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A MEMS seismometer respiratory monitor for work of breathing assessment and adventitious lung sounds detection via deep learning
Influence of 3D printing angles on the accuracy of indirect adhesion transfer models: an in vitro study
A high-performance extracellular field potential analyzer for iPSC-derived cardiomyocytes
Activation of PI3K-AKT pathway prevents steroid-induced osteonecrosis of the femoral head via inhibiting Cuproptosis
VM-UNet++ research on crack image segmentation based on improved VM-UNet
Abstract Cracks are common defects in physical structures, and if not detected and addressed in a timely manner, they can pose a severe threat to the overall safety of the structure. In recent years, with advancements in deep learning, particularly the widespread use of Convolutional Neural Networks (CNNs) and Transformers, significant breakthroughs have been made in the field of crack detection. However, CNNs still face limitations in capturing global information due to their local receptive fields when processing images. On the other hand, while Transformers are powerful in handling long-range dependencies, their high computational cost remains a significant challenge. To effectively address these issues, this paper proposes an innovative modification to the VM-UNet model. This modified model strategically integrates the strengths of the Mamba architecture and UNet to significantly improve the accuracy of crack segmentation. In this study, we optimized the original VM-UNet architecture to better meet the practical needs of crack segmentation tasks. Through comparative experiments on the Crack500 and Ozgenel public datasets, the results clearly demonstrate that the improved VM-UNet achieves significant advancements in segmentation accuracy. Compared to the original VM-UNet and other state-of-the-art models, VM-UNet++ shows a 3% improvement in mDS and a 4.6–6.2% increase in mIoU. These results fully validate the effectiveness of our improvement strategy. Additionally, VM-UNet++ demonstrates lower parameter count and floating-point operations, while maintaining a relatively satisfactory inference speed. These improvements make VM-UNet++ advantageous for practical applications.
The effect of norethisterone acetate on the uterine telocytes, immune cells and progesterone receptors in albino rats
Abstract This study is the first attempt to examine the effects of NETA on immune cells and telocytes. The results of this study form an important knowledge base for the development of new information on the mechanism of contraceptive action of NETA in the uterus. Norethisterone acetate (NETA) is a synthetic progestogen medication commonly utilized in birth control pills, menopausal hormone therapy, and for curing abnormal uterine bleeding and endometriosis. Furthermore NETA has many beneficial uses in veterinary medicine as control and synchronization of estrous cycle. The impact of NETA on the endometrial stromal cells (ESCs), telocytes, and uterine immune cells is not well understood. Therefore, this study focuses on assessing changes in uterine immune cells, ESCs, and telocytes following exposure to NETA in albino rats. To achieve this objective, fourteen adult female albino rats were randomly divided into two groups: a control group and an NETA-treated group. Rats in the control group received daily pelleted food, water, and were oral administered of 2 ml distilled water. In contrast, rats in the NETA-treated group received daily pelleted food, water, and were orally administered 20 µg of NETA dissolved in 2 ml distilled water. The experiment spanned three weeks. The findings of this study revealed that NETA usage increases the infiltration and activity of immune cells (eosinophils, neutrophils, macrophages, lymphocytes, and mast cells). Furthermore, it enhances the vesicular activity of uterine telocytes and their communication with various immune cells. NETA also influences decidualization and the immunoexpression of progesterone receptors in uterine epithelial and immune cells. This study concludes that the primary mechanism by which NETA controls pregnancy is through decidual (pregnancy-like) effects or improper decidualization, which inhibits fertilization and implantation respectively. Our research provides evidence of the contraceptive mechanism of NETA from an immunological perspective in an animal model.
