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Breast cancer (BC) is currently the most common form of cancer diagnosed worldwide with an incidence estimated at 2.26 million in 2020. Additionally, BC is the leading cause of cancer death. Many subtypes of breast cancer exist with distinct biological features and which respond differently to various treatment modalities and have different clinical outcomes. To ensure that sufferers receive lifesaving patients-tailored treatment early, it is crucial to accurately distinguish dangerous malignant (ductal carcinoma, lobular carcinoma, mucinous carcinoma, and papillary carcinoma) subtypes of tumors from adenosis, fibroadenoma, phyllodes tumor, and tubular adenoma benign harmless subtypes. An excellent automated method for detecting malignant subtypes of tumors is desirable since doctors do not identify 10% to 30% of breast cancers during regular examinations. While several computerized methods for breast cancer classification have been proposed, deep convolutional neural networks (DCNNs) have demonstrated superior performance. In this work, we proposed an ensemble of four variants of DCNNs combined with the support vector machines classifier to classify breast cancer histopathological images into eight subtypes classes: four benign and four malignant. The proposed method utilizes the power of DCNNs to extract highly predictive multi-scale pooled image feature representation (MPIFR) from four resolutions (40×, 100×, 200×, and 400×) of BC images that are then classified using SVM. Eight pre-trained DCNN architectures (Inceptionv3, InceptionResNetv2, ResNet18, ResNet50, DenseNet201, EfficientNetb0, shuffleNet, and SqueezeNet) were individually trained and an ensemble of the four best-performing models (ResNet50, ResNet18, DenseNet201, and EfficientNetb0) was utilized for feature extraction. One-versus-one SVM classification was then utilized to model an 8-class breast cancer image classifier. Our work is novel because while some prior work has utilized CNNs for 2- and 4-class breast cancer classification, only one other prior work proposed a solution for 8-class BC histopathological image classification. A 6B-Net deep CNN model was utilized, achieving an accuracy of 90% for 8-class BC classification. In rigorous evaluation, the proposed MPIFR method achieved an average accuracy of 97.77%, with 97.48% sensitivity, and 98.45% precision on the BreakHis histopathological BC image dataset, outperforming the prior state-of-the-art for histopathological breast cancer multi-class classification and a comprehensive set of DCNN baseline models. [ABSTRACT FROM AUTHOR]

This paper presents the results of an experimental study of the micromechanisms of surface topography evolution and fatigue fracture in polysilicon MEMS structures. The initial stages of fatigue are shown to be associated with stress-assisted surface topography evolution and the thickening of Si[O.sub.2] layers that form on the unpassivated polysilicon surfaces and crack/notch faces. The differences in surface topography and oxide thickness are characterized as functions of fatigue cycling before discussing the micromechanisms of fatigue fracture. [840] Index Terms--Fatigue, fracture, microelectromechanical systems (MEMS), polysilicon, Si[O.sub.2] layers, surface topography evolution.

Research demonstrates the microstructural changes in the thermal barrier coating as influenced by isothermal and thermocyclic exposures. Long exposures to 1100 C create pores between thermally grown oxide layer and the bond coat and cracks within the former. Thermocyclic exposures led to wavy contoured thermally grown oxide layer.

This paper presents an implantable polymer/metal alloy thin film structure for localized post-operative treatment of breast cancer. A combination of experiments and models is used to study the temperature changes due to Joule heating by patterned metallic thin films embedded in polydimethylsiloxane. The heat conduction within the device and the surrounding normal/cancerous breast tissue is modeled with three-dimensional finite element method (FEM). The FEM simulations are used to explore the potential effects of device geometry and Joule heating on the temperature distribution and lesion (thermal dose). The FEM model is validated using a gel model that mimics biological media. The predictions are also compared to prior results from in vitro studies and relevant in vivo studies in the literature. The implications of the results are discussed for the potential application of polymer/metal thin film structures in hyperthermic treatment of cancer. [ABSTRACT FROM AUTHOR]

This paper explores the potential of implantable magnetic nanocomposites for the localized treatment of breast cancer via hyperthermia. Magnetite (Fe3O4)-reinforced polydimethylsiloxane composites were fabricated and characterized to determine their structural, magnetic, and thermal properties. The thermal properties and degree of optimization were shown to be strongly dependent on material properties of magnetic nanoparticles (MNPs). The in-vivo temperature profiles and thermal doses were investigated by the use of a 3D finite element method (FEM) model to simulate the heating of breast tissue. Heat generation was calculated using the linear response theory model. The 3D FEM model was used to investigate the effects of MNP volume fraction, nanocomposite geometry, and treatment parameters on thermal profiles. The implications of the results were then discussed for the development of implantable devices for the localized treatment of breast cancer. [ABSTRACT FROM AUTHOR]

This paper presents the evidence of growth of dendrites during the annealing of poly (3-hexylthiophene) and [6,6]-phenyl C61-butyric acid methyl ester (P3HT:PCBM) blends that are being explored for potential applications in bulk heterojunction polymer solar cells. These dendrites were observed in high resolution scanning electron microscopy to have morphologies that depend on the annealing temperature. Consistent with a recent eutectic phase diagram, the dendrites were not observed at 200 °C. The observations were explained by considering the effects of temperature on the kinetics of phase nucleation and growth in P3HT: PCBM blends. The implications of the results are also discussed for the stability of electrical properties in bulk heterojunction solar cells. [ABSTRACT FROM AUTHOR]

The role of thermal gradients and their attendant mechanical stresses in the overall stability of organic electronic devices has been elucidated through the occurrence of spiral shaped blisters that develop on the surface of suitably biased polymer light emitting diodes. A model based on the spontaneous disordering (or ordering) of polymeric thin film systems has been used to explain the formation and growth of these blisters. The model is shown to provide insights into how thermal stresses affect the overall stability of organic electronic devices. The implications of the results are then discussed for the design of flexible organic electronic devices. [ABSTRACT FROM AUTHOR]

This paper presents the results of a combined experimental and theoretical study of adhesion between hard and soft layers that are relevant to medical devices such as drug-eluting stents and semiconductor applications. Brazil disk specimens were used to measure the interfacial fracture energies between model parylene C and 316L stainless steel over a wide range of mode mixities. The trends in the overall fracture energies are predicted using a combination of adhesion theories and fracture mechanics concepts. The measured interfacial fracture energies are shown to be in good agreement with the predictions. [ABSTRACT FROM AUTHOR]

Surface biofunctionalization of the hydrophobic lanthanide ion doped hexagonal phase NaYF4:Yb,Er upconversion nanophosphors (UCNPs) was achieved by introducing amino and carboxyl groups, respectively. Amino groups were added by using the 3-aminopropyltrimethoxysilane reaction after a thin layer of SiO2 coating. The carboxyl groups on surface were added directly by coating modified amphiphilic polyacrylic acid polymer. Experimental studies of cytotoxicity and cell uptake of UCNPs were conducted. The cytotoxicity analysis of the functionalized UCNPs was conducted by methylthiazol tetrazolium assays. Cell uptake was accomplished by incubating the UCNPs with human osteosarcoma cells and proved by transmission electron microscopy. The results showed that the functionalized UCNPs had very low toxicity compared with the control group, while UCNPs taken into the cells indicated that they had very high biocompatibility. The imaging of UCNPs, which were incubated with AB12 mouse mesothelioma cells and excited by 1 W 980 nm light, showed individual particles with visible light emission. These results exhibited promising applications of functionalized UCNPs in cell imaging and photodynamic therapy. [ABSTRACT FROM AUTHOR]