Search Results (138)

Korean pine (Pinus koraiensis) is a vital woody oil tree species native to Northeast Asia, with its pine nuts serving as the primary global source of edible pine nuts globally due to their rich nutritional content. Currently, seed yield from Korean pine is low and unstable, failing to meet the market demand. The limited number of female cones is the primary factor restricting its yield. MADS-box family members are crucial in regulating the initiation, differentiation, and morphogenesis of floral organs. However, systematic identification and characterization of MADS-box proteins in Korean pine have not been reported. This study utilized transcriptome data from reproductive and vegetative buds during the flower bud differentiation stage of Korean pine to comprehensively identify MADS-box family members through bioinformatics analysis and molecular biology approaches. A total of 37 PkMADS-box genes were identified, including 6 type I and 31 type II (MIKC) genes, which were classified into 8 subfamilies. The physicochemical properties, conserved domains, conserved motifs, protein structures, gene expression profiles, and protein–protein interaction networks of these genes were analyzed. Key genes associated with physiological differentiation (flower induction) and sexual organogenesis were identified based on expression patterns during flower bud differentiation and flower organ development. Among these, PkMADS4 and PkMADS26 are likely involved in positively regulating flower induction, while PkMADS9 plays a role in the morphological differentiation of sexual organs in a dose-dependent manner and overexpression of PkMADS9 promoting early flowering in transgenic Arabidopsis. These genes were also identified as key candidates for regulating reproductive phase changes and strobilus development. This study provides a theoretical foundation for further investigation of MADS-box genes in reproduction and offers insights into genetic improvements aimed at enhancing the seed yield of Korean pine. Full article

In contemporary practice, dental implants are widely recognized as a reliable and effective solution for rehabilitating edentulous patients. Nevertheless, implant placement in the atrophied maxilla presents considerable challenges, with treatment planning influenced by various factors such as patient demographics, anatomical constraints, and economic considerations. Advances in imaging technology have positioned cone-beam computed tomography (CBCT) as the preferred modality for enhancing implant placement accuracy. By producing high-resolution three-dimensional radiographic images, CBCT facilitates precise assessment of maxillary anatomy at the proposed implant site—including bone height, width, length, and angulation—thereby optimizing surgical planning and improving the predictability and success rates of implant integration. Moreover, the timing of implant placement must account for the necessity of maxillary augmentation to ensure implant stability and reduce the risk of postoperative complications. This review discusses the clinical utility of CBCT as a diagnostic tool for preoperative assessment, focusing on the identification of critical anatomical landmarks and the determination of indications for bone augmentation, thereby highlighting its crucial role in enabling accurate treatment planning, minimizing surgical risks, and promoting the long-term survival of dental implants. Full article

Background: Pulmonary arteriovenous malformations (PAVMs) are abnormal vascular connections between the pulmonary arteries and veins, often leading to significant clinical complications. Embolisation has become the primary therapeutic modality for managing symptomatic PAVMs, with advancements in both technique and technology improving patient outcomes. Recent progress includes the introduction of precisely targeted embolisation techniques, such as cone-beam computed tomography (CBCT) guidance and three-dimensional imaging, enabling more accurate identification and treatment of complex, multiple, or peripheral lesions. Additionally, vascular plugs and microcoils have demonstrated superior performance in terms of lower recurrence rates and more complete occlusion of feeding vessels compared to traditional devices. The use of endovascular navigation systems has further enhanced procedural success. Aim: The objective of this review is to explore the latest innovations in embolisation therapies for PAVMs, emphasising emerging techniques, devices, and strategies that have refined treatment efficacy and safety. Methods: We performed a focused literature search to identify key publications relevant to current approaches in thoracic vascular imaging. Searches were conducted in PubMed and Embase using combinations of terms related to ‘thoracic imaging,’ ‘vascular,’ ‘Computed Tomography (CT) angiography,’ and ‘MRI.’ Additional articles were identified from reference lists of major reviews and landmark studies. Priority was given to publications from the past 10 years, with older key papers included when historically relevant. Selection was based on thematic relevance rather than formal criteria. Conclusions: Advancements in patient selection and pre-procedural planning, driven by enhanced imaging modalities such as CT pulmonary angiography (CTPA) and contrast-enhanced ultrasound, have led to improved outcomes and reduced complications. While the benefits of embolisation are well-documented, ongoing research continues to explore the long-term outcomes, including post-embolisation pulmonary function, recurrence rates, and quality of life improvements. Full article

