Search Results (11,615)

Speckle noise is a granular interference that degrades image quality in coherent imaging systems, including underwater sonar, Synthetic Aperture Radar (SAR), and medical ultrasound. This study aims to enhance speckle noise reduction through advanced deep learning techniques. We introduce the Deep Gradient-Guidance Network (DGGNet), which features an architecture comprising one encoder and two decoders—one dedicated to image recovery and the other to gradient preservation. Our approach integrates a gradient map and fractional-order total variation into the loss function to guide training. The gradient map provides structural guidance for edge preservation and directs the denoising branch to focus on sharp regions, thereby preventing over-smoothing. The fractional-order total variation mitigates detail ambiguity and excessive smoothing, ensuring rich textures and detailed information are retained. Extensive experiments yield an average Peak Signal-to-Noise Ratio (PSNR) of 31.52 dB and a Structural Similarity Index (SSIM) of 0.863 across various benchmark datasets, including McMaster, Kodak24, BSD68, Set12, and Urban100. DGGNet outperforms existing methods, such as RIDNet, which achieved a PSNR of 31.42 dB and an SSIM of 0.853, thereby establishing new benchmarks in speckle noise reduction. Full article

Objectives: The goal of this study is to document outcomes of ablation for high-risk accessory pathways in paediatrics using 3D mapping systems with minimal to zero fluoroscopy. Methods: It is a cross-sectional, multicentre study, conducted between 2013 and 2023, and involving four different centres in Hungary, Croatia, Kuwait, and Slovenia. Results: A total of 128 procedures were performed on 111 patients. The cohort included 57.8% anteroseptal (AS) pathways and 42.2% midseptal (MS) pathways. The mean follow-up time was 2.0 ± 2.1 years. Cryoablation was used in 72.7% of the cases, and radiofrequency ablation was used in 27.3%. The EnSite Precision™ Cardiac Mapping System was the predominant system used. The overall acute success rate was 89.1%, with recurrence rates at 17.2% with similar results regardless of the type of energy used. The success rate was not significantly different between AS and MS substrates. The age and weight of the patient had no bearing on the outcomes (median age and weight were 13 years and 52 kg, respectively). The complications rate was at 4.69% and included transient AV block (three patients), hematoma (one patient), right bundle branch block (one patient), and possible permanent complete AV block (one patient). Fluoroscopy was utilized in 18 cases, with a fluoroscopy time mean of 3 min and 45 s. Conclusions: MS and AS AP in paediatric patients can be treated effectively with either RF or cryoablation and with a low dose of radiation using 3D mapping systems, with excellent acute success rates and low complication rates. Full article

There is an increasing understanding that some mitral valve pathologies have developmental origins. The time course of valvulogenesis varies by animal model; in cattle, the branched chordae tendineae architecture becomes fully developed at full term. The mechanism by which chordae tendineae bifurcate during fetal development remains unknown. The current study presents a detailed description of bovine chordae tendineae formation and bifurcation during fetal development. Analysis of Movat Pentachrome-stained histological sections of the developing mitral valve apparatus was accompanied by micro-CT imaging. TEM imaging of chordae branches and common trunks allowed the measurement of collagen fibril diameter distributions. We observed a proteoglycan-rich “transition zone” at the junction between the fetal mitral valve anterior leaflet and chordae tendineae with “perforations” lined by MMP1/2 and Ki-67 expressing endothelial cells. This region also contained clusters of proliferating endothelial cells within the bulk of the tissue. We hypothesize this zone marks a region where chordae tendineae bifurcate during fetal development. In particular, perforations created by localized MMP activity serve as a site for the initiation of a “split” of a single chordae attachment into two. This is supported by TEM results that suggest a similar population of collagen fibrils runs from the branches into a common trunk. A clear understanding of normal mitral valvulogenesis and its signaling mechanisms will be crucial in developing therapeutics and/or tissue-engineered valve replacements. Full article

This study addresses the challenges of traditional date palm harvesting, which is often labor-intensive and hazardous, by introducing an innovative solution utilizing multirotor flying vehicles (MRFVs). Unlike conventional methods such as hydraulic lifts and ground-based robotic manipulators, the proposed system integrates a quadrotor equipped with a winch and a suspended robotic arm with a precision saw. Controlled remotely via a mobile application, the quadrotor navigates to targeted branches on the date palm tree, where the robotic arm, guided by live video feedback from integrated cameras, accurately severs the branches. Extensive testing in a controlled environment demonstrates the system’s potential to significantly improve harvesting efficiency, safety, and cost-effectiveness. This approach offers a promising alternative to traditional harvesting methods, providing a scalable solution for date palm cultivation, particularly in regions with large-scale plantations. This work marks a significant advancement in the field of agricultural automation, offering a safer, more efficient method for harvesting date palms and contributing to the growing body of knowledge in automated farming technologies. Full article

