bluuebunny/crossref_metadata_2025 huggingface dataset:
Intelligent Monitoring System for Deep Foundation Pit Based on Digital Twin
Authors: Pan Peng , Sun Shuo-Hui , Feng Jie-Xun , Wen Jiang-Tao , Lin Jia-Rui , Wang Hai-Shen
Published: January 2025

Underground space development has significantly increased the depth, scale, and complexity of foundation pit engineering. However, monitoring systems lack mechanical analysis models and fail to predict and control construction risks. Additionally, the foundation pit model could not be updated based on on-site observed data, leading to inaccurate predictions. This study proposes a DT modeling framework for foundation pits, which is used to simulate, predict, and control the risks associated with the entire excavation process. Consequently, based on the DT modeling framework, a DT foundation pit model (DTFPM) was established using modeling and updating algorithms. This study summarizes and identifies the key modeling parameters of foundation pits. A parametric modeling algorithm based on ABAQUS (v2020) was developed to drive the excavation pit modeling process within seconds. Furthermore, an inverse analysis optimization algorithm based on genetic algorithms (GA) and real-time observed deformation was employed to update the elastic modulus of the soil. The algorithm supports parallel computing and can converge within 10 generations. The prediction error of the model after inverse analysis can be reduced to within 10%. Finally, the authors applied DTFPM to establish an intelligent monitoring system. The focus is on real-time and predictive warnings based on the monitoring deformation of the current construction step and the updated model. This study analyzes a Beijing project case to verify the effectiveness of the system, demonstrating the practical application of the proposed method. The results showed that the DTFPM could accurately simulate the deformation behavior of the foundation pit. The system could provide more timely and accurate safety warnings. The proposed method can potentially contribute to the intelligent construction of foundation pits in the future, both theoretically and practically.
Genetic Alterations in Patients with NF2-Related Schwannomatosis and Sporadic Vestibular Schwannomas
Authors: Douwes Jules P. J. , van Eijk Ronald , Maas Sybren L. N. , Jansen Jeroen C. , Aten Emmelien , Hensen Erik F.
Published: January 2025

Background: Unilateral (uVS) and bilateral vestibular schwannoma (bVS) are distinct disease types, yet share tumorigenic features. This study examined causative genetic alterations in three groups: patients with NF2-related schwannomatosis (NF2), young patients with uVS (≤30 years), and older patients with uVS (≥40 years). Methods: Lymphocyte and vestibular schwannoma DNA was genetically analyzed. Outcomes included gene involvement, pathogenicity classification, variant type, effect, and location, and loss of heterozygosity (LOH) of chromosome 22. Results: Among 93 patients, 17% had NF2, 39% were ≤30 years with uVS, and 44% were ≥40 years with uVS. In all patients with NF2 (100%), two or more hits were detected in the tumor DNA, whereas patients with uVS had a slightly lower detection rate (89–98%). NF2-related tumors had a higher frequency of nucleotide variants (76%), while LOH events were more common in uVS (64–69%). Variants were mostly identified in NF2, with nonsense variants over-represented in patients with NF2 (38%) and frameshift variants more prevalent in uVS (44–51%). Conclusions: Biallelic NF2 inactivation primarily drives vestibular schwannoma tumorigenesis. In patients with NF2, two pathogenic NF2 variants or one NF2 variant with LOH are common, whereas patients with uVS often exhibit one NF2 variant with LOH. Additionally, variant types differ between patient groups.
Metabolic Heterogeneity in Diffuse Large B-Cell Lymphoma Cells Reveals an Innovative Antimetabolic Combination Strategy
Authors: Lordello Leonardo , Nuan-Aliman Stéphanie , Kielbassa-Elkadi Karoline , Montagne Aurélie , Kotta Konstantina , Martins Isabelle , Pinto Jurado Eva , Caradeuc Cédric , Lehmann-Che Jacqueline , Martínez-Climent José Ángel , Meignin Véronique , Giraud Nicolas , Kroemer Guido , Bertho Gildas , Thieblemont Catherine , Baud Véronique
Published: January 2025

Background/Objectives: Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma, characterized by aggressive and heterogeneous tumors originating from B-cells. Especially in patients with relapsed or refractory (R/R) disease, DLBCL remains a challenging cancer to treat. Metabolic reprogramming is a hallmark of malignant cells. Our research focuses on developing strategies to enhance clinical outcomes for R/R DLBCL patients by targeting metabolic vulnerabilities. Methods: We investigated the effects of combining metformin and L-asparaginase, two FDA-approved antimetabolic drugs, on DLBCL cell metabolism and survival. Nuclear magnetic resonance (NMR) spectroscopy was employed to assess metabolic disturbances induced by the drug combination. The impact on lipid metabolism, glycolysis, glutaminolysis, the tricarboxylic acid (TCA) cycle, and antioxidant responses was examined. Induction of apoptosis was evaluated by FACS analysis. Results: The combination of metformin and L-asparaginase strongly sensitized DLBCL cells to apoptosis, independently of their oxidative phosphorylation (OxPhos) or BCR/glycolytic status. NMR spectroscopy revealed that this combination induces broader metabolic disturbances than either drug alone. It disrupts lipid metabolism by altering levels of phospholipids, cholesterol, and fatty acids. Additionally, it counteracts the pro-glycolytic effect of metformin, decreases glycolysis, and reduces glutaminolysis. It also affects the TCA cycle and antioxidant responses, critical for cellular energy production and redox balance. Furthermore, this combination interferes with two key cancer survival pathways, mTORC1 and MAPK signaling. Importantly, proof of principle for its beneficial effect was demonstrated in DLBCL patients. Conclusions: Combining metformin and L-asparaginase affects DLBCL cell survival by targeting multiple metabolic pathways and may represent a novel therapeutic approach for R/R DLBCL patients.
Bi4Ti3O12-V/Ag Composite with Oxygen Vacancies and Schottky Barrier with Photothermal Effect for Boosting Nizatidine Degradation
Authors: Liu Sheng , Hu Chen , Gong Ying , Guo Yujuan , Cheng Zhenping , Yuan Mengyi , Liao Zixiang , Xiao Xuewen , Xu Zushun , Du Jun , Shen Ping , Li Qing
Published: January 2025

