our quantification method can be integrated into a TRIZ-based (Theory of Inventive Problem Solving) methodological framework for cross-disciplinary innovation, providing a foundation for systematic knowledge transfer and inventive problem solving across domains. Overall, this approach not only offers a scalable measurement of interdisciplinarity but also contributes to a framework for facilitating innovation through structured cross-domain knowledge integration.
Live-Streaming Adoption Strategies in Downstream-Dominant Supply Chain
Authors: Jin Delong
Published: January 2025

In recent years, live streaming has become popular among merchants as it helps them obtain direct access to and attract customers. This study examines how weak upstream providers and strong downstream sellers adopt live streaming in a supply chain framework. It uses a theoretical game model with one provider and one seller. The seller sets the procurement price, and then the provider decides the supply level. Both can use live streaming alongside traditional channels. The results show that (1) live streaming raises both procurement and retail prices in traditional channels; (2) retail prices may differ or coincide between channels when different parties use live streaming; (3) as live streaming’s market cultivation efficiency decreases, the adoption strategies shift from both parties using it to only the provider or neither; and (4) live streaming always benefits the provider but harms the seller, with the overall impact on the supply chain depending on the cultivation efficiency and types of equilibrium strategies.
Investigations of Modified Classical Dynamical Models: Melnikov’s Approach, Simulations and Applications, and Probabilistic Control of Perturbations
Authors: Kyurkchiev Nikolay , Zaevski Tsvetelin , Iliev Anton , Kyurkchiev Vesselin , Rahnev Asen
Published: January 2025

We suggest a few kinds of extended classical oscillators in this study. We present a few specific modules for examining these oscillators’ behavior. This will be an essential component of a broader web-based scientific computing platform that is in the works. The modeling and synthesis of radiating antenna designs is also taken into consideration as a potential use case for Melnikov functions. Additionally, we discuss strategies for achieving probabilistic control over system perturbations.
The Discrete Ueda System and Its Fractional Order Version: Chaos, Stabilization and Synchronization
Authors: Diabi Louiza , Ouannas Adel , Hioual Amel , Grassi Giuseppe , Momani Shaher
Published: January 2025

The Ueda oscillator is one of the most popular and studied nonlinear oscillators. Whenever subjected to external periodic excitation, it exhibits a fascinating array of nonlinear behaviors, including chaos. This research introduces a novel fractional discrete Ueda system based on Y-th Caputo fractional difference and thoroughly investigates its chaotic dynamics via commensurate and incommensurate orders. Applying numerical methods like maximum Lyapunov exponent spectra, bifurcation plots, and phase plane. We demonstrate the emergence of chaotic attractors influenced by fractional orders and system parameters. Advanced complexity measures, including approximation entropy (ApEn) and C0 complexity, are applied to validate and measure the nonlinear and chaotic nature of the system; the results indicate a high level of complexity. Furthermore, we propose a control scheme to stabilize and synchronize the introduced Ueda map, ensuring the convergence of trajectories to desired states. MATLAB R2024a simulations are employed to confirm the theoretical findings, highlighting the robustness of our results and paving the way for future works.
Actinomycete-Derived Pigments: A Path Toward Sustainable Industrial Colorants
Authors: Díez Blanca Hey , Torres Cristiana A. V. , Gaudêncio Susana P.
Published: January 2025

Pigment production has a substantial negative impact on the environment, since mining for natural pigments causes ecosystem degradation, while synthetic pigments, derived from petrochemicals, generate toxic by-products that accumulate and persist in aquatic systems due to their resistance to biodegradation. Despite these challenges, pigments remain essential across numerous industries, including the cosmetic, textile, food, automotive, paints and coatings, plastics, and packaging industries. In response to growing consumer demand for sustainable options, there is increasing interest in eco-friendly alternatives, particularly bio-based pigments derived from algae, fungi, and actinomycetes. This shift is largely driven by consumer demand for sustainable options. For bio-pigments, actinomycetes, particularly from the Streptomyces genus, have emerged as a promising green source, aligning with global sustainability goals due to their renewability and biodegradability. Scale-up of production and yield optimization challenges have been circumvented with the aid of biotechnology advancements, including genetic engineering and innovative fermentation and extraction methods, which have enhanced these bio-pigments’ viability and cost-competitiveness. Actinomycete-derived pigments have successfully transitioned from laboratory research to commercialization, showcasing their potential as sustainable and eco-friendly alternatives to synthetic dyes. With the global pigment market valued at approximately USD 24.28 billion in 2023, which is projected to reach USD 36.58 billion by 2030, the economic potential for actinomycete pigments is extensive. This review explores the environmental advantages of actinomycete pigments, their role in modern industry, and the regulatory and commercialization challenges they face, highlighting the importance of these pigments as promising solutions to reduce our reliance on conventional toxic pigments. The successful commercialization of actinomycete pigments can drive an industry-wide transition to environmentally responsible alternatives, offering substantial benefits for human health, safety, and environmental sustainability.
Aluminum and Inorganic Natural Pigment Colored Composites by Powder Metallurgy Forming
Authors: Martínez Miguel Angel , Abenojar Juana
Published: January 2025

