Machine learning models, including thyroid biomarkers, are increasingly utilized in healthcare for biomarker prediction. These models offer the potential to enhance disease diagnosis through data-driven approaches rel...
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The paper is about the study of building a Reliability program for the Leonardo AW139 Fleet of a start-up company that is based in the Middle East. The start-up helicopter company started its operations in 2018 with a...
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Rainfall frequency analysis, an essential work for water resources management, is often conducted by using the annual maximum rainfall series. For rainfall stations with short record lengths and outliers presence, the...
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This paper investigates mutual coupling in narrow-band uniform linear antenna arrays through Thévenin network modeling. After an in-depth analysis, we derive a Thévenin network representing a given mutual co...
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ISBN:
(数字)9798331522124
ISBN:
(纸本)9798331522131
This paper investigates mutual coupling in narrow-band uniform linear antenna arrays through Thévenin network modeling. After an in-depth analysis, we derive a Thévenin network representing a given mutual coupling matrix and develop a method to achieve an equivalent decoupled model that significantly reduces computational and memory requirements in practical applications.
The well-being of modern societies depends on the functioning of their infrastructure networks. During their service lives, infrastructure networks are subject to different stresses (e.g., deterioration, hazards, etc....
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Filamentous-actin (F-actin) crosslinking within the cell cytoskeleton mediates the transmission of mechanical forces, enabling changes in cell shape, as occurs during cell division and cell migration. Crosslinking by ...
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Filamentous-actin (F-actin) crosslinking within the cell cytoskeleton mediates the transmission of mechanical forces, enabling changes in cell shape, as occurs during cell division and cell migration. Crosslinking by actin binding proteins (ABPs) generally increases the connectivity of the F-actin network, but also increases network rigidity. As a result, there is a narrow range in the concentration of crosslinker protein at which F-actin networks are both connected and labile. Another ABP, cofilin, severs F-actin filaments at high pH through increasing their bending flexibility and concentrating mechanical stress, inducing fragmentation. By contrast, at lower pH, cofilin increases filament flexibility yet does not sever. Instead, it forms disulfide bonds, which crosslink F-actin into bundles, and bundles into networks. Here, we combine light microscopy and rheology to determine the impact of two potentially opposing effects on the mechanics of F-actin networks—increased flexibility at the filament level, and increased connectivity at the network level. Indeed, by linear rheology, we find that these mechanisms are counterbalanced, such that cofilactin network moduli are only weakly dependent on cofilin concentration over a broad range, in contrast to the dramatic stiffening that occurs with F-actin crosslinking protein. Further, by nonlinear rheology, the network stiffens at a higher stress than crosslinking protein, indicative of a broader range in which the material remains flexible. These results may enable F-actin networks to increase connectivity without heavy penalties to rigidity, and thus provide a new route to modulating active polymer mechanics unseen using traditional F-actin accessory proteins.
An important paradigm shift within healthcare is the shift toward patient-centered care (PCC). Multidisciplinary team meetings (MDTM) are considered essential for PCC, despite being considered time-consuming and expen...
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Diagnosing gastrointestinal cancer by classical means is a hazardous *** have witnessed several computerized solutions for stomach disease detection and ***,the existing techniques faced challenges,such as irrelevant ...
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Diagnosing gastrointestinal cancer by classical means is a hazardous *** have witnessed several computerized solutions for stomach disease detection and ***,the existing techniques faced challenges,such as irrelevant feature extraction,high similarity among different disease symptoms,and the least-important features from a single *** paper designed a new deep learning-based architecture based on the fusion of two models,Residual blocks and Auto ***,the Hyper-Kvasir dataset was employed to evaluate the proposed *** research selected a pre-trained convolutional neural network(CNN)model and improved it with several residual *** process aims to improve the learning capability of deep models and lessen the number of ***,this article designed an Auto-Encoder-based network consisting of five convolutional layers in the encoder stage and five in the decoder *** research selected the global average pooling and convolutional layers for the feature extraction optimized by a hybrid Marine Predator optimization and Slime Mould optimization *** features of both models are fused using a novel fusion technique that is later classified using the Artificial Neural Network *** experiment worked on the HyperKvasir dataset,which consists of 23 stomach-infected *** last,the proposed method obtained an improved accuracy of 93.90%on this *** is also conducted with some recent techniques and shows that the proposed method’s accuracy is improved.
Work from home (WFH) has become a global phenomenon that continues to grow, especially since the COVID-19 pandemic hit the world. Many organizations and companies are forced to adopt a remote working model to keep the...
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Work from home (WFH) has become a global phenomenon that continues to grow, especially since the COVID-19 pandemic hit the world. Many organizations and companies are forced to adopt a remote working model to keep their employees safe. The usefulness of WFH is still up for dispute, though. Text mining analysis can be utilized to determine how beneficial working from home is. Sentiment analysis uses text analysis to gather ten thousand data from social media Tweets. Joy emotion is predicted to dominate with 83.98 percent according to the mining performed by the vocabulary valence aware dictionary and sentiment reasoner (VADER).
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