Fuse, Blade, 5A, 32V, Fast Acting
- Known as:
- Fuse, Blade, 5A, 32V, Fast Acting
- Catalog number:
- rvth5383
- Product Quantity:
- EUR
- Category:
- -
- Supplier:
- Diasource
- Gene target:
- Fuse Blade 5A 32V Fast Acting
Related genes to: Fuse, Blade, 5A, 32V, Fast Acting
- Gene:
- FUSE NIH gene
- Name:
- polykaryocytosis promoter
- Previous symbol:
- -
- Synonyms:
- -
- Chromosome:
- 10
- Locus Type:
- phenotype only
- Date approved:
- 2001-06-22
- Date modifiied:
- 2012-10-02
Related products to: Fuse, Blade, 5A, 32V, Fast Acting
Related articles to: Fuse, Blade, 5A, 32V, Fast Acting
- Early identification of ICU patients at high mortality risk is essential for triage and timely intervention. We present adaptive layer fusion with intelligent attention (ALFIA), a modular architecture that jointly trains low-rank adaptation (LoRA) adapters and an adaptive layer-weighting mechanism to fuse multi-layer semantic features from a pretrained transformer backbone. ALFIA operates on , in which tabular clinical variables (demographics, vital signs, laboratory values, and severity scores) are converted into standardized natural-language descriptions rather than processed as free-text clinical notes. Evaluated on the CriticalWindow-24 benchmark with MIMIC-IV and eICU cohorts, ALFIA achieves strong AUPRC while maintaining a balanced precision-recall profile. The learned embeddings can be further combined with gradient boosting (ALFIA-boost) or neural networks (ALFIA-nn) for additional gains. These findings demonstrate that text-encoded structured EHR data can support practical, generalizable early-warning models for ICU mortality risk stratification. - Source: PubMed
Publication date: 2026/06/04
Wang HanLao GuoguangHe RuoyunLiu TingLuo HejiaoQin ChangqiLuo HongyingLiu YingqiHuang JunminWei ZihanChen LuXu YongzhiBi ZiqianSong JunhaoWang TianyangChia Xin LiangHou XuanheLiu HuafengHao JunfengTian Chunjie - Underwater images often suffer from visual degradation due to varying light absorption at different wavelengths and scattering from suspended particles. To tackle these issues, we present an intelligent optimized multi-exposure image fusion method called IMIF. Specifically, we propose an adaptive color transfer strategy that employs a colorless reference image to correct the color distortion issue by transferring the mean and standard deviation of the reference image to adjust a color-balanced image. Subsequently, we introduce a particle swarm optimization algorithm that intelligently selects the optimal set of exposure image sequences by employing information entropy and edge intensity of the image as fitness metrics. Meanwhile, we leverage a guided filtering strategy to decompose the exposure image sequences into basic and detailed layers, taking into account the exposure characteristics of each layer to generate corresponding weight maps. Finally, we employ a multi-exposure fusion strategy to adaptively fuse the exposed image sequences with weight maps, producing an enhanced result. Extensive experiments conducted on three datasets demonstrate that our IMIF method outperforms state-of-the-art (SOTA) methods in both qualitative and quantitative evaluations. Additionally, the enhanced results produced by our proposed IMIF method significantly improve the accuracy of object detection and keypoint detection. The is available at https://www.researchgate.net/publication/403951386 2026-IMIF. - Source: PubMed
Publication date: 2026/06/16
Zhang WeidongYu BaiqiangZhao WenyiLiang ZhengZhuang PeixianZhu Keran - Lower-limb wearable robots require accurate Locomotion Mode Prediction (LMP) to provide appropriate assistance across diverse terrains. Recent reconstructionbased LMP methods fuse high-dimensional multimodal sensor data to model the relationship between human motion and terrains, improving prediction accuracy and cross-terrain adaptability. However, they typically incur high computational cost, including GPU dependency, and often require initialization procedures involving wearer participation or professional supervision. This paper proposes a self-initialized, GPU-free LMP method to overcome these deployment constraints. Our method adopts a gravity-aligned world