Piezo-photocatalysis is a promising solution to address both water pollution and the energy crisis. However, the recombination of electron–hole pairs often leads to poor performance, rendering current piezoelectric photocatalysts unsuitable for industrial water treatment. To overcome this issue, oxygen vacancies (V) and Ag nanoparticles (NPs) are introduced into Bi4Ti3O12 (BTO) nanosheets, forming Schottky junctions (BTO-V/Ag). These 2D/3D structures offer more exposed active sites, shorter carrier separation distances, and improved piezo-photocatalytic performance. Additionally, the photothermal effect of Ag NPs supplies additional energy to counteract adsorption changes caused by active species, promoting the generation of more active species. The rate constant of the optimized BTO-V/Ag-2 in the piezo-photocatalytic degradation of nizatidine (NZTD) was 4.62 × 10−2 min−1 (with a removal rate of 98.34%), which was 4.32 times that of the initial BTO. Moreover, the composite catalyst also showed good temperature and pH response. This study offers new insights into the regulatory mechanisms of piezo-photocatalysis at the Schottky junction.
The Effect of Layer Thickness and Nozzle Diameter in Fused Deposition Modelling Printing on the Flexural Strength of Zirconia Ceramic Samples Produced by a Multistage Manufacturing Process
Authors: Smirnov Anton , Yanushevich Oleg , Krikheli Natella , Zhukovskaya Yulia , Soloninkin Mihail , Naumenko Petr , Solis Pinargote Nestor Washington , Peretyagin Pavel , Grigoriev Sergey , Nikitin Nikita
Published: January 2025

The process of creating ceramic items using fused deposition modelling (FDM) enables the creation of intricate shapes for a variety of purposes, including tooling and prototyping. However, due to the numerous variables involved in the process, it is challenging to discern the impact of each parameter on the final characteristics of FDM components, which impedes the advancement of this technology. This paper deals with the application of statistical analysis in the study of the dependence of the flexural strength of sintered zirconia disks on the printing parameters (nozzle diameter, layer thickness, and infill pattern) of the fused deposition method printing of a ceramic–polymer filament containing 80 wt.% zirconia and 20 wt.% polylactide. X-ray-computed tomography and diffraction systems, scanning electron microscopy combined with energy-dispersive spectroscopy, were used for a microstructural analysis of the sintered samples. It was found that the nozzle diameter and infill pattern have no significant influence on the flexural strength values. It was assumed that this is due to the heterogeneous distribution of the ceramic phase in the manufactured filament during extrusion. On the other hand, correlation analysis and analysis of correlation diagrams have shown that the thickness of the filling layer has the greatest effect on flexural strength. The maximum (684 MPa) strength value was found in a sample printed with a layer thickness of 0.2 mm. The minimum layer thickness ensures a more uniform distribution of ceramic particles and minimizes defects in samples that occur during FDM printing. The results obtained make it possible to optimize the considered process of manufacturing ceramic products from ZrO2 printed using FDM technology from extruded composite filaments.
Stretching the Limits of Refractometric Sensing in Water Using Whispering-Gallery-Mode Resonators
Authors: Soler-Carracedo Kevin , Ruiz Antonia , Ríos Susana , de Armas-Rillo Sergio , Martín Leopoldo L. , Hohmann Martin , Martín Inocencio R. , Lahoz Fernando
Published: January 2025

A novel application of microresonators for refractometric sensing in aqueous media is presented. To carry out this approach, microspheres of different materials and sizes were fabricated and doped with Nd3+ ions. Under 532 nm excitation, the microspheres presented typical NIR Nd3+ emission bands with superimposed sharp peaks, related to the Whispering Gallery Modes (WGMs), due to the geometry of the microspheres. When the microspheres were submerged in water with increasing concentrations of glycerol, spectral shifts for the WGMs were observed as a function of the glycerol concentration. These spectral shifts were studied and calibrated for three different microspheres and validated with the theoretical shifts, obtained by solving the Helmholtz equations for the electromagnetic field, considering the geometry of the system, and also by calculating the extinction cross-section. WGM shifts strongly depend on the diameter of the microspheres and their refractive index (RI) difference compared with the external medium, and are greater for decreasing values of the diameter and lower values of RI difference. Experimental sensitivities ranging from 2.18 to 113.36 nm/RIU (refractive index unit) were obtained for different microspheres. Furthermore, reproducibility measurements were carried out, leading to a repeatability of 2.3 pm and a limit of detection of 5 × 10−4 RIU. The proposed sensors, taking advantage of confocal microscopy for excitation and detection, offer a robust, reliable, and contactless alternative for environmental water analysis.
Vegetarian Diets During Complementary Feeding: An Overview of Nutritional and Health Features
Authors: Brusati Marco , Baiocchi Michela
Published: January 2025

