Search Results (28,806)

Background/Objectives: This study assessed the long-term prognostic implications of newly developed left bundle branch block (LBBB) in patients with ST-elevation myocardial infarction (STEMI) and a single coronary lesion, following primary percutaneous coronary intervention (PCI). Methods: Among 3526 patients admitted with acute myocardial infarction between January 2011 and December 2013, 42 were identified with STEMI, a single coronary lesion, and newly diagnosed LBBB. A control group of 42 randomly selected STEMI patients without LBBB was also included. All participants were prospectively evaluated with a median follow-up duration of 9.4 years. Demographic, clinical, and laboratory data were analyzed to assess the impact of LBBB on long-term outcomes. Results: The baseline characteristics were similar between the groups. The STEMI with new LBBB group had significantly higher rates of new myocardial infarction, revascularization, and mortality, highlighting the severe prognostic implications and elevated risk for adverse outcomes compared to STEMI without LBBB. The multivariate Cox regression analysis demonstrated that the presence of LBBB (HR: 2.15, 95% CI: 1.28–3.62, p = 0.003), lower LVEF (HR: 1.45, 95% CI: 1.22–1.72, p < 0.001), and longer pain-to-admission time (HR: 1.32, 95% CI: 1.09–1.61, p = 0.008) were significant independent predictors of adverse outcomes. Conclusions: Newly acquired LBBB in STEMI patients is associated with poorer long-term outcomes. Early identification and management of factors such as reduced LVEF and timely hospital admission, specifically in patients with new-onset LBBB, can improve prognosis. Full article

Farm aerial survey layers can assist in unmanned farm operations, such as planning paths and early warnings. To address the inefficiencies and high costs associated with traditional layer construction, this study proposes a high-precision instance segmentation algorithm based on SparseInst. Considering the structural characteristics of farm elements, this study introduces a multi-scale attention module (MSA) that leverages the properties of atrous convolution to expand the sensory field. It enhances spatial and channel feature weights, effectively improving segmentation accuracy for large-scale and complex targets in the farm through three parallel dense connections. A bottom-up aggregation path is added to the feature pyramid fusion network, enhancing the model’s ability to perceive complex targets such as mechanized trails in farms. Coordinate attention blocks (CAs) are incorporated into the neck to capture richer contextual semantic information, enhancing farm aerial imagery scene recognition accuracy. To assess the proposed method, we compare it against existing mainstream object segmentation models, including the Mask R-CNN, Cascade–Mask, SOLOv2, and Condinst algorithms. The experimental results show that the improved model proposed in this study can be adapted to segment various complex targets in farms. The accuracy of the improved SparseInst model greatly exceeds that of Mask R-CNN and Cascade–Mask and is 10.8 and 12.8 percentage points better than the average accuracy of SOLOv2 and Condinst, respectively, with the smallest number of model parameters. The results show that the model can be used for real-time segmentation of targets under complex farm conditions. Full article

Alloyed high-carbon steels are materials primarily intended for components operating under conditions of intense tribological wear. The carbides present in the microstructure of these materials significantly contribute to improving the wear resistance of such alloys. However, changes in the morphology of these precipitates can considerably alter the wear rate, leading to a deterioration in the properties of the materials. Therefore, this study aims to analyze the influence of several factors on the tribological wear of alloyed high-carbon steel. The research included friction tests under various load conditions and different sliding paths. Additionally, the samples were subjected to heat treatment to change the morphology of the observed precipitates. The tribological tests were conducted in a block-on-ring configuration under dry friction conditions. The tribological tests were analyzed statistically using analysis of variance (ANOVA). The results of the statistical analysis indicated that the primary factor influencing the observed differences between the samples was the heat treatment time of the material. Additionally, there were no significant statistical differences when pressure and friction path were varied. These findings, in conjunction with the SEM studies, allowed for the evaluation of the wear mechanism. The results demonstrated that, within the adopted tribological system, no alterations in the wear mechanism were observed with changes in test parameters. The observed differences in wear properties between the samples were found to be related to their heat treatment. The heat treatment resulted in alterations to the particle size distribution, with the annealing of the material at an elevated temperature leading to the dissolution of finer particles within the material. An increase in the average diameter of the carbide present in the material was observed to improve the wear resistance of the alloy tested. Full article