coordinate frame as a unified geometric reference: a self-initialization procedure first establishes this reference, upon which a progressive plane representation enables GPU-free terrain reconstruction. Together, these two components form a pipeline that achieves reconstruction-based LMP on an onboard CPU without manual intervention. Comprehensive experiments across various terrains and subjects evaluate the system in terms of LMP accuracy, initialization success rate, computational efficiency, and memory footprint. We also compare the proposed method with a lightweight end-to-end baseline to further examine the role of the GPU-free terrain reconstruction. The results show that the proposed method achieves prediction accuracy comparable to state-of-the-art methods, including GPU-dependent counterparts, while operating entirely on a CPU without manual intervention. - Source: PubMed
Publication date: 2026/06/15
Zhao ShunyiYu ZehuanZhou ZhihaoRuan LechengWang Qining - Adequate iodine intake is essential for maintaining thyroid function. School meal iodine content (SMIC) is one of the main sources of iodine for schoolchildren. The median urinary iodine concentration (mUIC) in spot urine samples is a reliable indicator of a population's iodine status. The aim of this study is to explore the association between SMIC and mUIC in school-children aged 6-12 year. From 2013-2023 we estimated the SMIC from school lunch menus and compared it to mUIC. Overall, 15,091 children from 115 elementary schools in 25 regions across Japan were included. The mUIC was 294.5 μg/L suggesting adequate iodine intake. The median value of SMIC over a one-month period was 53.0 μg/meal and there was a positive correlation of mUIC with the SMIC (Spermann r = 0.5040) or the SMIC prior to urine sampling (r = 0.4816). Between the two survey years the mUICs decreased by 31.8 to 77.2% in Rishiri Island, Rebun Island, Nakashibetsu and Hiroshima despite no significant change in SMIC over a one-month period except in Rebun Island. The average SMIC, SMIC consumed immediately prior to urine collection, and the time elapsed between the last school meal and urine collection were possible factors that may influence mUIC values. The high mUIC value observed in our earlier survey was partially due to the influence of school lunches. Although school lunches make a significant contribution to iodine nutrition, SMIC can be a potential pitfall for school-based surveys using spot urine samples. - Source: PubMed
Publication date: 2026/06/15
Fuse YozenTsukada NobuYamaguchi MayuIto YoshiyaShishiba Yoshimasa - The trafficking, docking, and fusion of membrane vesicles at the mother centriole (MC) are important for primary cilium construction. Here, we determined the three-dimensional (3D) membrane ultrastructures, and associated proteins, involved in this primary cilium assembly mechanism upstream of axoneme growth. Our work suggests that the enlargement of small vesicles docked to the MC is a key trigger for ciliogenesis progression, a process requiring the MC distal appendage protein CEP164. These vesicles appear to fuse to form tubular C-shaped intermediates and an unprecedented toroidal membrane intermediate. The formation of these previously uncharacterized tubular membrane ciliogenesis intermediates is orchestrated by the membrane trafficking regulators EHD1 and RAB8, and is associated with the IFT-B complex protein IFT88. Remarkably, we show that EHD1, through its membrane tubulation function, regulates ciliogenesis progression by directly promoting CP110/CEP97 removal from the MC cap. The establishment of these tubular membrane structures is also associated with the recruitment of the ciliary gate transition zone proteins. Together, these findings redefine the architectural framework of early ciliogenesis and underscore the utility of isotropic ultrastructural imaging combined with quantitative 3D analysis for elucidating mechanisms of membrane trafficking and organelle biogenesis. - Source: PubMed
Publication date: 2026/06/13
Lu QuanlongZhao HuijieKhan ZiamHarned AdamKamiya ErinaMagidson ValentinSenthilkumar AbhiKilnagar AvaneeshDoan Phuong Thi BichPerera SumethNarayan KedarWestlake Christopher J