Nowadays, vegetarian diets are present in a solid way in Western countries’ lifestyles. Some families opt for this dietetic pattern for their infants too, during the period of introduction of complementary foods. Many releases have been issued about this subject, with different and often contradictory advice and conclusions. The aim of this work is to provide a comprehensive overview through the analysis of recently published opinions of the implementation of a vegetarian or vegan diet over the course of complementary feeding. The literature agrees about some key points to consider, that is the necessity for the diet to be well-planned, in order to meet energy, macro- and micronutrients requirements, as well as the need to follow the child longitudinally. Also, there is a substantial agreement on the need for fortified foods and/or supplements to be included in the diet. Following these suggestions, most (but not all) of the papers agree that normal growth and development may be achieved. Final considerations, however, are not straightforward to make and more research with better definition of the features of the diet adopted and of supplementation used and long-term follow-up studies are highly warranted.
Sub-Daily Performance of a Convection-Permitting Model in Simulating Decade-Long Precipitation over Northwestern Türkiye
Authors: Sonuç Cemre Yürük , Yavuz Veli , Ünal Yurdanur
Published: January 2025

One of the main differences between regional climate model and convection-permitting model simulations is not just how well topographic characteristics are represented, but also how deep convection is treated. The convection process frequently occurs within hours, thus a sub-daily scale becomes appropriate to evaluate these changes. To do this, a series of simulations has been carried out at different spatial resolutions (0.11° and 0.025°) using the COSMO-CLM (CCLM) climate model forced by the ECMWF Reanalysis v5 (ERA5) between 2011 and 2020 over a domain covering northwestern Türkiye. Hourly precipitation and heavy precipitation simulated by both models were compared with the observations by Turkish State Meteorological Service (TSMS) stations and Integrated Multi-satellitE Retrievals for GPM (IMERG). Subsequently, we aimed to identify the reasons behind these differences by computing several atmospheric stability parameters and conducting event-scale analysis using atmospheric sounding data. CCLM12 displays notable discrepancies in the timing of the diurnal cycle, exhibiting a premature shift of several hours when compared to the TSMS. CCLM2.5 offers an accurate representation of the peak times, considering all hours and especially those occurring during the wet hours of the warm season. Despite this, there is a tendency for peak intensities to be overestimated. In both seasons, intensity and extreme precipitation are highly underestimated by CCLM12 compared to IMERG. In terms of statistical metrics, the CCLM2.5 model performs better than the CCLM12 model under extreme precipitation conditions. The comparison between CCLM12 and CCLM2.5 at 12:00 UTC reveals differences in atmospheric conditions, with CCLM12 being wetter and colder in the lower troposphere but warmer at higher altitudes, overestimating low-level clouds and producing lower TTI and KI values. These conditions can promote faster air saturation in CCLM12, resulting in lower LCL and CCL, which foster the development of low-level clouds and frequent low-intensity precipitation. In contrast, the simulation of higher TTI and KI values and a steeper lapse rate in CCLM2.5 enables air parcels to enhance instability, reach the LFC more rapidly, increase EL, and finally promote deeper convection, as evidenced by higher CAPE values and intense low-frequency precipitation.
Characterization of Additively Manufactured Titanium-Based Alloy with a Micro-Arc Oxidation Coating and Overlying Polyurethane Layer
Authors: Lien Po-Wei , Jian Shun-Yi , Hung Jung-Chou , Yang Po-Jen , Lin Hsuan-Han , Chu Kuan-Yu , Kao Chun-Hsiang , Ferng Yi-Cherng , Huang Sheng-Hsiang , Jen Kuo-Kuang
Published: January 2025

