A Graphic Review of the Free Speech Clause

This work acts as a spring board for the study of the Free Speech Clause of the First Amendment. It builds useful graphical representations of complex constitutional theories from the ground up, allowing students to follow both development and the application of these theories

Microstructural and Electron-Emission Characteristics of Nb-Si-N Films in Surface-Conduction Electron-Emitter Display

AbstractWe proposed ternary nitride Nb-Si-N film as a promising surface-conduction electron emitter (SCE) in surface-conduction electron-emitter display (SED). Nb-Si-N films consisted of continuous NbN polycrystalline phase with (Si3-xNb4x)N4 amorphous phase in NbN grain boundaries. After electroforming, serrated nanogaps were observed in Nb-Si-N SCE strips. The emission current of Nb-Si-N SCE array of 1×18 cells was 6.50μA with anode voltage of 1.5kV and device voltage of 22V, indicating satisfying potential for display applications comparing with NbN SCEs. © 2009 Published by Elsevier B.V

Case Report: Rhabdomyolysis in aneurysmal subarachnoid hemorrhage: A rare case with implications for management

BackgroundIn recent years, some cases of rhabdomyolysis after surgery have been reported. In this report, we present an adult patient with rhabdomyolysis after intracranial aneurysm surgery.Case ReportA 59-year-old male suffered from a coma, fever, and soy sauce urine after intracranial aneurysm clipping. A routine blood examination showed that liver and kidney function were impaired, and creatine phosphokinase(CK) and creatine phosphokinase isoenzyme(CK-MB) levels increased. Therefore, we consider patients with rhabdomyolysis after intracranial aneurysm surgery. A series of treatment schemes, such as intravenous fluid infusion, alkalized urine, and hemodialysis, were adopted immediately, and finally the patient was discharged safely.ConclusionFor some postoperative patients, once the level of CK/CK-MB increases, acute renal damage occurs, and the urine color turns soy sauce, we should be alert to postoperative rhabdomyolysis.For those patients who have been diagnosed with rhabdomyolysis, we need to take timely treatment measures to avoid an unfortunate occurrence

Fusing fine-tuned deep features for skin lesion classification

© 2018 Elsevier Ltd Malignant melanoma is one of the most aggressive forms of skin cancer. Early detection is important as it significantly improves survival rates. Consequently, accurate discrimination of malignant skin lesions from benign lesions such as seborrheic keratoses or benign nevi is crucial, while accurate computerised classification of skin lesion images is of great interest to support diagnosis. In this paper, we propose a fully automatic computerised method to classify skin lesions from dermoscopic images. Our approach is based on a novel ensemble scheme for convolutional neural networks (CNNs) that combines intra-architecture and inter-architecture network fusion. The proposed method consists of multiple sets of CNNs of different architecture that represent different feature abstraction levels. Each set of CNNs consists of a number of pre-trained networks that have identical architecture but are fine-tuned on dermoscopic skin lesion images with different settings. The deep features of each network were used to train different support vector machine classifiers. Finally, the average prediction probability classification vectors from different sets are fused to provide the final prediction. Evaluated on the 600 test images of the ISIC 2017 skin lesion classification challenge, the proposed algorithm yields an area under receiver operating characteristic curve of 87.3% for melanoma classification and an area under receiver operating characteristic curve of 95.5% for seborrheic keratosis classification, outperforming the top-ranked methods of the challenge while being simpler compared to them. The obtained results convincingly demonstrate our proposed approach to represent a reliable and robust method for feature extraction, model fusion and classification of dermoscopic skin lesion images