Search Results (42)

Background: Magnetic resonance imaging (MRI) plays a crucial role in staging and preoperative evaluation in osteosarcoma patient. Fewer studies have focused on 2-year survival, which reflects tumour aggressiveness and early disease progression. This study examines the association between MRI characteristics and 2-year survival outcomes in osteosarcoma to better understand the imaging characteristic of high-risk patients. Methods: A retrospective case–control study was conducted at a tertiary university hospital. Patients diagnosed with osteosarcoma between 2010 and 2022 were included if they had a pre-treatment MRI and at least 2 years of follow-up. MRI scans were reviewed by two blinded radiologists to assess tumour location, volume, growth pattern, presence of fluid–fluid levels (FFL), pathological fractures, skip metastases, neurovascular bundle involvement, regional lymphadenopathy, and physeal or joint involvement. Statistical analyses, including Fisher’s exact test, Chi-square test, and Mann–Whitney U test, were performed to determine associations between MRI features and survival outcomes. Results: Twenty-eight patients (n = 28) met the inclusion criteria. Larger tumour volume (>300 mls) was significantly associated with poorer 2-year survival (p = 0.008). The presence of skip metastases also correlated with worse outcomes (p = 0.041). While presence of FFL, concentric growth pattern, regional lymphadenopathy, and physeal involvement showed trends toward poorer prognosis, these associations were not statistically significant. Conclusions: MRI characteristics, particularly tumour volume and skip metastases, are significant prognostic indicators of 2-year survival in osteosarcoma. These findings highlight the potential role of MRI in risk stratification and treatment planning, aiding in the identification of high-risk patients that can help with management. Full article

This study evaluated how fruit fermentation liquid (FFL) enhances the conversion of chicken manure by black soldier fly larvae (BSFL) and modulates their gut microbiota. Three groups were tested: control (A: 300 g manure + 50 g water), low-dose FFL (B: 300 g manure + 25 g FFL + 25 g water), and high-dose FFL (C: 300 g manure + 50 g FFL). The results show that the dry matter conversion rate significantly increased by 9.5% (p < 0.05), while the feed-to-larvae ratio was reduced by 1.02 (p < 0.01) in group C. NH₃ emissions in group C decreased by 24.48 mg·kg⁻¹·DM (dry matter substrate) day⁻¹ (24.48 mg per kilogram of dry matter substrate per day) (p < 0.01), with suppressed H₂S release. Gut microbiota analysis revealed that FFL reduced the abundance of Proteobacteria (6.07% decrease in group C) while enriching Actinobacteriota (4.68% increase) and beneficial genera (Corynebacterium, Gallicola). Substrate microbial diversity in group C improved, with Proteobacteria and Firmicutes increasing by 11.07% and 4.83%, respectively, and pathogenic Sphingobacteriaceae declining by 21.16% by day 7. FFL likely introduced organic acids and nutrients, enhancing larval digestion and nutrient absorption while inhibiting the production of harmful gases. These findings demonstrate that FFL optimizes BSFL-driven waste conversion efficiency through modulation of the microbiota, offering a sustainable strategy for organic waste management and contributing to circular agricultural systems. Full article

When an unmanned aerial vehicle (UAV) tilts to capture an image of a ground target, variations in object distance may lead to uneven resolution distribution, with the focal length ranging from zero to the full field of view. The field-of-view focal length (FFL), which is a function of the field of view, characterizes the optical properties of the system for each viewing angle. The field-of-view focal length (FFL) quantifies the incremental change in image height resulting from marginal rays exiting the optical system, with infinitesimal angular variations at the field boundary. The optical aberration manifests as an effective focal length variation that exhibits field-dependent characteristics. Through systematic calculation and optimization of the field-of-view focal lengths (FFLs) for ground resolution (GR) control, a mid-wave infrared (MWIR) optical system has been successfully designed, featuring a 10° × 8° field of view (FOV) with an F-number of 3. The optical system implements field-adapted focal length adjustment across distinct viewing angles to ensure consistent ground resolution preservation throughout the full field of view. The designed optical system achieves near-diffraction-limited modulation transfer function (MTF) performance across the full field of view, with all dispersion spots consistently confined within the Airy disk at every viewing angle. The optical system demonstrates superior imaging performance with all dispersion spots confined within the Airy disk radius, fully complying with stringent image quality specifications. Featuring a compact structural configuration, the system exhibits optimal suitability for airborne ground-target reconnaissance applications. Full article