Titanium alloys are widely used in the aerospace, automotive, chemical, and biomedical industries due to their excellent corrosion resistance, mechanical properties, and biocompatibility. However, the surface properties of titanium alloys are often insufficient to meet the increasingly complex requirements of certain applications. Therefore, enhancing the surface performance of titanium alloys in physiological environments has become a key focus of research. In this study, a porous oxide layer was generated on the surface of a titanium substrate through micro-arc oxidation (MAO). This layer served as an intermediate layer for a subsequently deposited polyurethane (PU) coating, providing a strong foundation for adhesion. The high porosity of the MAO layer not only facilitated the adhesion of the PU coating but also protected the titanium alloy, further enhancing its corrosion resistance. The surface microstructure after MAO treatment and the morphological changes after application of the PU coating were characterized using scanning electron microscopy. The PU layer uniformly covered the surface of the MAO layer, significantly improving the smoothness and uniformity of the surface. The increase in surface smoothness due to the PU coating on top of the MAO layer was verified through white light interferometry. Additionally, surface hydrophobicity was assessed through water contact angle measurements. The PU layer over the MAO coating significantly enhanced the hydrophobicity of the titanium alloy’s surface, which is crucial for reducing biofouling and improving the effectiveness of biomedical implants. Finally, electrochemical analysis was conducted to study the corrosion resistance of the titanium alloy after MAO and PU treatment. The titanium alloy with an MAO–PU composite coating exhibited the highest corrosion resistance. The findings revealed that the combination of the MAO layer and PU coating provides an excellent multifunctional protective layer for titanium alloys, not only enhancing their durability but also their ability to adapt to physiological and harsh environments.
Structural Aspects and Adhesion of Polyurethane Composite Coatings for Surface Acoustic Wave Sensors
Authors: de Carvalho Mauro dos Santos , Rapp Michael , Voigt Achim , Dirschka Marian , Geckle Udo
Published: January 2025

Surface acoustic wave-based (SAW) sensors are of great interest due to their high sensibility and fast and stable responses. They can be obtained at an overall low cost and with an intuitive and easy-to-use method. The chemical sensitization of a piezoelectric transducer plays a key role in defining the properties of SAW sensors. In this study, we investigate the structural and adhesion properties of a new class of coating material based on polyurethane polymeric composites. We used dark-field microscopy (DFM) and scanning electron microscopy (SEM) to observe the microstructure of polyurethane composite coatings on piezoelectric sensor elements and to analyze the effects of the chemical resistance and adhesion test (CAT) on the coating layers obtained with the polyurethane polymeric composites. The results of the microscopy showed that all polyurethane composite coatings exhibited excellent uniformity and stability after chemical adherence testing (CAT). All of the observations were correlated with the results of the ultrasonic analysis, which demonstrated the role of polyurethane as a binder to form the stable structure of the composites and, at the same time, as an adhesion promoter, increasing the chemical resistance and the adherence of the coating layer to the complex surface of the piezoelectric sensor element.
Pollen Resource Repartition Between Managed Honey Bees (Apis mellifera L. 1758) and Unmanaged Bees in Three Italian National Parks
Authors: Boni Chiara Benedetta , Coppola Francesca , Sagona Simona , Quaranta Marino , Flaminio Simone , Biella Paolo , Tempesti Stefano , Lazzeri Anna Marta , Di Santo Marco , Felicioli Antonio
Published: January 2025

Despite its global importance for the maintenance of healthy ecosystems and its contribution in providing economic benefits to human society, the clade Anthophila is in severe decline worldwide. In this context, counteracting the decline in Apoidea is of fundamental importance. Honey bee density and beekeeping are believed to negatively impact wild bee populations, mostly through competition for food sources. In this study, interspecific trophic competition was investigated using the still seldom exploited approach of a palynological analysis combined with a metabarcoding analysis of the pollen gathered by both managed honey bees and wild bees in three Italian national parks. The entire trophic network was identified as highly specialized (H2′ = 0.933). The results obtained suggest that, overall, wild bee species are sustained by different pollen sources than honey bees. This low sharing of resources could be due to the natural trend occurring in natural populations, where species tend to minimize the competitive overlap through niche differentiation or niche complementarity as a result of coevolution. National parks play a fundamental role in animal and plant species protection and conservation. Therefore, plans should focus on evaluating honey bee densities in the interests of achieving less intensive, more traditional, and sustainable beekeeping, as well as habitat restoration, to promote the survival and reproduction of wild bee populations.
Microstructure and Wear and Corrosion Resistance of CoCrFeMoNiSix (x = 0.25, 0.50, 0.75) HEACs Prepared by Plasma Cladding
Authors: Ma Mingxing , Zhu Chengjun , Wang Zhixin , Dong Ying , Ding Lipei , Ma Haoyuan , Xi Yanjun , Wang Bozhen , Zhu Dachuan , Zhang Deliang
Published: January 2025

CoCrFeMoNiSix (x = 0.25, 0.50, 0.75) HEACs were successfully prepared on Q235 steel substrates by the plasma cladding method. The phase structure, microstructure, element distribution, and wear and corrosion resistance of these coatings were investigated by XRD, OM, SEM, EDS, a friction and wear tester, and an electrochemical workstation. The results show that the CoCrFeMoNiSix (x = 0.25, 0.50, 0.75) coatings are composed of a major FCC phase and minor BCC phase. With an increase in Si content, the lattice constant and cell volume of both phases and the BCC phase content in these alloys gradually increase, while the enthalpy of mixing, Gibbs free energy, atomic radius difference, VEC, and phase density decrease. All the three alloys exhibit typical dendritic structures. With an increase in Si content, the enrichment of Mo and Si in the interdendrite region is significantly reduced. The friction coefficients of CoCrFeMoNiSix (x = 0.25, 0.50, 0.75) HEACs show a trend of first increasing, then decreasing, and gradually stabilizing with an increase in time, and are 0.604, 0.526, and 0.534, respectively. The wear resistance of the three alloys is mainly related to the changes in crystallinity and high-strength BCC phase content caused by different Si contents. The polarization curves of CoCrFeMoNiSix (x = 0.25, 0.50, 0.75) high-entropy alloy coatings show an obvious passivation zone, and the corrosion resistance is significantly better than that of Q235 steel substrate. The CoCrFeMoNiSi0.75 coating has the highest self-corrosion potential, smallest self-corrosion current, largest capacitive reactance arc radius, and best corrosion resistance in a 3.5% NaCl solution.
Multi-Physics Modeling in Curved Surface Laser Cladding: Impact of Scanning Trajectories and Cladding Parameters on Temperature Field and Coating Thickness
Authors: Deng Chenyun , Chen Wei , Zhu Yingxia
Published: January 2025