This article focuses on zircon U-Pb isotope dating and a whole-rock elemental analysis of granodiorites, monzonitic granites, granodioritic porphyries, and alkali feldspar granites in the Yangmugang area of the Lesser Xing’an–Zhangguangcai Range. The zircon U-Pb isotope-dating results revealed that these granitic rocks formed during the late Early Jurassic period (182.9–177.2 Ma). Their geochemical characteristics and zircon saturation temperatures suggest that the granodiorites are moderately differentiated I-type granites and the monzonitic granite, granodioritic porphyries, and alkali feldspar granites are highly differentiated I-type granites. The degree of magma differentiation progressively increased from granodiorites to alkali feldspar granites. By combining the regional Nd and Hf isotope compositions, it was inferred that the magma source involved the melting of lower crustal material from the Mesoproterozoic to the Neoproterozoic eras. By integrating these findings with contemporaneous intrusive rock spatial variations, it was indicated that the late Early Jurassic granitoids in the Lesser Xing’an–Zhangguangcai Range formed within an extensional tectonic setting after the collision and closure of the Songnen–Zhangguangcai Range and Jiamusi blocks. Additionally, this study constrains the closure of the Mudanjiang Ocean to the late Early Jurassic period (177.2 Ma). Full article

This study evaluates the utilization of in vitro embryo production (IVEP) technology for the conservation and breeding of the Auliekol cattle breed, a primary beef breed in Kazakhstan facing population decline due to the cessation of breeding programs and the incursion of transboundary diseases. We assessed the effect of consecutive ovum pick-up (OPU) procedures on oocyte yield and embryo production in Auliekol and Aberdeen Angus cows. A total of 2232 and 3659 oocytes were aspirated from Auliekol and Aberdeen Angus donors, respectively, with significantly higher yields and embryo production observed in Aberdeen Angus cows. The application of a meiotic block using Butyrolactone I (BLI) and subsequent in vitro fertilization (IVF) protocols was employed, with embryo development monitored up to the morula/blastocyst stage. Results indicated that Auliekol cows exhibited lower oocyte recovery, cleavage, and blastocyst rates compared to Aberdeen Angus cows, likely due to genetic characteristics. Despite the challenges, IVEP presents a valuable tool for the preservation and future propagation of the Auliekol breed, highlighting the need for further research to enhance reproductive outcomes and conservation strategies. Full article

Diabetes greatly reduces the survival rates in breast cancer patients due to chemoresistance and metastasis. Reorganization of the cytoskeleton is crucial to cell migration and metastasis. Regulatory cytoskeletal protein kinases such as the Rho kinase (ROCK) and focal adhesion kinase (FAK) play a key role in cell mobility and have been shown to be affected in cancer. It is hypothesized that diabetes/high-glucose conditions alter the cytoskeletal structure and, thus, the elasticity of breast cancer cells through the ROCK and FAK pathway, which can cause rapid metastasis of cancer. The aim of the study was to investigate the role of potential mediators that affect the morphology of cancer cells in diabetes, thus leading to aggressive cancer. Breast cancer cells (MDA-MB-231 and MCF-7) were treated with 5 mM glucose (low glucose) or 25 mM glucose (high glucose) in the presence of Rho kinase inhibitor (Y-27632, 10 mM) or FAK inhibitor (10 mM). Cell morphology and elasticity were monitored using atomic force microscopy (AFM), and actin staining was performed by fluorescence microscopy. For comparative study, normal mammary breast epithelial cells (MCF-10A) were used. It was observed that high-glucose treatments modified the cytoskeleton of the cells, as observed through AFM and fluorescence microscopy, and significantly reduced the elasticity of the cells. Blocking the ROCK or FAK pathway diminished the high-glucose effects. These changes were more evident in the breast cancer cells as compared to the normal cells. This study improves the knowledge on the cytoarchitecture properties of diabetic breast cancer cells and provides potential pathways that can be targeted to prevent such effects. Full article

Moisture accelerates the degradation of asphalt properties, significantly impacting the service life of roads. Therefore, this study uses simplified viscoelastic continuous damage theory and employs frequency scanning, linear amplitude scanning, and fatigue–healing–fatigue tests with a dynamic shear rheometer. The objective is to investigate the effects of aging time, moisture conditions, and aging temperature on the fatigue and self-healing performance of SBS (Styrene–Butadiene–Styrene block copolymer)-modified asphalt, nano-SiO₂-modified asphalt, and nano-SiO₂/SBS composite modified asphalt in a moisture-rich environment. The results indicate that nano-SiO₂ powder enhances the low-temperature performance of modified asphalt, whereas the SBS modifier reduces temperature sensitivity and increases the recovery percentage after deformation. Compared to SBS-modified asphalt, the deformation resistance of nano-SiO₂/SBS composite modified asphalt has increased by about 30%, while nano-SiO₂-modified asphalt shows relatively poor deformation resistance. The fatigue performance of SBS-modified asphalt deteriorates under moisture, whereas the addition of nano-SiO₂ powder improves its fatigue life. Nano-SiO₂/SBS composite modified asphalt exhibits strong self-healing capabilities. Although self-healing can enhance the fatigue life of modified asphalt, moisture inhibits this improvement after self-healing. Full article