Towards enhanced Sargassum monitoring in the Caribbean Sea
Abstract Monitoring Sargassum along the coasts of the Greater Caribbean has become essential due to recurrent blooms since 2018, which bring severe ecological, economic, and social impacts that accumulate yearly. Developing an advanced, monitoring platform would enable affected countries to make informed decisions, manage critical zones, and mitigate negative impacts on coastal ecosystems, economies, and public health. In this work, we present the LANOT platform, a new tool for monitoring Sargassum across the Mexican Caribbean and neighboring regions, including Belize, Guatemala, and parts of Honduras. Utilizing Sentinel-2 and Landsat-8/9 satellite imagery, the platform provides data updated every five days and includes interactive features for selecting layers, querying Sargassum imagery by date or raft area, measuring regions, and downloading files in GeoTIFF, GeoJSON, and PNG formats. These interactive tools allow users to create and download custom files for use in their Sargassum management plans. Although the platform faces inherent limitations of satellite remote sensing, it represents a key advancement in monitoring efforts, marking a milestone for Sargassum observation in the region and supporting regional ecosystem management and research.
The role of recharge/discharge and hydraulic conductivity in gravitational groundwater flow systems
Coal dust particles can upregulate the expression of NLRP3 inflammasome components in rat alveolar macrophages through phagocytosis
Metabolomic profile of dromedary camel follicular fluid during the breeding and non-breeding seasons
Abstract Understanding the metabolic profile within the follicular microenvironment is crucial for optimizing reproductive efficiency in camels. In this study, we examined the metabolomic profile of camel follicular fluid (FF) during the breeding (n = 10) and non-breeding seasons (n = 10). Gas chromatography-mass spectrometry (GC-MS) was utilized to describe the metabolites present in follicular fluid samples. The results found considerable differences in the metabolomics profiles between the breeding and non-breeding seasons. Hexadecenoic acid, galactose and glucose levels were significantly (P < 0.05) higher in camel FF during the breeding season, while 9-octadecenamide, oleonitrile, glycine, octadecanamide, cholesterol, and propanoic acid were higher (P < 0.05) in FF during the non-breeding season. Multivariante analyses pointed to those 9 metabolites, and univariate analysis showed hexadecenoic acid, galactose, glucose, and oleanitril were the most significant ones in camel follicular fluid collected during both breeding and non-breeding seasons. The univariate and multivariate analyses showed an increase in the levels of hexadecanoic acid, galactose, glucose, and a depletion in the level of oleanitrile in the breeding season compared to the non-breeding season. The ROC curve and statistical analysis showed that hexadecanoic acid, galactose, and oleanitril with AUC = 1 were promising to be seasonal biomarkers of fertility in female camels. In conclusion, the metabolomic analysis of camel FF reveals distinct changes in metabolite levels between breeding and non-breeding seasons, reflecting adaptive metabolic responses to support reproductive processes. These results offer valuable insights into the reproductive physiology of camels and offer practical implications for potential biomarkers and assessing the reproductive status in camels, which can be utilized in reproductive management and conservation efforts in these valuable animal species.
Evaluating logistic regression and geographically weighted logistic regression models for predicting orange-fleshed sweet potato adoption intention in Benin
Insights into the enhanced photocatalytic degradation of congo red using advanced BaDyxFe12−xO19 catalytic hexamaterials
Characteristics mode analysis and excitation of orthogonal modes on a single substrate for wideband IoT applications in the millimeter wave band
Abstract This paper presents the design of a circularly polarized millimeter-wave (mm-wave) metasurface (MTS) antenna. The Characteristics Modes Analysis (CMA) is employed to examine various modes within the unit-cell design of the proposed metasurface. Based on a thorough analysis, two orthogonal TM modes with a broadside radiation pattern were identified. These modes were then simultaneously excited on a single substrate using simple coplanar waveguide (CPW) magnetic dipoles resulting in circular polarization (CP). Further, it has been demonstrated that the sense of polarization can be easily reconfigured for realizing multiple-input-multiple-output (MIMO) antenna with polarization diversity. Both the single MTS antenna and the MIMO design are characterized numerically and experimentally. The simulated and measured results show that impedance bandwidth (S11 ≤ − 10 dB) of the antenna is from 25 to 30.8 GHz. The axial ratio (AR) below 3 dB is from 26 to 31 GHz with a stable broadside radiation pattern. The proposed design features a low profile and simple geometry which is extremely appropriate for applications in the mm-wave band.