Transformer-based methods have demonstrated impressive performance in image super-resolution tasks. However, when applied to large-scale Earth observation images, the existing transformers encounter two significant challenges: (1) insufficient consideration of spatial correlation between adjacent ground objects; and (2) performance bottlenecks due to the underutilization of the upsample module. To address these issues, we propose a novel distance-enhanced strip attention transformer (DESAT). The DESAT integrates distance priors, easily obtainable from remote sensing images, into the strip window self-attention mechanism to capture spatial correlations more effectively. To further enhance the transfer of deep features into high-resolution outputs, we designed an attention-enhanced upsample block, which combines the pixel shuffle layer with an attention-based upsample branch implemented through the overlapping window self-attention mechanism. Additionally, to better simulate real-world scenarios, we constructed a new cross-sensor super-resolution dataset using Gaofen-6 satellite imagery. Extensive experiments on both simulated and real-world remote sensing datasets demonstrate that the DESAT outperforms state-of-the-art models by up to 1.17 dB along with superior qualitative results. Furthermore, the DESAT achieves more competitive performance in real-world tasks, effectively balancing spatial detail reconstruction and spectral transform, making it highly suitable for practical remote sensing super-resolution applications. Full article

Bacteroides fragilis is a new generation of probiotics, and its probiotic effects on humans and some animals have been verified. However, research on B. fragilis in cattle is still lacking. In this study, 24 stool samples were collected from two large-scale cattle farms in Wuzhong, Ningxia, including 12 diarrheal and 12 normal stools. A non-toxigenic Bacteroides fragilis (NTBF) was isolated and identified by 16S rRNA high-throughput sequencing and named BF-1153; genome composition and genome functional analyses were carried out to reflect the biological characteristics of the BF-1153 strain. A cluster analysis of BF-1153 was performed using Mega X to explore its genetic relationship. In addition, Cell Counting Kit-8 (CCK8) was used to determine the toxic effects of the strain on human ileocecal colorectal adenocarcinoma cell line cells (HCT-8), Madin-Darby bovine kidney cells (MDBK), and intestinal porcine epithelial cells (IPECs). The results showed that BF-1153 conformed to the biological characteristics of B. fragilis. BF-1153 had no toxic effects on HCT-8, MDBK, and IPEC. Animal experiments have shown that BF-1153 has no toxic effects on healthy SPF Kunming mice. Notably, the supernatant of BF-1153 enhanced cell activity and promoted cell growth in all three cell lines. At the same time, a cluster analysis of the isolated strains showed that the BF-1153 strain belonged to the same branch as the B. fragilis strain 23212, and B. fragilis strain 22998. The results of the animal experiments showed that BF-1153 had a certain preventive effect on diarrhea symptoms in SPF Kunming mice caused by a bovine rotavirus (BRV). In summary, the strain BF-1153 isolated in this experiment is NTBF, which has no toxic effect on MDBK, HCT-8, and IPEC, and has obvious cell growth-promoting effects, especially on MDBK. BF-1153 promotes the growth and development of SPF Kunming mice when compared with the control group. At the same time, BF-1153 alleviated the diarrhea symptoms caused by BRV in SPF Kunming mice. Therefore, BF-1153 has the potential to be a probiotic for cattle. Full article

The Gaia DR3 GSP-spec/TESS (GST) catalog combines asteroseismic data from NASA’s TESS mission with spectroscopic data from ESA’s Gaia mission, and contains about 116,000 Red Clump and Red Giant Branch stars, surpassing previous datasets in size and precision. The Bayesian tool PARAM is used to estimate stellar ages using MESA models for, currently, 30,297 stars. This GST catalog, which includes kinematics and chemical information, is adopted for studying the Milky Way’s structure and evolution, in particular its thin and thick disk components. Full article

In coal mining operations, methane explosions constitute a severe safety risk, endangering miners’ lives and causing substantial economic losses, which, in turn, weaken the production efficiency and economic benefits of the mining industry and hinder the sustainable development of the industry. To address this challenge, this article explores the application of decoupling network-based methods in methane explosion simulation, aiming to optimize underground mine ventilation system design through scientific means and enhance safety protection for miners. We used the one-dimensional finite difference method (FDM) software Flowmaster to simulate the propagation process of shock waves from a gas explosion source in complex underground tunnel networks, covering a wide range of scenarios from laboratory-scale parallel network samples to full-scale experimental mine settings. During the simulation, we traced the pressure loss in the propagation of the shock wave in detail, taking into account the effects of pipeline friction, shock losses caused by bends and obstacles, T-joint branching connections, and cross-sectional changes. The results of these two case studies were presented, leading to the following insights: (1) geometric variations within airway networks exert a relatively minor influence on overpressure; (2) the positioning of the vent positively contributes to attenuation effects; (3) rarefaction waves propagate over greater distances than compression waves; and (4) oscillatory phenomena were detected in the conduits connecting to the surface. This research introduces a computationally efficient method for predicting methane explosions in complex underground ventilation networks, offering reasonable engineering accuracy. These research results provide valuable references for the safe design of underground mine ventilation systems, which can help to create a safer and more efficient mining environment and effectively protect the lives of miners. Full article