Background/Objectives: Sinus elevation in the posterior maxilla carries a risk of hemorrhage due to injury of the posterior superior alveolar artery (PSAA). Accurate preoperative identification of the PSAA using cone-beam computed tomography (CBCT) can enhance surgical safety. This retrospective study evaluated the prevalence, location, diameter, and visibility of the PSAA in a Saudi population. Methods: A total of 117 CBCT scans (234 sinuses) obtained between 2022 and 2024 were analyzed. The PSAA’s visibility, diameter, and distances from the alveolar crest, sinus floor, medial wall, and sinus septa were measured. Associations with age, sex, smoking status, and the presence of sinus septa were statistically assessed. Results: The PSAA was identified in 98.3% of sinuses. Intraosseous and submucosal locations predominated in premolar and molar regions, respectively. Class A arteries (≤1 mm) were most frequent. Significant differences were found between premolar and molar regions in arterial location and distances from the alveolar crest and sinus walls (p < 0.001). Older individuals exhibited medial displacement of the artery in the molar region, and smokers showed significantly smaller diameters (p < 0.05). Sinus septa were associated with increased PSAA distances from the sinus floor and medial wall. Conclusions: The PSAA demonstrates high detectability and marked variability in position and caliber within this Saudi cohort. Recognition of these anatomical variations is essential for reducing complications during sinus-augmentation procedures. Full article

The conversion of biodiesel’s chemical energy into mechanical work in diesel engines is strongly influenced by the formation and quality of the fuel–air mixture. The physical and chemical properties of biodiesel, together with the operating characteristics of the fuel injection system, play a crucial role in this process. This study presents experimental findings on the injection behavior of a mechanically controlled injection system using three fuel types: pure rapeseed biodiesel, a 50% biodiesel–diesel blend, and conventional diesel fuel. The analysis focused on injection pressure, injection timing, injection duration, and fuel delivery under various operating conditions. In the second part of the experimental investigation, spray visualization was carried out by injecting fuels into a transparent liquid-filled chamber. A dedicated imaging and processing system was applied to capture and analyze spray development. From the recorded sequences, macroscopic spray parameters—including spray penetration length, spray cone angle, and projected spray area—were determined across different injection regimes. This approach allows clear identification of spray development tendencies and supports systematic comparison between fuels, particularly in relation to differences in injection pressure, injection duration, and delivered fuel quantity arising from the mechanically governed injection system. Correlation analysis between spray penetration length and peak injection pressure further highlights pressure-driven contributions to spray evolution. The findings contribute to better understanding of biodiesel spray behavior under realistic mechanically controlled conditions, supporting optimization of fuel injection performance and aiding in the selection or formulation of biodiesel fuels with improved spray characteristics. Full article

The piezocone penetration test (CPTU) provides rapid, continuous measurements of in situ geotechnical parameters, making it a valuable tool for soil classification and stratigraphic identification. However, conventional classification methods frequently exhibit poor cross-regional generalizability and remain limited in achieving fine-grained stratigraphic identification. To address these limitations, this study constructs a cross-regional CPTU soil classification dataset by integrating data from three sources: the Premstaller Geotechnik database, the Global-CPT/3/1196 database, and a Chinese engineering project database. The compiled dataset was subsequently partitioned into a training set of 454,184 samples and three independent test sets. Three feature combinations and four machine learning algorithms—Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Artificial Neural Network (ANN), and Extreme Gradient Boosting (XGBoost), were evaluated in terms of classification performance and cross-regional robustness. Results indicate that the XGBoost-based model, using Depth, corrected cone resistance (q_t), friction ratio (R_f), pore pressure ratio (B_q), normalized friction ratio (F_r), and pore pressure (u₂) as inputs, achieved the highest performance across the three independent test sets. Misclassifications primarily occurred between adjacent soil types with similar physical characteristics. SHapley Additive exPlanations (SHAP) analysis indicated that F_r and q_t were the dominant contributors to model predictions; R_f played an important role in minority classes; Depth showed relatively balanced importance across classes, while B_q and u₂ made minimal contributions. Applying the best-performing model to unseen CPTU data and comparing the predictions with borehole logs showed that the model not only preserves overall stratigraphic trends but also identifies finer-scale stratigraphic details. Full article