The ubiquitous presence of marine litter has brought huge environmental pressure. A wide range of measures have been developed to address this problem. This paper focuses on the removal measure—Fishing for Litter (FEL). It aims to identify the potential factors affecting fishers’ participation in the FFL program. A two-step approach, including interviews and questionnaire surveys, was employed. A total of 10 fishers participated in the interviews, and 8 factors were initially identified using thematic analysis and utilized in the questionnaire design. A total of 412 valid samples were collected. Descriptive statistics and binary logit regression were used for data analysis. The results showed that rewards, the participation of other friends, and inconveniences or troubles incurred from handling trash feature most in fishers’ decision-making on the participation. Furthermore, fishers’ views toward marine environments also had a behavioral impact on their participation in the program. Potential management measures were proposed, including reducing inconveniences incurred from handling trash on board as well as at ports, providing rewards, encouraging environmental education for fishers, and distributing information regarding the program. It is hoped that fishers will eventually make it a normal onboard practice to collect trash found at sea and develop a sense of marine environmental stewardship. Full article

MicroRNA (miR)-126 is frequently downregulated in malignancies, including breast cancer (BC). Despite its tumor-suppressive role, the mechanisms underlying miR-126 deregulation in BC remain elusive. Through silencing experiments, we identified Early B Cell Factor 1 (EBF1), ETS Proto-Oncogene 2 (ETS2), and Krüppel-Like Factor 2 (KLF2) as pivotal regulators of miR-126 expression. These transcription factors were found to be downregulated in BC due to epigenetic silencing or a “poised but not transcribed” promoter state, impairing miR-126 expression. Gene Ontology analysis of differentially expressed miR-126 target genes in the Cancer Genome Atlas: Breast Invasive Carcinoma (TCGA-BRCA) cohort revealed their involvement in cancer-related pathways, primarily signal transduction, chromatin remodeling/transcription, and differentiation/development. Furthermore, we defined interconnections among transcription factors, miR-126, and target genes, identifying a potential feed-forward loop (FFL) crucial in maintaining cellular identity and preventing the acquisition of stemness properties associated with cancer progression. Our findings propose that the dysregulation of the EBF1/ETS2/KLF2/miR-126 axis disrupts this FFL, promoting oncogenic transformation and progression in BC. This study provides new insights into the molecular mechanisms of miR-126 downregulation in BC and highlights potential targets for therapeutic intervention. Further research is warranted to clarify the role of this FFL in BC, and to identify novel therapeutic strategies aimed at modulating this network as a whole, rather than targeting individual signals, for cancer management. Full article

The Internet of Things (IoT) contains many devices that can compute and communicate, creating large networks. Industrial Internet of Things (IIoT) represents a developed application of IoT, connecting with embedded technologies in production in industrial operational settings to offer sophisticated automation and real-time decisions. Still, IIoT compels significant cybersecurity threats beyond jamming and spoofing, which could ruin the critical infrastructure. Developing a robust Intrusion Detection System (IDS) addresses the challenges and vulnerabilities present in these systems. Traditional IDS methods have achieved high detection accuracy but need improved scalability and privacy issues from large datasets. This paper proposes a Fog-enabled Federated Learning-based Intrusion Detection System (FFL-IDS) utilizing Convolutional Neural Network (CNN) that mitigates these limitations. This framework allows multiple parties in IIoT networks to train deep learning models with data privacy preserved and low-latency detection ensured using fog computing. The proposed FFL-IDS is validated on two datasets, namely the Edge-IIoTset, explicitly tailored to environments with IIoT, and CIC-IDS2017, comprising various network scenarios. On the Edge-IIoTset dataset, it achieved 93.4% accuracy, 91.6% recall, 88% precision, 87% F1 score, and 87% specificity for jamming and spoofing attacks. The system showed better robustness on the CIC-IDS2017 dataset, achieving 95.8% accuracy, 94.9% precision, 94% recall, 93% F1 score, and 93% specificity. These results establish the proposed framework as a scalable, privacy-preserving, high-performance solution for securing IIoT networks against sophisticated cyber threats across diverse environments. Full article

The rapid increase in data volume and variety within the field of machine learning necessitates ethical data utilization and adherence to strict privacy protection standards. Fair federated learning (FFL) has emerged as a pivotal solution for ensuring fairness and privacy protection within distributed learning environments. FFL not only enhances privacy safeguards but also addresses inherent limitations of existing federated learning (FL) systems by fostering equitable model training across diverse participant groups, mitigating the exclusion of individual users or minorities, and improving overall model fairness. This study examines the causes of bias and fairness within existing FL systems and categorizes solutions according to data partitioning strategies, privacy mechanisms, applicable machine learning models, communication architectures, and technologies designed to manage heterogeneity. To mitigate bias, enhance fairness, and strengthen privacy protections in FL, this study also explores fairness evaluation metrics, relevant applications, and associated challenges of FFL. Addressing bias, fairness, and privacy concerns across all mechanisms serves as a valuable resource for practitioners aiming to develop efficient FL solutions. Full article