The genus Borodinellopsis is extremely rare and is the subject of limited research and reports. It currently comprises only two species, Borodinellopsis texensis and Borodinellopsis oleifera, which differ from other globose algae due to their unique centrally radiating chloroplasts. In this study, we describe a new specimen in detail based on morphological data and phylogenetic analysis and identify it as B. insignis. B. insignis and B. texensis exhibit a high degree of similarity, likely due to their shared characteristics of centrally radiating chloroplasts and flagella that are significantly longer than the cell body. A phylogenetic tree constructed based on the 18S rDNA sequence indicates that B. insignis and B. texensis form a branch that is distinct from other genera, such as Tetracystis, Spongiococcum, and Chlorococcum. Phylogenetic analysis of the ITS sequence, the rbcL gene, and the tufA gene reveals that B. insignis is significantly different from B. texensis, in that it has oil droplets, smaller vegetative cells and zoospores, and distinct habitats. It is also different from B.oleifera as it has smaller vegetative cells and zoospores, turns red after cultivation, has longer flagella, and resides in different habitats. The chloroplast genomes of B. texensis and B. insignis further show significant differences, with the phylogenetic tree constructed based on the analysis of 49 protein-coding genes forming two separate branches. The collinearity of the chloroplast genomes in B. texensis and B. insignis is poor, with 15 out of the 31 homologous modules displaying inversions and complex rearrangements. Given these differences, we classify this alga as a new species and named it Borodinellopsis insignis sp. nov. Full article

Background: Graphene Oxide (GO) has shown great potential in biomedical applications for cancer therapeutics. The biosafety and stability issues of GO in biological media have been addressed by functionalization with polyethylene glycol (PEG). Methods: In this work, carboxylated, nanosized GO (nCGO) was evaluated as a potential carrier of paclitaxel (PCT). The effect of PEG characteristics on particle size and surface charge, colloidal stability, drug, and release, and the hemolytic potential of nCGO, was investigated. Optimum PEG-nCGO/PCT formulations based on the above properties were evaluated for their anticancer activity (cytotoxicity and apoptosis induction) in the A549 lung cancer cell line. Results: An increase in the length of linear PEG chains and the use of branched (4-arm) instead of linear PEG resulted in a decrease in hydrodynamic diameter and an increase in ζ potential of the pegylated nCGO particles. Pegylated nCGO exhibited high colloidal stability in phosphate-buffered saline and in cell culture media and low hemolytic effect, even at a relatively high concentration of 1 mg/mL. The molecular weight of PEG and branching adversely affected PCT loading. An increased rate of PCT release at an acidic pH of 6.0 compared to the physiological pH of 7.4 was observed with all types of pegylated nCGO/PCT. Pegylated nCGO exhibited lower cytotoxicity and apoptotic activity than non-pegylated nCGO. Cellular uptake of pegylated nCGO increased with incubation time with cells leading to increased cytotoxicity of PEG-nCGO/PCT with incubation time, which became higher than that of free PCT at 24 and 48 h of incubation. Conclusions: The increased biocompatibility of the pegylated nCGO and the enhanced anticancer activity of PEG-nCGO/PCT compared to free PCT are desirable properties with regard to the potential clinical application of PEG-nCGO/PCT as an anticancer nanomedicine. Full article

Low back pain (LBP) affects over 60% of individuals in their lifetime and is a leading cause of disability and increased healthcare expenditure. Facet joint pain (FJP) occurs in 27% to 40% of LBP patients but is often overlooked or misdiagnosed. Additionally, there is no clear correlation between the clinical examination, radiological findings, and clinical presentation, complicating the diagnosis and treatment of FJP. This narrative review aims to provide an overview of the literature regarding facet joint pain and discusses the utility of medial branch blocks (MBBs) and intra-articular (IA) injections as diagnostic and therapeutic tools prior to radiofrequency ablation (RFA). RFA is considered the gold standard for managing FJP, employing techniques that include precise needle placement and stimulation parameters to disrupt pain signals. Promising alternatives such as cooled RFA and cryodenervation require further research on their long-term efficacy and safety. Endoscopic denervation and multifidus stimulation are emerging therapies that may benefit chronic LBP patients, but additional research is needed to establish their effectiveness. When conservative management fails, RFA provides significant and lasting relief in well-selected patients and has a favourable safety profile. The current literature does not support surgical interventions for FJP management. Full article