In order to apply laser cladding technology to the complex surface processing of hot-working dies, this study developed a numerical model for curved surface laser cladding along various scanning trajectories under multi-physics coupling considering the dynamics of the molten pool, cladding parameters (scanning speed and laser power), Marangoni effect, and solid–liquid phase transition. Utilizing this model and by altering cladding parameters, the temperature field and the variation in coating thickness along various scanning trajectories were studied as well as the interaction between the two. The following discoveries were made. Variations in scanning trajectories lead to differences in the coating thickness of curved surface laser cladding. Regardless of the combination of cladding parameters, the coating thickness of scanning from top to bottom is always less than that from bottom to top, with a difference of approximately 0.05 mm. The temperature field and coating thickness influence each other. The Marangoni effect induced by the temperature field is the primary cause of coating thickness growth, while the coating thickness affects thermal transfer from the thermal source, ultimately influencing the temperature field. Employing a greater laser power or a slower scanning speed, or a combination of greater laser power and slower scanning speed, can increase the coating thickness and its maximum temperature in curved surface laser cladding. The model, when contrasted with experimental data, exhibits a comprehensive discrepancy of 3.49%, signifying its high precision and practical engineering applicability.
Artificial Intelligence in Oral Cancer: A Comprehensive Scoping Review of Diagnostic and Prognostic Applications
Authors: Vinay Vineet , Jodalli Praveen , Chavan Mahesh S. , Buddhikot Chaitanya. S. , Luke Alexander Maniangat , Ingafou Mohamed Saleh Hamad , Reda Rodolfo , Pawar Ajinkya M. , Testarelli Luca
Published: January 2025

Background/Objectives: Oral cancer, the sixth most common cancer worldwide, is linked to smoke, alcohol, and HPV. This scoping analysis summarized early-onset oral cancer diagnosis applications to address a gap. Methods: A scoping review identified, selected, and synthesized AI-based oral cancer diagnosis, screening, and prognosis literature. The review verified study quality and relevance using frameworks and inclusion criteria. A full search included keywords, MeSH phrases, and Pubmed. Oral cancer AI applications were tested through data extraction and synthesis. Results: AI outperforms traditional oral cancer screening, analysis, and prediction approaches. Medical pictures can be used to diagnose oral cancer with convolutional neural networks. Smartphone and AI-enabled telemedicine make screening affordable and accessible in resource-constrained areas. AI methods predict oral cancer risk using patient data. AI can also arrange treatment using histopathology images and address data heterogeneity, restricted longitudinal research, clinical practice inclusion, and ethical and legal difficulties. Future potential includes uniform standards, long-term investigations, ethical and regulatory frameworks, and healthcare professional training. Conclusions: AI may transform oral cancer diagnosis and treatment. It can develop early detection, risk modelling, imaging phenotypic change, and prognosis. AI approaches should be standardized, tested longitudinally, and ethical and practical issues related to real-world deployment should be addressed.
Diagnostic Challenge of Localized Tenosynovial Giant Cell Tumor in Children
Authors: Ichikawa Jiro , Ochiai Satoshi , Kawasaki Tomonori , Onohara Kojiro , Wako Masanori , Haro Hirotaka , Hagino Tetsuo
Published: January 2025

This report describes a rare case of a pediatric tenosynovial giant cell tumor (TSGCT) with a delayed diagnosis. A 9-year-old boy presented with a 3-month history of knee pain and swelling, initially attributed to a femoral non-ossifying fibroma and arthritis based on computed tomography findings and slightly elevated C-reactive protein levels. The symptoms persisted despite medical treatment. Magnetic resonance imaging (MRI) revealed a tumor in the posterior compartment. He underwent surgery, and the pathology confirmed the diagnosis of localized TSGCT. Six months postoperatively, the patient remained asymptomatic. Pediatric knee pain is a complex symptom associated with inflammatory conditions and benign and malignant tumors. Benign tumors, as in this case, can be misdiagnosed as arthritis, delaying diagnosis and treatment. MRI is recommended in cases involving symptom persistence. However, histopathological, immunohistochemical, and morphological examinations are crucial for definitive diagnosis, particularly when the imaging findings are inconclusive.
Artificial Intelligence-Empowered Radiology—Current Status and Critical Review
Authors: Obuchowicz Rafał , Lasek Julia , Wodziński Marek , Piórkowski Adam , Strzelecki Michał , Nurzynska Karolina
Published: January 2025