System modeling language (SysML) diagrams generated manually by system modelers can sometimes be prone to errors, which are time-consuming and introduce subjectivity. Natural language processing (NLP) techniques and tools to create SysML diagrams can aid in improving software and systems design processes. Though NLP effectively extracts and analyzes raw text data, such as text-based requirement documents, to assist in design specification, natural language, inherent complexity, and variability pose challenges in accurately interpreting the data. In this paper, we explore the integration of NLP with SysML to automate the generation of system models from input textual requirements. We propose a model generation framework leveraging Python and the spaCy NLP library to process text input and generate class/block definition diagrams using PlantUML for visual representation. The intent of this framework is to aid in reducing the manual effort in creating SysML v1.6 diagrams—class/block definition diagrams in this case. We evaluate the effectiveness of the framework using precision and recall measures. The contribution of this paper to the systems modeling domain is two-fold. First, a review and analysis of natural language processing techniques for the automated generation of SysML diagrams are provided. Second, a framework to automatically extract textual relationships tailored for generating a class diagram/block diagram that contains the classes/blocks, their relationships, methods, and attributes is presented. Full article

Epithelial-to-mesenchymal transition (EMT) is a complex cellular process that allows cells to change their phenotype from epithelial to mesenchymal-like. Type 3 EMT occurs during cancer progression. The aim of this study was to investigate the role of RNA-binding motif single-stranded interacting protein 3 (RBMS 3) in the process of EMT. To investigate the impact of RBMS 3 on EMT, we performed immunohistochemical (IHC) reactions on archived paraffin blocks of invasive ductal breast carcinoma (n = 449), allowing us to analyze the correlation in expression between RBMS 3 and common markers of EMT. The IHC results confirmed the association of RBMS 3 with EMT markers. Furthermore, we performed an in vitro study using cellular models of triple negative and HER-2-enriched breast cancer with the overexpression and silencing of RBMS 3. RT-qPCR and Western blot methods were used to detect changes at both the mRNA and protein levels. An invasion assay and confocal microscopy were used to study the migratory potential of cells depending on the RBMS 3 expression. The studies conducted suggest that RBMS 3 may potentially act as an EMT-promoting agent in the most aggressive subtype of breast cancer, triple negative breast cancer (TNBC), but as an EMT suppressor in the HER-2-enriched subtype. The results of this study indicate the complex role of RBMS 3 in regulating the EMT process and present it as a future potential target for personalized therapies and a diagnostic marker in breast cancer. Full article

Compressive sensing (CS) is a notable technique in signal processing, especially in multimedia, as it allows for simultaneous signal acquisition and dimensionality reduction. Recent advancements in deep learning (DL) have led to the creation of deep unfolding architectures, which overcome the inefficiency and subpar quality of traditional CS reconstruction methods. In this paper, we introduce a novel CS image reconstruction algorithm that leverages the strengths of the fast iterative shrinkage-thresholding algorithm (FISTA) and modern Transformer networks. To enhance computational efficiency, we employ a block-based sampling approach in the sampling module. By mapping FISTA’s iterative process onto neural networks in the reconstruction module, we address the hyperparameter challenges of traditional algorithms, thereby improving reconstruction efficiency. Moreover, the robust feature extraction capabilities of Transformer networks significantly enhance image reconstruction quality. Experimental results show that the FusionOpt-Net model surpasses other advanced methods on various public benchmark datasets. Full article

In this study, novel ergosterol peroxide (EP) derivatives were synthesized and evaluated to assess their antiproliferative activity against four human cancer cell lines (A549, HepG2, MCF-7, and MDA-MB-231). Compound 3g exhibited the most potent antiproliferative activity, with an IC₅₀ value of 3.20 µM against MDA-MB-231. This value was 5.4-fold higher than that of the parental EP. Bioassay optimization further identified 3g as a novel glutaminase 1 (GLS1) inhibitor (IC₅₀ = 3.77 µM). In MDA-MB-231 cells, 3g reduced the cellular glutamate levels by blocking the glutamine hydrolysis pathway, which triggered reactive oxygen species production and induced caspase-dependent apoptosis. Molecular docking indicated that 3g interacts with the reaction site of the variable binding pocket by forming multiple interactions with GLS1. In a mouse model of breast cancer, 3g showed remarkable therapeutic effects at a dose of 50 mg/kg, with no apparent toxicity. Based on these results, 3g could be further evaluated as a novel GLS1 inhibitor for triple-negative breast cancer (TNBC) therapy. Full article