Electromechanical systems are inherently hybrid in nature, combining electrical and mechanical processes, and their increasing complexity requires the development of universal and computationally efficient mathematical models. In this study, we propose a macromodeling approach that represents the electromechanical system as a “black box,” in which internal physical processes are disregarded and the system behavior is defined solely by the relationship between input and output signals. The identification of such macromodels is reduced to solving a nonlinear optimization problem. To address this challenge, the directed cone method is applied, which searches for the global minimum of the objective function through stochastic movement across the hyperplane defined by the optimization problem. Several algorithmic improvements of the directed cone method are investigated, including step-size adaptation, simultaneous adaptation of step size and hypercone opening angle, and a tunneling procedure. Their effectiveness is evaluated using the construction of a macromodel of a single-phase asynchronous motor as a case study. Performance was assessed according to computational complexity (measured as the number of objective function evaluations until convergence), relative modeling accuracy, and the dynamics of progression toward the global minimum. The experimental results show that the tunneling-based algorithm provides the highest modeling accuracy with the lowest computational cost, whereas the step-size-only adaptation was found to be the least effective. The proposed approach demonstrates the feasibility of constructing accurate macromodels of electromechanical systems that can be integrated into computer-aided modeling environments such as MATLAB/Simulink R2023b. Future work will focus on extending the approach to a broader class of electromechanical systems and developing hybrid algorithms to enhance robustness with respect to model nonlinearity. Full article

The Messara Basin, a critical agricultural region in Crete, Greece, faces escalating geohazards, particularly land subsidence driven by intensive groundwater abstraction. Historical radar interferometry (1992–2009) indicated subsidence up to 20 mm·yr⁻¹, while recent European Ground Motion Service data (2016–2021) show mean vertical velocities reaching −31.2 mm·yr⁻¹. This study provides the first integrated hydrogeological assessment for the Basin, based on systematic field surveys, borehole inventories, and four coordinated campaigns (2021–2023) that established a basin-wide monitoring network of 767 stations. The dataset supports delineation of recharge zones, identification of potentiometric depressions, and mapping of aquifer-stress areas. Results show strong seasonality and extensive cones of depression, with local heads declining to ~−50 m below sea level. Land-use change (1990–2018 CORINE data; 2000–2020 agricultural censuses) combined with updated geological mapping highlights the vulnerability of post-Alpine formations, especially Quaternary and Plio–Pleistocene deposits, to deformation. The combined evidence links pumping-induced head decline with spatially coherent subsidence, delineates hotspots of aquifer stress, and identifies zones of elevated compaction risk. These findings provide a decision-ready baseline to support sustainable groundwater management, including enhanced monitoring, targeted demand controls, and managed aquifer-recharge trials. Full article

In the context of industrial transitions and tariff frictions, financial markets are experiencing frequent defaults, emphasizing the urgency of upgrading credit scoring methodologies. A novel credit risk identification model integrating generative adversarial networks (GAN) and the minimax probability machine (MPM) is proposed. GAN generates realistic augmented samples to alleviate class imbalance in the credit score dataset, while the MPM optimizes the classification hyperplane by reformulating probability constraints into second-order cone problems via the multivariate Chebyshev inequality. Numerical experiments conducted on the South German Credit dataset, which represents individual (consumer) credit risk, demonstrate that the proposed generative adversarial network’s minimax probability machine (GAN-MPM) model achieves 76.13%, 60.93%, 71.78%, and 72.03% for accuracy, F1-score, sensitivity, and AUC, respectively, significantly outperforming support vector machines, random forests, and XGBoost. Furthermore, SHAP analysis reveals that the installment rate in percentage of disposable income, housing type, duration in month, and status of existing checking accounts are the most influential features. These findings demonstrate the effectiveness and interpretability of the GAN-MPM model, offering a more accurate and reliable tool for credit risk management. Full article