Humanity stands at a pivotal moment of technological revolution, with artificial intelligence (AI) reshaping fields traditionally reliant on human cognitive abilities. This transition, driven by advancements in artificial neural networks, has transformed data processing and evaluation, creating opportunities for addressing complex and time-consuming tasks with AI solutions. Convolutional networks (CNNs) and the adoption of GPU technology have already revolutionized image recognition by enhancing computational efficiency and accuracy. In radiology, AI applications are particularly valuable for tasks involving pattern detection and classification; for example, AI tools have enhanced diagnostic accuracy and efficiency in detecting abnormalities across imaging modalities through automated feature extraction. Our analysis reveals that neuroimaging and chest imaging, as well as CT and MRI modalities, are the primary focus areas for AI products, reflecting their high clinical demand and complexity. AI tools are also used to target high-prevalence diseases, such as lung cancer, stroke, and breast cancer, underscoring AI’s alignment with impactful diagnostic needs. The regulatory landscape is a critical factor in AI product development, with the majority of products certified under the Medical Device Directive (MDD) and Medical Device Regulation (MDR) in Class IIa or Class I categories, indicating compliance with moderate-risk standards. A rapid increase in AI product development from 2017 to 2020, peaking in 2020 and followed by recent stabilization and saturation, was identified. In this work, the authors review the advancements in AI-based imaging applications, underscoring AI’s transformative potential for enhanced diagnostic support and focusing on the critical role of CNNs, regulatory challenges, and potential threats to human labor in the field of diagnostic imaging.
The Perspectives of Young Adults with Cerebral Palsy on Transition to Adult’s Health Care and Rehabilitation
Authors: Jeglinsky-Kankainen Ira , Vänskä Nea , Kinnunen Anu , Sätilä Heli , Sipari Salla
Published: January 2025

The purpose of this study was to describe the perspectives of young adults with cerebral palsy on participating in the transition process when transitioning from children’s health care to adults’ health care and rehabilitation. A phenomenographic approach with data collected with semi-structured interviews was used. Fourteen young adults aged 19–26 with cerebral palsy participated. The analysis resulted in four categories: (1) need for comprehensive and participatory rehabilitation; (2) barriers in the rehabilitation system; (3) self-awareness, courage and activity are rewarded; and (4) a dream of an active role in society. To conclude, the young adults had both positive and negative experiences of the transition process as well as of the rehabilitation planning at the adult health care service. It is important to start the transition planning early, and to involve the young adult as an active participant in the planning process. Both in the transition phase and in the adult health care service an anticipatory and collaborative approach where the young adult’s holistic needs would be considered should be standard practice. A focus is needed on how to grow towards a good adulthood and how to live a meaningful life as a valued member of society.
Dynamical Systems on Generalised Klein Bottles
Authors: Grindrod Peter , Yim Ka Man
Published: January 2025

We propose a high-dimensional generalisation of the standard Klein bottle extending beyond those considered previously. We address the problem of generating continuous scalar fields (distributions) and dynamical systems (flows) on such state spaces, which can provide a rich source of examples for future investigations. We consider a class of high-dimensional dynamical systems that model distributed information processing within the human cortex, which may be capable of exhibiting some Klein bottle symmetries. We deploy topological data analytic methods in order to analyse their resulting dynamical behaviour and suggesting future challenges.
A Novel Quadrilateral Contour Disentangled Algorithm for Industrial Instrument Reading Detection
Authors: Li Xiang , Zeng Changchang , Yao Yong , Qian Jide , Zhang Haiding , Zhang Sen , Yang Suixian
Published: January 2025

Instrument reading detection in industrial scenarios poses significant challenges due to reading contour distortion caused by perspective transformation in the instrument images. However, existing methods fail to accurately read the display automatically due to incorrect labeling of the target box vertices, which arises from the vertex entanglement problem. To address these challenges, a novel Quadrilateral Contour Disentangled Detection Network (QCDNet) is proposed in this paper, which utilizes the quadrilateral disentanglement idea. First, a Multi-scale Feature Pyramid Network (MsFPN) is proposed for effective feature extraction to improve model accuracy. Second, we propose a Polar Coordinate Decoupling Representation (PCDR), which models each side of the instrument contour using polar coordinates. Additionally, a loss function for the polar coordinate parameters is designed to aid the PCDR in more effectively decoupling the instrument reading contour. Finally, the experimental results on the instrument dataset demonstrate that QCDNet outperforms existing quadrilateral detection algorithms, with improvements of 4.07%, 1.8%, and 2.89% in Precision, Recall, and F-measure, respectively. These results confirm the effectiveness of QCDNet for instrument reading detection tasks.
Uncovering the Factors Affecting the Engagement of and Changes in Participants in a Blended Academic Leadership Development Program
Authors: Li Xinyi , Cheng Zhao , Zhu Chang
Published: January 2025