Atherosclerosis (AS) is a chronic inflammatory condition of the arteries, characterized by plaque formation that can restrict blood flow and lead to potentially fatal cardiovascular events. Given that AS is responsible for a quarter of global deaths, this study aimed to develop a systematic bioinformatics approach to identify biomarkers and regulatory targets involved in plaque development, with the goal of reducing cardiovascular disease risk. AS-specific mRNA expression profiles were retrieved from a publicly accessible database, followed by differentially expressed genes (DEGs) identification and AS-specific weighted gene co-expression network (WGCN) construction. Thereafter, calcification and atherosclerosis-specific (CASS) DEGs were utilized for protein–protein interaction network (PPIN) formation, followed by gene ontology (GO) term and pathway enrichment analyses. Lastly, AS-specific 3-node miRNA feed-forward loop (FFL) construction and analysis was performed. Microarray datasets GSE43292 and GSE28829 were obtained from gene expression omnibus (GEO). A total of $3785$ and $6176$ DEGs were obtained in case of GSE28829 and GSE43292; $3256$ and $5962$ module DEGs corresponding to GSE28829 and GSE43292 were obtained from WGCN. From a total of 54 vascular calcification (VC) genes, $20$ and $29$ CASS-DEGs corresponding to GSE28829 and GSE43292 were overlapped. As observed from FFL centrality measures, the highest-order subnetwork motif comprised one TF (SOX7), one miRNA (miR-484), and one mRNA (SPARC) in the case of GSE28829. Also, in the case of GSE43292, the highest-order subnetwork motif comprised one TF (ESR2), one miRNA (miR-214-3p), and one mRNA (MEF2C). These findings have important implications for developing new therapeutic strategies for AS. The identified TFs and miRNAs may serve as potential therapeutic targets for treating atherosclerotic plaques, offering insights into the molecular mechanisms underlying the pathogenesis and highlighting new avenues for research and treatment. Full article

The durability and performance of dental composites are essential for ensuring long-lasting dental restorations. However, there is a lack of a standardized procedure for evaluating the lifespan of dental materials. Our proposal assumed that dental materials should be tested under aggressive aging conditions to accelerate materials’ degradation in vitro and such an approach should simulate prolonged material usage in the oral cavity. A comprehensive examination of the impacts of three aging methodologies on various mechanical properties, including the flexural strength (FS), diametral tensile strength (DTS), hardness (HV), fracture toughness (FT), flexural fatigue limit (FFL), and microstructure of selected dental materials (Resin F, Flow-Art and Arkon), was conducted. The findings revealed that preformed aging results in an average reduction of 30% in the mechanical strength properties of the dental composites when compared to the control. Notably, a strong correlation was identified between FS and FFL post-aging whereas no such relationship was observed between these parameters and FT. This paper highlights the significance of aging tests for new dental composites and recommends a focus on flexural strength and fracture toughness to optimize costs and time efficiency. Furthermore, the establishment of a standardized test for fracture toughness in dental composites is recommended. It is proposed that a minimum flexural strength of more than 32–48 MPa after aging should be maintained. A more extensive analysis of commercially available materials is suggested to refine the proper evaluation methods for composite materials. Full article

We present two magnetic particle imaging (MPI) systems with bore sizes of 75 mm and 100 mm, respectively, using three-dimensionally arranged permanent magnets for excitation and frequency mixing magnetic detection (FMMD) coils for detection. A rotational and a translational stage were combined to move the field free line (FFL) and acquire the MPI signal, thereby enabling simultaneous overall translation and rotational movement. With this concept, the complex coil system used in many MPI systems, with its high energy consumption to generate the drive field, can be replaced. The characteristic signal of superparamagnetic iron oxide (SPIO) nanoparticles was generated via movement of the FFL and acquired using the FMMD coil. The positions of the stages and the occurrence of the f₁ + 2f₂ harmonics were mapped to reconstruct the spatial location of the SPIO. Image reconstruction was performed using Radon and inverse Radon transformations. As a result, the presented method based on mechanical movement of permanent magnets can be used to measure the MPI, even for samples as large as 100 mm. Our research could pave the way for further technological developments to make the equipment human size, which is one of the ultimate goals of MPI. Full article

Numerous studies derived from medicinal herbs have been conducted to explore bioactive compounds as potential alternatives to synthetic drugs, aiming to mitigate harmful side effects and alleviate economic burdens. In this study, we assessed the safety and potential biological activities of extracts from Fomes fomentarius L. (FFL). The FFL extracts were obtained through various ethanol concentrations, as follows: 0%, 30%, 50%, 70%, and 100%, respectively. All extracts did not induce mutagenicity even up to 5 mg/plate concentration. In the assessment of antioxidant activity, only the hot water extract exhibited weaker antioxidant activity than the other ethanol extracts. Notably, all extracts exhibited significant antimutagenetic effects only with a metabolically active enzyme system (S9 mix). The condition of 70% ethanol extract displayed the most robust antimutagenic activity; thus, the extract was sequentially fractionated with solvents of varying polarities to isolate inhibitory components. After the fractionization, the diethyl ether and butanol fractions effectively suppressed the growth of mutated colonies, suggesting that those such as essential oils, vitamins, alkaloids, and flavonoids can be considered major active compounds. Overall, our study demonstrated that FFL extracts induce potent antioxidant and antimutagenic effects. Further investigations are warranted to verify specific active compounds which induce an antimutagenic effect. Our findings provide valuable insights into FFL as a promising source for potential functional food development. Full article

