In this paper, the effect of Split Ring Resonator (SRR) loading on mutual coupling reduction of Magneto Electric (ME)-dipole antennas fed through printed ridge gap waveguide (PRGW) is presented for millimeter-wave 5G ...
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Objective and Impact *** present a fully automated hematological analysis framework based on single-channel(single-wavelength),label-free deep-ultraviolet(UV)microscopy that serves as a fast,cost-effective alternative...
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Objective and Impact *** present a fully automated hematological analysis framework based on single-channel(single-wavelength),label-free deep-ultraviolet(UV)microscopy that serves as a fast,cost-effective alternative to conventional hematology *** analysis is essential for the diagnosis and monitoring of several diseases but requires complex systems operated by trained personnel,costly chemical reagents,and lengthy ***-free techniques eliminate the need for staining or additional preprocessing and can lead to faster analysis and a simpler *** this work,we leverage the unique capabilities of deep-UV microscopy as a label-free,molecular imaging technique to develop a deep learning-based pipeline that enables virtual staining,segmentation,classification,and counting of white blood cells(WBCs)in single-channel images of peripheral blood *** train independent deep networks to virtually stain and segment grayscale images of *** segmented images are then used to train a classifier to yield a quantitative five-part WBC *** virtual staining scheme accurately recapitulates the appearance of cells under conventional Giemsa staining,the gold standard in *** trained cellular and nuclear segmentation networks achieve high accuracy,and the classifier can achieve a quantitative five-part differential on unseen test *** proposed automated hematology analysis framework could greatly simplify and improve current complete blood count and blood smear analysis and lead to the development of a simple,fast,and low-cost,point-of-care hematology analyzer.
This research paper introduces a novel design of an inductive sensor based on a MEMS (Micro-Electro-Mechanical System) inductive link. The sensor comprises two identical Al inductor coils micromachined on each side of...
*** aim to develop a machine learning algorithm to quantify adipose tissue deposition at surgical sites as a function of biomaterial *** *** our knowledge,this study is the first investigation to apply convolutional n...
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*** aim to develop a machine learning algorithm to quantify adipose tissue deposition at surgical sites as a function of biomaterial *** *** our knowledge,this study is the first investigation to apply convolutional neural network(CNN)models to identify and segment adipose tissue in histological images from silk fibroin biomaterial *** designing biomaterials for the treatment of various soft tissue injuries and diseases,one must consider the extent of adipose tissue *** this work,we analyzed adipose tissue accumulation in histological images of sectioned silk fibroin-based biomaterials excised from rodents following subcutaneous implantation for 1,2,4,or 8 *** strategies for quantifying adipose tissue after biomaterial implantation are often tedious and prone to human bias during *** used CNN models with novel spatial histogram layer(s)that can more accurately identify and segment regions of adipose tissue in hematoxylin and eosin(H&E)and Masson’s trichrome stained images,allowing for determination of the optimal biomaterial *** compared the method,Jointly Optimized Spatial Histogram UNET Architecture(JOSHUA),to the baseline UNET model and an extension of the baseline model,attention UNET,as well as to versions of the models with a supplemental attention-inspired mechanism(JOSHUA+and UNET+).*** inclusion of histogram layer(s)in our models shows improved performance through qualitative and quantitative *** results demonstrate that the proposed methods,JOSHUA and JOSHUA+,are highly beneficial for adipose tissue identification and *** new histological dataset and code used in our experiments are publicly available.
Diagnosing thyroid cancer is notably challenging because of its diverse manifestations and the rising number of cases worldwide. Early detection and diagnosis of thyroid nodules’ malignancy is crucial for reducing th...
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Model Predictive Control (MPC) is commonly used to solve flight control problems in quadrotors due to its ability to handle multivariate and practical constraints. Considering its computational problem, which may lead...
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Breast cancer (BC) remains a significant global health concern, necessitating accurate and efficient diagnostic approaches. In this study, we propose a comprehensive framework that integrates feature extraction, selec...
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The added value of the information transmitted in a cybernetic environment has resulted in a sophisticated malicious actions scenario aimed at data exfiltration. In situations with advanced actors, like APTs, such act...
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We present a technique for information-theoretic optimization of computational imaging systems demonstrated in snapshot 3D microscopy. By directly evaluating measurement quality and decoupling optimization from downst...
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Vanadium Redox Flow Batteries (VRFB) are promising for large-scale energy storage due to their long life and environmental benefits. Accurate temperature prediction is key to optimizing VRFB performance and longevity....
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