This study explores what factors influence academics’ engagement, and enhances the comprehension of engagement and the application of leadership skills among young academics within blended learning settings. Through mixed-method research, analyzing quantitative data derived from engagement scores and qualitative insights from 20 participants’ self-feedback reports, the study reveals a shift towards leadership models characterized by collaborative and digital proficiency underpinned by strategic thinking and problem-solving skills. The findings reveal that program design, intra-group interaction, communication, and collaborative environment were the key factors that enhanced academics’ engagement. Meanwhile, multiple regression analysis revealed the effects of variables such as gender, position type, educational level, and age on engagement. Among them, academic level, especially Doctoral degree, was significantly associated with higher engagement. Based on these findings, this study provides empirical support for optimizing the design of academic leadership development programs and suggests ways to further improve scholarly engagement.
Enhancing Automotive Intrusion Detection Systems with Capability Hardware Enhanced RISC Instructions-Based Memory Protection
Authors: Kalutharage Chathuranga Sampath , Mohan Saket , Liu Xiaodong , Chrysoulas Christos
Published: January 2025

The rapid integration of connected technologies in modern vehicles has introduced significant cybersecurity challenges, particularly in securing critical systems against advanced threats such as IP spoofing and rule manipulation. This study investigates the application of CHERI (Capability Hardware Enhanced RISC Instructions) to enhance the security of Intrusion Detection Systems (IDSs) in automotive networks. By leveraging CHERI’s fine-grained memory protection and capability-based access control, the IDS ensures the robust protection of rule configurations against unauthorized access and manipulation. Experimental results demonstrate a 100% detection rate for spoofed IP packets and unauthorized rule modification attempts. The CHERI-enabled IDS framework achieves latency well within the acceptable limits defined by automotive standards for real-time applications, ensuring it remains suitable for safety-critical operations. The implementation on the ARM Morello board highlights CHERI’s practical applicability and low-latency performance in real-world automotive scenarios. This research underscores the potential of hardware-enforced memory safety in mitigating complex cyber threats and provides a scalable solution for securing increasingly connected and autonomous vehicles. Future work will focus on optimizing CHERI for resource-constrained environments and expanding its applications to broader automotive security use cases.
ResShift-4E: Improved Diffusion Model for Super-Resolution with Microscopy Images
Authors: Gao Depeng , Gong Ying , Cao Jingzhuo , Wang Bingshu , Zhang Han , Dong Jiangkai , Qiu Jianlin
Published: January 2025

Blind super-resolution algorithms based on diffusion models still face significant challenges at the current stage, including high computational cost, long inference time, and limited cross domain generalization ability. This paper aims to apply super-resolution algorithms to the field of optical microscopy imaging to reveal more microscopic structures and details. Firstly, we proposed a lightweight super-resolution model called ResShift-4E, which is an optimized model from two important aspects: reducing the diffusion steps in ResShift and strengthening the influence of the original residuals on model learning. Secondly, we constructed a dataset of Multimodal High-resolution Microscopy Images (MHMI) including a total of 1220 images, which is available on line. Moreover, we extended our model to application-oriented research on blind image super-resolution of optical microscopy imaging. The experimental results demonstrate that our ResShift-4E model outperforms other models on various microscopy images.
Neural Network Based Power Meter Wiring Fault Recognition of Smart Grids Under Abnormal Reactive Power Compensation Scenarios
Authors: Zheng Huizhe , Lin Zhongshuo , Lin Huan , Huang Chaokai , Huang Xiaoqi , Ji Suna , Zhang Xiaoshun
Published: January 2025

This paper explores the challenges of detecting wiring anomalies in three-phase, four-wire energy metering devices, especially when large amounts of reactive power compensation are involved. Traditional methods, such as the hexagon phasor diagram technique, perform well under standard loads, but struggle to adapt to new situations, such as over- or under-compensation. To overcome these limitations, this paper proposes a hybrid approach that combines mechanism-based knowledge with data-driven technologies, including backpropagation neural networks (BPNNs). This method improves the accuracy and efficiency of anomaly detection and can better adapt to a dynamic power environment. The result is improved universality of anomaly detection, which helps to achieve safer, more accurate, and more efficient smart grid operation in complex situations.
Photovoltaic-Thermal Side-Absorption Concentrated Module with Micro-Structures as Spectrum-Division Component for a Hybrid-Collecting Reflection Solar System
Authors: Sze Jyh-Rou , Wei An-Chi
Published: January 2025

A photovoltaic-thermal side-absorption concentrated module (PT-SACM) based on spectrum division for photovoltaic-thermal hybrid applications is carried out. In order to reduce the absorption by materials and the axial-chromatic aberration caused by the transmissive optical system and to improve the performance of the entire system, a reflective system, the parabolic mirror array, fabricated by the ultra-precision diamond turning technology, is proposed herein. For the purposes of spectrum division, thinner volume, lightweight, and wide acceptance angle, the proposed module is designed with a diffraction optical element (DOE), a light-guide plate with a micro-structure array and a parabolic mirror array. Among them, the DOE can separate the solar spectrum into the visible band, which is converted to electrical energy via photovoltaics, and the infrared band, whose thermal energy is collected. Experimental measurements show that the overall optical efficiency of the entire system reached 38.32%, while a deviation percentage of 3.5% is calculated based on the simulation. The system has successfully demonstrated the separation of visible and infrared bands of the solar spectrum. Meanwhile, the lateral displacement between the micro-structures of the light-guide plate and the focus of the parabolic mirror array can be used to compensate for the angular deviation of the sun incidence, thereby achieving wide-angle acceptance via the proposed solar concentration system.
New Nusselt Number Correlation and Turbulent Prandtl Number Model for Turbulent Convection with Liquid Metal Based on Quasi-DNS Results
Authors: Fu Hao , Chen Juan , Tong Yanjun , Peng Sifan , Liu Fang , Lyu Xuefeng , Zhao Houjian
Published: January 2025