For large-scale measurement of microbubble parameters on the ocean surface beneath breaking waves, a buoy-type bubble sensor (BBS) is proposed. This sensor integrates a panoramic bubble imaging sub-sensor with a circular array fiber-optic sub-sensor. The sensitive unit of the latter sub-sensor is designed via theoretical modeling and experimental validation. Theoretical calculations indicate that the optimal cone angle for a quartz fiber-optic-based sensitive unit ranges from 45.2° to 92°. A prototype array element with a cone angle of 90° was fabricated and used as the core component for feasibility experiments in static and dynamic two-phase (gas and liquid) identification. During static identification, the reflected optical power differs by an order of magnitude between the two phases. For dynamic sensing of multiple microbubble positions, the reflected optical power varies from 13.4 nW to 29.3 nW, which is within the operating range of the array element’s photodetector. In theory, assembling conical quartz fiber-based sensitive units into fiber-optic probes and configuring them as arrays could overcome the resolution limitations of the panoramic bubble imaging sub-sensor. Further discussion of this approach will be presented in a subsequent paper. Full article

Accurate numerical simulations of soil-tire interactions are essential for optimizing agricultural machinery to minimize soil compaction and enhance crop yield. This study developed and compared two approaches for identifying and validating parameters of a LS-Dyna soil model. The laboratory-based approach derives parameters from triaxial, consolidation, and cone penetrometer tests (CPT), while the optimization-based method refines them using in-situ CPT data via LS-OPT to better capture field variability. Simulations employing Multi-Material Arbitrary Lagrangian–Eulerian (MM-ALE), Smoothed Particle Hydrodynamics (SPH), and Hybrid-SPH methods demonstrate that Hybrid-SPH achieves the optimal balance of accuracy (2% error post-optimization) and efficiency (14-h runtime vs. 22 h for SPH). Optimized parameters improve soil–tire interaction predictions, including net traction and tire sinkage across slip ratios from −10% to 30% (e.g., sinkage of 12.5 mm vs. 11.1 mm experimental at 30% slip, with overall mean-absolute percentage error (MAPE) reduced to 3.5% for sinkage and 4.2% for traction) and rut profiles, outperforming lab-derived values. This framework highlights the value of field-calibrated optimization for sustainable agriculture, offering a cost-effective alternative to field trials for designing low-compaction equipment and reducing yield losses from soil degradation. While sandy loam soil at 0.4% moisture content was used in this study, future extensions to different soil types with varied moisture are recommended. Full article

This study presents nanofractionation analytics coupled with in vivo profiling of zebrafish embryo paralysis and lethality in response to toxins in cone snail venoms. The focus of this study is on the development of this approach using venoms of Conus marmoreus, Conus ebraeus, and Conus bandanus. In brief, cone snail venoms were separated using reversed-phase chromatography following high-resolution nanofractionation on microplates with parallel mass spectrometry, enabled via a post-column flow split. All collected fractions were dried overnight, followed by assays on zebrafish embryos. For the paralysis assessment, we monitored swimming behavior and swimming distance and found that exposure to cone snail toxins led to paralysis and decreased movement and swim distance. To correlate the masses of eluted toxins with their paralyzing effects and potency, we compared the fractionation retention time versus normalized swimming distance. This allowed identification of the masses of toxins with paralyzing bioactivity, which were predominantly conopeptides. To assess lethality, zebrafish embryos were exposed to fractionated toxins for 24 h, after which they were inspected. The lethal doses and correlated toxins were identified by comparing retention times of fractionation versus the lethal dose values calculated for each fraction. We found that the most lethal venom was from C. bandanus, displaying the largest number of lethal peptides, followed by C. marmoreus and C. ebraeus. On the other hand, the most paralytic venom was from C. ebraeus, presenting a higher number of peptides with non-lethal paralytic effects, followed by C. bandanus and C. marmoreus. This study provides a pipeline to rapidly identify paralytic and lethal cone snail venom toxins using the zebrafish embryo model. Full article