Aluminum powder, along with other powders such as steel or stainless steel, is extensively used in powder metallurgy (PM) to produce complex samples with irregular geometric shapes. PM enables the incorporation of fillers to modify the physical, mechanical, or wear properties of aluminum without melting, thereby preventing phase segregation. The novelty of this work lies in the use of inorganic natural pigments (INPs). The primary goal of this study is to produce colored aluminum samples via PM without compromising their mechanical properties. INPs are first characterized to select those with the highest heat resistance. The composites are fabricated with different pigments (10 wt%), formed through uniaxial compaction at 500 MPa, and sintered in a nitrogen atmosphere at 610 °C for 30 min. Density, color, bending strength, and wear are evaluated to identify the most suitable pigment for gas kitchen burners. Mars red, Cobalt blue, and Chrome green pigments provide the best coloration. Dimensional variation is generally less than 1%. The pigments increase the material’s brittleness by 41% to 77%, resulting in a bending modulus increase of up to 160% and deformation reduction of up to 70%. In some cases, intermetallic compounds improve bending strength, as in Al–Chrome green, by 30%. Al–Chrome green exhibits wear resistance comparable to aluminum, with a 40% lower friction coefficient. X-ray diffraction and SEM-EDX confirm AlCr and AlCo intermetallic particles. Thermal stability is verified after 160 heating and cooling cycles without significant material degradation.
Microstructures and Mechanical Properties of Al Matrix Composites Reinforced with TiO2 and Graphitic Carbon Nitride
Authors: Wang Chen , Zhu Xianyong , Zhang Ke , Liu Jiaan , Xiao Xiong , Jiang Cheng , Zhang Jinyuan , Lv Changchun , Sun Zhaoxue
Published: January 2025

The scattering of reinforcement plays a crucial role in the microstructure and properties of metal matrix composites. In this study, an aluminum matrix composite (AMC) was reinforced by 10 wt% TiO2 (Al-10TiO2), with an average particle size of a submicron, combined with a different content of graphitic carbon nitride (g-C3N4), which was fabricated by shift-speed ball milling (SSBM) combined with multi-pass friction stir processing (FSP). In addition to the high hardness of TiO2, g-C3N4 has functional groups to promote in situ reactions. SSBM improves the distribution of reinforcement, refines grain size, and reduces the structural destruction of g-C3N4. The in situ reaction was achieved after multi-pass FSP at a high rotational speed and low travel speeds, which can promote uniform dispersion and grain refinement. Moreover, the g-C3N4 shows the efficient enhancement of strength while maintaining the elongation of AMC. Because the exfoliation of g-C3N4 under the effect of processing reduces the agglomeration of TiO2, boosts the flattening of Al, and enhances interface integration with the base metal. In situ phases can reduce the generation of coarse phases and improve interfacial bonding ability to enhance mechanical properties. The maximum tensile strength has been found at about 172.5 MPa in the Al-10TiO2 containing 1 wt% g-C3N4, which was enhanced by 34% compared to that of the Al-10TiO2. The tensile strength increases when the g-C3N4 content increases from 0 to 1 wt%, but then reduces with a further increase of content. The hardness was increased by 50.2%, 60.2%, and 35% with a g-C3N4 content of 0.5, 1, and 2 wt% compared to AMCs without reinforcement, respectively. According to the test, the enhancement mechanism is mainly attributed to Orowan, grain refinement strengthening, and load transfer of scattered reinforcement. In summary, the utilization of hybrid reinforcements successfully enhances the microstructure and mechanical properties.
Design and Mechanical Behavior of Martensitic Alloys
Authors: Bönisch Matthias
Published: January 2025

In the world of materials, few phenomena are as intriguing and simultaneously as useful as martensitic phase transformations [...]
Smart Zinc-Based Coatings with Chitosan–Alginate Nanocontainers Loaded with ZnO and Caffeine for Corrosion Protection of Mild Steel
Authors: Kamburova Kamelia , Boshkova Nelly , Radeva Tsetska , Boshkov Nikolai
Published: January 2025