Liquid metal is widely used as the primary coolant in many advanced nuclear energy systems. Prandtl number of liquid metal is much lower than that of the conventional coolant of water or gas. Based on the Reynolds analogy, the turbulent Prandtl number is assumed to be a constant around unity. For the turbulent convection of liquid metal, dissipations of half the temperature variance are larger than those of turbulent kinetic energies. The dissimilarity between the thermal and momentum fields increases as Pr decreases. The turbulent Prandtl number is larger than one for the liquid metal. In the current investigation, the turbulent convection of liquid metal in the channel is quasi-directly simulated with OpenFOAM-7. The turbulent statistics of the momentum and the thermal field are compared with the existing database to validate the numerical model. The power law for dimensionless temperature distribution with different Prandtl numbers is obtained by regression analysis of numerical results. A new Nusselt number correlation is derived based on the power law. The new Nusselt number correlation agrees well with the DNS results in the literature. The momentum mixing process between different layers in the cross section is compared with the thermal mixing process. The effects of the Prandtl number on the difference between the turbulence time scale and scalar time scale are analyzed. A new turbulent Prandtl number model with local parameters is obtained for turbulent convection with liquid metal. Combined with the k−ω model, the temperature distributions with the new turbulent Prandtl number model agree well with the DNS results in the literature. The new turbulent Prandtl number model can be used for turbulent convection with different Prandtl and different Reynolds numbers.
The Potential of a Thermoelectric Heat Dissipation System: An Analytical Study
Authors: Li Xuechun , Shi Rujie , Zhu Kang
Published: January 2025

Thermoelectric heat dissipation systems offer unique advantages over conventional systems, including vibration-free operation, environmental sustainability, and enhanced controllability. This study examined the benefits of incorporating a thermoelectric cooler (TEC) into conventional heat sinks and investigated strategies to improve heat dissipation efficiency. A theoretical model introducing a dimensionless evaluation index (rq) is proposed to assess the system’s performance, which measures the ratio of the heat dissipation density of a conventional heat dissipation system to that of a thermoelectric heat dissipation system. Here, we subjectively consider 0.9 as a cutoff, and when rq<0.9, the thermoelectric heat dissipation system shows substantial superiority over conventional ones. In contrast, for rq>0.9, the advantage of the thermoelectric system weakens, making conventional systems more attractive. This analysis examined the effects of engineering leg length (L*), the heat transfer allocation ratio (rh), and temperature difference (ΔT) on heat dissipation capabilities. The results indicated that under a fixed heat source temperature, heat sink temperature, and external heat transfer coefficient, an optimal engineering leg length exists, maximizing the system’s heat dissipation performance. Furthermore, a detailed analysis revealed that the thermoelectric system demonstrated exceptional performance under small temperature differences, specifically when the temperature difference was below 32 K with the current thermoelectric (TE) materials. For moderate temperature differences between 32 K and 60 K, the system achieved optimal performance when rh≥−2.4+1.37e0.019ΔT. This work establishes a theoretical foundation for applying thermoelectric heat dissipation systems and provides valuable insights into optimizing hybrid heat dissipation systems.
Study on the Effect of Mixed-Phase Icing on the Aerodynamic Characteristics of Wind Turbine Airfoil
Authors: Wang Xiang , Ru Yiyao , Zhao Huanyu , Wang Zhengzhi
Published: January 2025

Wind turbines operating in high-altitude and cold regions are susceptible to icing phenomenon, which is a serious threat to the power generation efficiency and operational safety. On the basis of the current research on supercooled droplet icing, mixed-phase icing is investigated. Based on icing numerical simulations under mixed-phase conditions, the aerodynamic characteristics of wind turbine airfoils before and after icing are analyzed. The results indicate that as the icing thickness increases, the aerodynamic characteristics of the airfoil gradually deteriorate, with the lift decreasing by 40.2% and the drag increasing by 135.2%. The aerodynamic characteristics of airfoil after icing are analyzed under both glaze and rime ice conditions and compared to those of the clear airfoil. The results show that icing leads to a decrease in the lift coefficient and an increase in the drag coefficient of the airfoil. This deterioration is primarily due to the fact that icing causes premature separation of the airfoil airflow, and icing can cause obstruction at the leading edge, which leads to the formation of local vortices and a decline in aerodynamic performance. The effects of icing on the aerodynamic characteristics of wind turbine airfoils under glaze and rime ice conditions are compared, and the lift-to-drag ratio decreases by 87.9% under the glaze ice condition and by 62.4% under rime ice conditions. The results show that the effects of mixed-phase icing under glaze ice conditions has a more severe impact than under rime ice conditions.