NAC transcription factors are key regulators involved in diverse cellular processes, stress responses, and developmental pathways in plants. However, their roles in female cone development of Torreya grandis, a representative gymnosperm species, remain largely unexplored. In this study, we performed a comprehensive identification and analysis of NAC transcription factors in T. grandis to investigate their potential functions in female cone development. A total of 82 TgNAC members containing conserved NAM domains were identified, distributed unevenly across 11 chromosomes. Phylogenetic analysis with Arabidopsis NACs classified them into 15 groups, with TgNACs represented in 10 groups and showing a notable enrichment in the TERN clade on chromosome 2. Promoter cis-element analysis revealed correlations between regulatory elements and expression patterns. Tissue-specific expression profiling indicated clear functional specialization, with some TgNACs showing no detectable expression in the examined tissues. During female cone development, several TgNACs were highly expressed in the early stages, whereas TgNAC72, TgNAC76 and TgNAC82 were upregulated during the latter stages. Among these, TgNAC72 exhibited the highest overall expression level. Subcellular localization confirmed TgNAC72 is localized in the nucleus. Dual-luciferase assays further demonstrated that TgNAC72 activates the TgBGLU13 promoter, suggesting its role in starch and sucrose metabolism. Collectively, these findings provide novel insights into the regulatory involvement of TgNACs in reproductive organ development. Full article

Background/Objectives: Forensic dental determination plays a central role in human identification, age estimation, and trauma analysis in medico-legal contexts. Traditional approaches—including clinical examination, odontometric analysis, and radiographic comparison—remain essential but are constrained by examiner subjectivity, population variability, and reduced applicability in fragmented or degraded remains. Recent advances in cone-beam computed tomography (CBCT), three-dimensional surface scanning, intraoral imaging, and artificial intelligence (AI) offer promising opportunities to enhance accuracy, reproducibility, and integration with multidisciplinary forensic evidence. The aim of this review is to synthesize conventional and emerging approaches in forensic odontology, critically evaluate their strengths and limitations, and highlight areas requiring validation. Methods: A structured literature search was performed in PubMed, Scopus, Web of Science, and Google Scholar for studies published between 2015 and 2025. Search terms combined forensic odontology, dental identification, CBCT, 3D scanning, intraoral imaging, and AI methodologies. From 108 records identified, 81 peer-reviewed articles met eligibility criteria and were included for analysis. Results: Digital methods such as CBCT, 3D scanning, and intraoral imaging demonstrated improved diagnostic consistency compared with conventional techniques. AI-driven tools—including automated age and sex estimation, bite mark analysis, and restorative pattern recognition—showed potential to enhance objectivity and efficiency, particularly in disaster victim identification. Persistent challenges include methodological heterogeneity, limited dataset diversity, ethical concerns, and issues of legal admissibility. Conclusions: Digital and AI-based approaches should complement, not replace, the expertise of forensic odontologists. Standardization, validation across diverse populations, ethical safeguards, and supportive legal frameworks are necessary to ensure global reliability and medico-legal applicability. Full article

Hepatocellular carcinoma (HCC) is a hypervascular malignancy commonly treated with transarterial chemoembolization (TACE), in which success relies on the accurate identification and embolization of tumor feeding arteries while sparing the nontumorous liver parenchyma. This review introduces the concept of selective angiographic roadmap analysis (SARA), a systematic and stepwise approach to evaluating hepatic arterial supply in HCC, with the aim of standardizing angiographic planning and improving TACE outcomes. SARA emphasizes recognition of typical and variant hepatic arterial anatomy, systematic identification of accessory and extrahepatic feeders, and integration with intraprocedural cone-beam computed tomography (CBCT) to enhance feeder detection and reduce nontarget embolization. Although primarily applied in TACE, the principles of SARA are equally relevant to transarterial radioembolization (TARE) where precise arterial mapping is critical. Embolization strategies are discussed across different levels of selectivity, from lobar to superselective techniques. The complementary role of advanced imaging modalities, such as CT angiography (CTA), MR angiography (MRA), and artificial intelligence-assisted vessel tracking, is also explored. Adopting the SARA framework in conjunction with these technologies may improve technical success and tumor control and preserve liver function in patients undergoing intra-arterial therapies. Full article