The recent emergence of SARS-CoV-2 in 2019 has highlighted the necessity of antiviral therapeutics for current and future emerging coronaviruses. Recently, the traditional herbal medicines baicalein, baicalin, and andrographolide have shown inhibition against the main protease of SARS-CoV-2. This provides a promising new direction for COVID-19 therapeutics, but it remains unknown whether these three substances inhibit other human coronaviruses. In this study, we describe the development of novel chimeric mouse hepatitis virus (MHV) reporters that express firefly luciferase (FFL) and the 3CLpro proteases of human coronaviruses HKU1 and OC43. These chimeric viruses were used to determine if the phytochemicals baicalein, baicalin, and andrographolide are inhibitory against human coronavirus strains HKU1 and OC43. Our data show that both baicalein and baicalin exhibit inhibition towards the chimeric MHV strains. However, andrographolide induces cytotoxicity and failed to demonstrate selective toxicity towards the viruses. This study reports the development and use of a safe replicating reporter platform to investigate potential coronavirus 3CLpro inhibitors against common-cold human coronavirus strains HKU1 and OC43. Full article

In this study, we propose an efficient field-free line (FFL) generator for mechanically driven FFL magnetic particle imaging (MPI) applications. The novel FFL generator comprises pairs of Halbach arrays and bar magnets. The proposed design generates high-gradient FFLs with low-mass permanent magnets, realizing fine spatial resolutions in MPI. We investigate the magnetic field generated using simulations and experiments. Our results show that the FFL generator yields a high gradient of 4.76 T/m at a cylindrical field of view of 30 mm diameter and a 70 mm open bore. A spatial resolution of less than 3.5 mm was obtained in the mechanically driven FFL-MPI. Full article

Fine fuel load (FFL) is a crucial variable influencing the occurrence of wildfire. Accurate knowledge of the distribution of FFL in mountainous forests is essential for ongoing wildfire risk management and the stability of mountain ecosystems. Traditional methods of estimating forest fuel load typically involve ground surveys combined with remote sensing, which can be costly and inefficient. Therefore, low-cost, large-scale FFL estimation remains challenging. In this study, Sentinel-2A satellite imagery from the Changsha forest region was used as the data source. Firstly, different feature variables were constructed based on false-color (B843), true-color (B432), four-band (B8432) combinations, and the Normalized Difference Water Index (NDWI). Subsequently, a machine learning approach based on random convolution was employed to estimate FFL. This study also included accuracy assessments of the estimation results and the creation of FFL maps for the study area. The results showed that the FFL estimation based on the B8432 band combination achieved the highest accuracy, with RMSE and R² values of 5.847 t·hm⁻² and 0.656, respectively. FFL estimation results based on false-color imagery followed, with true-color imagery and NDWI index-based estimation results exhibiting lower accuracy. This study offers critical FFL insights using random convolution techniques applied to Sentinel-2A imagery, enhancing the ability to monitor and manage forest fuel conditions effectively, thereby facilitating more informed regional wildfire risk management strategies. Full article

A fast feedback loop (FFL) based on comparators is proposed in this paper. The FFL improves the transient response characteristics of the output-capacitorless low-dropout (OCL-LDO) regulator. When the load current switches between 1 mA and 100 mA with 1 $\mathsf{\mu }$s edge time, the overshoot and undershoot are 33 mV and 37 mV, respectively, and recovery time is 1.2 $\mathsf{\mu }$s and 1.6 $\mathsf{\mu }$s, respectively. A damping-factor-control (DFC) frequency compensation circuit is used to ensure the stability of the OCL-LDO, and the simulation results show that the phase margin exceeds 50 degree in the entire load variation range. This design is based on 180 nm process, and the area of the chip is 0.068 mm${}^2$ (without pads). A band-gap reference circuit is also designed in this work; its output voltage is 1.2 V and its temperature coefficient is 7.96 ppm/${}^{\circ }$C. The input voltage range of the proposed OCL-LDO is 2.5 V to 5 V with a linear regulation rate of 0.128 mV/V and a load regulation rate of 0.0017 mV/mA. In addition, the load range of the proposed OCL-LDO is 0 mA to 100 mA, and the minimum required external capacitance is 0 F. The power supply rejection ratio (PSRR) is −46 dB @ 1 kHz. Full article