This paper reports the development of a highly crosslinked hyper-branched polyglycerol (HPG) polymer bound to elastin-like proteins (ELPs) to create a membrane that undergoes a distinct closed-to-open permeation transition at 32 °C. The crosslinked HPG forms a robust, mesoporous structure (150–300 nm pores), suitable for selective filtration. The membranes were characterized by FTIR, UV–visible spectroscopy, SEM, and AFM, revealing their structural and morphological properties. Incorporating a synthetic polypeptide introduced thermo-responsive behavior, with the membrane transitioning from impermeable to permeable above the lower critical solution temperature (LCST) of 32 °C. Permeation studies using crystal violet (CV) demonstrated selective transport, where CV permeated only above 32 °C, while water permeated at all temperatures. This hybrid HPG-ELP membrane system, acting as a molecular switch, offers potential for applications in drug delivery, bioseparations, and smart filtration systems, where permeability can be controlled by temperature. Full article

The transition in medical image segmentation from fine-grained to coarse-grained annotation methods, notably scribble annotation, offers a practical and efficient preparation for deep learning applications. However, these methods often compromise segmentation precision and result in irregular contours. This study targets the enhancement of scribble-supervised segmentation to match the accuracy of fine-grained annotation. Capitalizing on the consistency of target shapes across unpaired datasets, this study introduces a shape-aware scribble-supervised learning framework (MaskMixAdv) addressing two critical tasks: (1) Pseudo label generation, where a mixup-based masking strategy enables image-level and feature-level data augmentation to enrich coarse-grained scribbles annotations. A dual-branch siamese network is proposed to generate fine-grained pseudo labels. (2) Pseudo label optimization, where a CNN-based discriminator is proposed to refine pseudo label contours by distinguishing them from external unpaired masks during model fine-tuning. MaskMixAdv works under constrained annotation conditions as a label-efficient learning approach for medical image segmentation. A case study on public cardiac MRI datasets demonstrated that the proposed MaskMixAdv outperformed the state-of-the-art methods and narrowed the performance gap between scribble-supervised and mask-supervised segmentation. This innovation cuts annotation time by at least 95%, with only a minor impact on Dice performance, specifically a 2.6% reduction. The experimental outcomes indicate that employing efficient and cost-effective scribble annotation can achieve high segmentation accuracy, significantly reducing the typical requirement for fine-grained annotations. Full article

Semantic segmentation of remote sensing images is a fundamental task in computer vision, holding substantial relevance in applications such as land cover surveys, environmental protection, and urban building planning. In recent years, multi-modal fusion-based models have garnered considerable attention, exhibiting superior segmentation performance when compared with traditional single-modal techniques. Nonetheless, the majority of these multi-modal models, which rely on Convolutional Neural Networks (CNNs) or Vision Transformers (ViTs) for feature fusion, face limitations in terms of remote modeling capabilities or computational complexity. This paper presents a novel Mamba-based multi-modal fusion network called MFMamba for semantic segmentation of remote sensing images. Specifically, the network employs a dual-branch encoding structure, consisting of a CNN-based main encoder for extracting local features from high-resolution remote sensing images (HRRSIs) and of a Mamba-based auxiliary encoder for capturing global features on its corresponding digital surface model (DSM). To capitalize on the distinct attributes of the multi-modal remote sensing data from both branches, a feature fusion block (FFB) is designed to synergistically enhance and integrate the features extracted from the dual-branch structure at each stage. Extensive experiments on the Vaihingen and the Potsdam datasets have verified the effectiveness and superiority of MFMamba in semantic segmentation of remote sensing images. Compared with state-of-the-art methods, MFMamba achieves higher overall accuracy (OA) and a higher mean F1 score (mF1) and mean intersection over union (mIoU), while maintaining low computational complexity. Full article

Underwater images are important for underwater vision tasks, yet their quality often degrades during imaging, promoting the generation of Underwater Image Enhancement (UIE) algorithms. This paper proposes a Dual-Channel Convolutional Neural Network (DC-CNN)-based quality assessment method to evaluate the performance of different UIE algorithms. Specifically, inspired by the intrinsic image decomposition, the enhanced underwater image is decomposed into reflectance with color information and illumination with texture information based on the Retinex theory. Afterward, we design a DC-CNN with two branches to learn color and texture features from reflectance and illumination, respectively, reflecting the distortion characteristics of enhanced underwater images. To integrate the learned features, a feature fusion module and attention mechanism are conducted to align efficiently and reasonably with human visual perception characteristics. Finally, a quality regression module is used to establish the mapping relationship between the extracted features and quality scores. Experimental results on two public enhanced underwater image datasets (i.e., UIQE and SAUD) show that the proposed DC-CNN method outperforms a variety of the existing quality assessment methods. Full article