The development of environmentally friendly materials is a subject of increasing interest in corrosion protection research. The objective of the present investigation is to propose the preparation procedure of chitosan–alginate (CHI/ALG) nanocontainers loaded with zinc oxide (ZnO) nanoparticles or combining ZnO nanoparticles with corrosion inhibitor caffeine (CAF), both suitable for incorporation into the matrix of ordinary zinc coatings on mild steel substrates. The nanocontainers were synthesized through spontaneous polysaccharide complexation in the presence of ZnO nanoparticles and CAF using a cross-linking agent, namely tripolyphosphate (TPP). Dynamic light scattering and laser Doppler velocimetry measurements are used for evaluation of the size distribution and zeta potentials of the nanocontainers, both loaded or unloaded with CAF. Using UV-spectroscopy, entrapment efficiency and release amounts of CAF are quantitatively evaluated. The nanocontainers thus obtained were incorporated into the matrices of ordinary zinc coatings via co-electrodeposition with zinc from zinc sulfate solution, aiming to improve the corrosion protection of steel in corrosive environments containing chloride ions. The surface morphology and elemental composition of the electrodeposited hybrid coatings before and after treating in the model corrosive medium of 3.5% NaCl is studied by scanning electron microscopy (SEM). The cyclic voltammetry method (CVA) is applied to characterize the cathodic (electrodeposition) and anodic (dissolution) processes. The protective characteristics of the hybrid coatings are investigated by application of potentiodynamic polarization (PDP) curves and polarization resistance (Rp) measurements after a time interval of 40 days. The obtained results indicate that both hybrid coating types could prolong the life time of mild steel in aggressive Cl− ion-containing solution, combining the protection effect of sacrificial zinc with barrier (ZnO) and active (CAF) protective effects.
The Impact of Bacterial Leaf Blight Disease (Pantoea agglomerans) on Grain Yield and Nutritional Quality of Oat
Authors: Zhang Ruochen , Wang Jianjun , Xue Longhai , Kamran Malik , Wang Yue , Wei Xuekai , Zhao Guiqin , Li Chunjie
Published: January 2025

As an important cereal and feed crop, oat has significant economic value and is widely cultivated throughout the world. However, leaf diseases have become a crucial factor limiting the increase in oat grain yield and the optimization of its nutritional quality. Among these, the bacterial leaf blight disease (LBD) caused by Pantoea agglomerans has been an emerging and prevalent oat disease in Northwest China in recent years and has become a major challenge for oat cultivation in this region. This study was designed to investigate the effects of LBD on grain yield and nutritional quality of two common oat varieties, i.e., Avena nuda “Baiyan 2” (B2) and A. sativa “Baiyan 7” (B7), in greenhouses. The results showed that after infection causing LBD, the growth, grain yield and nutritional indexes (except the fiber content) of B2 and B7 were significantly reduced (p < 0.05), with grains per spike, thousand grain weight, protein, and β-glucan reduced by 14.2%, 5.5%, 12.9% and 21.5%, respectively. In contrast, the average fiber content of the infected oats increased by 8.4%. In addition, both with and without infection, the grain yield of B7 was higher than that of B2, while the nutritional quality of B2 seeds was superior to that of B7 seeds. This study provides a scientific basis for LBD control and the variety selection of oat, promoting the sustainable development of the oat industry.
Transition of CO2 from Emissions to Sequestration During Chemical Weathering of Ultramafic and Mafic Mine Tailings
Authors: Zhang Xiaolin , Gou Long-Fei , Tang Liang , Liu Shen , Werner Tim T. , Jiang Feng , Deng Yinger , Mudbhatkal Amogh
Published: January 2025

Weather-enhanced sulphide oxidation accelerates CO2 release into the atmosphere. However, over extended geological timescales, ultramafic and mafic magmatic minerals may transition from being sources of CO2 emissions to reservoirs for carbon sequestration. Ultramafic and mafic mine tailings present a unique opportunity to monitor carbon balance processes, as mine waste undergoes instantaneous and rapid chemical weathering, which shortens the duration between CO2 release and absorption. In this study, we analysed 30 vanadium-titanium magnetite mine tailings ponds with varying closure times in the Panxi region of China, where ~60 years of mineral excavation and dressing have produced significant outcrops of mega-mine waste. Our analysis of anions, cations, saturation simulations, and 87Sr/86Sr; δ13C and δ34S isotopic fingerprints from mine tailings filtrates reveals that the dissolution load of mine tailings may depend significantly on early-stage sulphide oxidation. Despite the abundance of ultramafic and mafic minerals in tailings, dolomite dominates chemical weathering, accounting for ~79.2% of the cationic load. Additionally, due to sulphuric-carbonate weathering, the filtrates undergo deacidification along with sulphide depletion. The data in this study suggest that pristine V-Ti-Fe tailings ponds undergo CO2 emissions in the first two years but subsequently begin to absorb atmospheric CO2 along with the filtrates. Our results provide valuable insights into monitoring weathering transitions and carbon balance in ultramafic and mafic rocks.