To address the issue of missing near-surface air temperature data caused by the uneven distribution of ground meteorological observation stations, we propose a method for near-surface air temperature estimation based on an improved conditional generative adversarial network (CGAN) framework. Leveraging the all-weather coverage advantage of Fengyun meteorological satellites, Fengyun-4A (FY-4A) satellite remote sensing data are utilized as conditional guiding information for the CGAN, helping to direct and constrain the near-surface air temperature estimation process. In the proposed network model of the method based on the conditional generative adversarial network structure, the generator combining a self-attention mechanism and cascaded residual blocks is designed with U-Net as the backbone, which extracts implicit feature information and suppresses the irrelevant information in the Fengyun satellite data. Furthermore, a discriminator with multi-level and multi-scale spatial feature fusion is constructed to enhance the network’s perception of details and the global structure, enabling accurate air temperature estimation. The experimental results demonstrate that, compared with Attention U-Net, Pix2pix, and other deep learning models, the method presents significant improvements of 68.75% and 10.53%, respectively in the root mean square error (RMSE) and Pearson’s correlation coefficient (CC). These results indicate the superior performance of the proposed model for near-surface air temperature estimation. Full article

Araucaria angustifolia is a species known for its valuable wood and nuts, but it is threatened with extinction. The plantation of forests for genetic resource conservation is a complementary strategy designed to reduce the species’ genetic variability loss. This study aimed to evaluate the technical and economic viability of A. angustifolia for genetic conservation through use. The analyzed provenance and progeny trial was established in 1982 in Itapeva, Brazil. It was structured using a compact family blocks design with 110 open-pollinated progenies from five natural populations, three replicates, ten plants per subplot, and 3.0 m × 2.0 m spacing. After 33 years, the trial was evaluated for total height, diameter at breast height, wood volume, and survival. The variance components and genetic parameter estimates were performed using Restricted Maximum Likelihood/Best Linear Unbiased Prediction methods (REML/BLUP) methods with the Selegen software (version 2014). The production and management scenarios were obtained using the SisAraucaria software (version 2003). Sensitivity analysis and economic parameter estimates were obtained through various economic evaluation methods using the Planin software (version 1995). In general, the genetic parameters indicated that the population has enough variability for both conservation and breeding purposes, suggesting technical viability for the establishment of a seed orchard. The economic parameters indicated that the commercialization of wood and araucaria nuts proved to be more profitable than wood production by itself. In conclusion, araucaria genetic conservation through use is a technically and economically viable ex situ conservation strategy. Full article

Modern masonry systems are generally built with hollow clay bricks with high thermal insulating properties, fulfilling the latest sustainability and environmental criteria for constructions. Despite the growing use of sustainable masonries in seismic-prone countries, there is a notable lack of experimental and numerical data on their structural behavior under lateral in-plane loads. The present study investigates the in-plane shear behavior of load-bearing masonry walls with thin bed joints and thermal insulating hollow clay blocks. Shear-compression tests were performed on three specimens to obtain information about their shear strength, displacement capacity and failure modes. The experimental characterization was supplemented by three shear tests on triplets, along with flexural and compression tests on the mortar for the thin joints. Furthermore, two Finite Element (FE) models were built to simulate the shear-compression tests, considering different constitutive laws and brick-to-brick contact types. The numerical simulations were able to describe both the shear failure modes and the shear strength values. The results showed that the experimental shear strength was 53% higher than the one obtained through Eurocode 6. The maximum shear load was found to be up to 75% greater compared to similar masonry specimens from the literature. These findings contribute to a better understanding of the potential structural applications of sustainable hollow clay block masonry in earthquake-prone areas. Full article

The artificial potential field algorithm has been widely applied to mobile robots and robotic arms due to its advantage of enabling simple and efficient path planning in unknown environments. However, solving the local minimum problem is an essential task and is still being studied. Among current methods, the technique using the virtual hill concept is reliable and suitable for real-time path planning because it does not create a new local minimum and provides lower complexity. However, in the previous study, the shape of the obstacles was not considered in determining the robot’s direction at the moment it is trapped in a local minimum. For this reason, longer or blocked paths are sometimes selected. In this study, we propose an enhanced virtual hill algorithm to reduce errors in selecting the driving direction and improve the efficiency of robot movemenIt. In the local minimum area, a dead-end algorithm is also proposed that allows the robot to return without entering deeply when it encounters a dead end. Full article