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ion of RASSF1A were 17.20 and 42.13 months for patients without promoter region hypermethylation of RASSF1A and the patients with KRAS mutation with or without hypermethylation of the promoter region of RASSF1A a tumor suppressor gene had poorer survival compared with those patients with wild type KRAS gene, with or without hypermethylation of RASSF1A promoter region. Silmitasertib cost These differences were statistically significant based on Log-rank (Mantel-cox) test (P = 0.0001). The median survivals among patients with mutation in KRAS protooncogene were 16 months and 42 months for NSCLC patients with wild type KRAS gene. Conclusions The aberrant RASSF1A gene promoter methylation with the subsequent mutation in KRAS gene (exon 2) plays a significant role in the pathogenesis and disease progression of non-small cell lung carcinoma (NSCLC). © 2020 Published by Elsevier Ltd.Advanced visible infrared imaging spectrometer-new generation (AVIRIS-NG) airborne Hyperspectral data has 5nm spectral resolution which allows us to identify characteristic spectral signatures of the different altered and weathered mineral assemblage. In this study Airborne AVIRIS-NG hyperspectral data were used to identify the different altered, weathered and clay group of minerals in the Jahajpur, Bhilwara, India. In the study area, different hydrothermal minerals such as Montmorillonite, Smectite and Talc were identified. Apart from this, Goethite/Limonite mineral spectral signatures were identified using the AVIRIS-NG data in the VNIR (visible and near infrared) region of the electromagnetic spectrum. Minerals thus identified were verified by the conventional geological analysis viz. petrography and XRD of the field samples collected from the study area. The results of the conventional geological methods and spectroscopy were in good confirmation with the results found through the analysis of the AVIRIS-NG data. Identified minerals show a good indication of the advance argillic alteration in the study area which stand in confirmation with the geology of the area. Spectral analysis of the AVIRIS-NG data reveals that the reflectance spectra of the airborne AVIRIS-NG Hyperspectral data found promising for mineral identification and mapping. © 2020 Published by Elsevier Ltd.Chitosan and chitin are mainly extracted from shells of fish such as lobsters, crabs or shrimps. Originally, the raw material and the two compounds are identical. This study aims to show the acid concentration effect on chitosan extraction from shrimp shells between concentrated and diluted acid; on surface morphology, thermal resistance, structural, elemental composition, optical and opto-electronic properties. It also aims to reduce the production time and increase the quantity. We focused mainly on comparing between Physico-chemical properties of chitosans extracted by diluted (1M) and concentrated (20%) Chloric acids, and sometimes we compare by other concentrated acids like nitric acid (70%) and sulphuric acid (98%). We performed the product’s characterization by various tools such as X-ray diffraction (XRD) spectroscopy, X-ray fluorescence (XRF) analysis, UV-Visible spectroscopy, Fourier Transformed Infra-Red (FTIR), Raman Spectroscopy, Thermogravimetry and Derivative Thermogravimetry (TG/DTG), Scanning Electron Microscopy (SEM), Energy-dispersive X-ray spectroscopy (EDX) analysis. The elemental analysis (XRF and EDX). The results showed that all chitosan samples we gained are good about 80% degree of deacetylation, and pure mostly composed by carbon between (15,02% – 45.55%), nitrogen (4,17% – 12.28%) and oxygen (42.16% and 81.25%), with appearance of essential peaks for chitosan in Raman analysis 470 cm-1 → ν(C-C(=O)-C), 1000 cm-1 → ν(C-H), 1800 cm-1 → δ(C=CCOOR), δ(C=O), 2630 cm-1 → δ(CH) rings, 3250 cm-1 → ν(NH2). All our chitosan particles are ultrafine nanoscale between 8 and 34 nm. © 2020 The Author(s).In the framework of a project on simple circuits with unexpected high degrees of freedom, we report an autonomous microwave oscillator made of a CLC linear resonator of Colpitts type and a single general purpose operational amplifier (Op-Amp). The resonator is in a parallel coupling with the Op-Amp to build the necessary feedback loop of the oscillator. Unlike the general topology of Op-Amp-based oscillators found in the literature including almost always the presence of a negative resistance to justify the nonlinear oscillatory behavior of such circuits, our zero resistor circuit exhibits chaotic and hyperchaotic signals in GHz frequency domain, as well as many other features of complex dynamic systems, including bistability. This simplest form of Colpitts oscillator is adequate to be used as didactic model for the study of complex systems at undergraduate level. Analog and experimental results are proposed. © 2020 Published by Elsevier Ltd.The location of pith in a cross-sectional surface of wood can be used to either evaluate its quality or guide the removal of soft wood from the wood stem. There have been many attempts to automate pith detection in images taken by a normal camera. The objective of this study is to comparatively study the effectiveness of two popular deep neural network (DNN) object detection algorithms for parawood pith detection in cross-sectional wood images. In the experiment, a database of 345 cross-sectional images of parawood, taken by a normal camera within a sawmill environment, was quadrupled in size via image augmentation. The images were then manually annotated to label the pith regions. The dataset was used to train two DNN object detection algorithms, an SSD (single shot detector) MobileNet and you-only-look-once (YOLO), via transfer learning. The inference results, utilizing pretrained models obtained by minimizing a loss function in both algorithms, were obtained on a separate dataset of 215 images and compared. The detection rate and average location error with respect to the ground truth were used to evaluate the effectiveness of detection. Additionally, the average distance error results were compared with the results of a state-of-the-art non-DNN algorithm. SSD MobileNet obtained the best detection rate of 87.7% with a ratio of training to test data of 8020 and 152,000 training iterations. The average distance error of SSD MobileNet is comparable to that of YOLO and six times better than that of the non-DNN algorithm. Hence, SSD MobileNet is an effective approach to automating parawood pith detection in cross-sectional images. © 2020 The Author(s).