Deep learning based Brain Tumour Classification based on Recursive Sigmoid Neural Network based on Multi-Scale Neural Segmentation

Brain tumours are malignant tissues in which cells replicate rapidly and indefinitely, and tumours grow out of control. Deep learning has the potential to overcome challenges associated with brain tumour diagnosis and intervention. It is well known that segmentation methods can be used to remove abnormal tumour areas in the brain. It is one of the advanced technology classification and detection tools. Can effectively achieve early diagnosis of the disease or brain tumours through reliable and advanced neural network classification algorithms. Previous algorithm has some drawbacks, an automatic and reliable method for segmentation is needed. However, the large spatial and structural heterogeneity between brain tumors makes automated segmentation a challenging problem. Image tumors have irregular shapes and are spatially located in any part of the brain, making their segmentation is inaccurate for clinical purposes a challenging task. In this work, propose a method Recursive SigmoidNeural Network based on Multi-scale Neural Segmentation (RSN2-MSNS) for image proper segmentation. Initially collets the image dataset from standard repository for brain tumour classification.  Next, pre-processing method that targets only a small part of an image rather than the entire image. This approach reduces computational time and overcomes the over complication. Second stage, segmenting the images based on the Enhanced Deep Clustering U-net (EDCU-net) for estimating the boundary points in the brain tumour images. This method can successfully colour histogram values are evaluating segment complex images that contain both textured and non-textured regions. Third stage, Feature extraction for extracts the features from segmenting images using Convolution Deep Feature Spectral Similarity (CDFS2) scaled the values from images extracting the relevant weights based on its threshold limits. Then selecting the features from extracting stage, this selection is based on the relational weights. And finally classified the features based on the Recursive Sigmoid Neural Network based on Multi-scale Neural Segmentation (RSN2-MSNS) for evaluating the proposed brain tumour classification model consists of 1500 trainable images and the proposed method achieves 97.0% accuracy. The sensitivity, specificity, detection accuracy and F1 measures were 96.4%, 952%, and 95.9%, respectively

On associating Fast Radio Bursts with afterglows

A radio source that faded over six days, with a redshift of $z\approx0.5$ host, has been identified by Keane et al. (2016) as the transient afterglow to a fast radio burst (FRB 150418). We report follow-up radio and optical observations of the afterglow candidate and find a source that is consistent with an active galactic nucleus. If the afterglow candidate is nonetheless a prototypical FRB afterglow, existing slow-transient surveys limit the fraction of FRBs that produce afterglows to 0.25 for afterglows with fractional variation, $m=2|S_1-S_2|/(S_1+S_2)\geq0.7$, and 0.07 for $m\geq1$, at 95% confidence. In anticipation of a barrage of bursts expected from future FRB surveys, we provide a simple framework for statistical association of FRBs with afterglows. Our framework properly accounts for statistical uncertainties, and ensures consistency with limits set by slow-transient surveys.Comment: Accepted version (ApJL

Lattice thermal conductivity of self-assembled PbTe-Sb_2Te_3 composites with nanometer lamellae

In the system of PbTe and Sb_2Te_3, a metastable compound Pb_2Sb_6Te_(11) appears by solidification processing. It has been reported that this compound is decomposed into the two immiscible thermoelectric materials forming nanosized lamellar structure by heat treatments. The fraction transformed and the inter-lamellar spacing was systematically investigated. In this work, the thermal conductivities and the electrical resistivities have been measured as functions of annealing time through the transformation and the coarsening processes to clarify the effect of the fraction transformed and the inter-lamellar spacing. The thermal conductivity of Pb_2Sb_6Te_(11) is lower than that after the decomposition. The lattice part of the thermal conductivity of PbTe/Sb_2Te_3 lamellar samples decreases with decreasing inter-lamellar spacing. This is considered to be due to the coarsening of the microstructure

ChemInform Abstract: A Facile Synthesis of N‐Z/Boc‐Protected 1,3,4‐Oxadiazole‐Based Peptidomimetics Employing Peptidyl Thiosemicarbazides.

A convenient protocol is presented for the cyclization of dipeptidyl thiosemicarbazides (III)

IR Studies of Impurities in In-Se-Tl Bulk Chalcogenide Glassy System

Chalcogenide glasses with composition In10Se90-xTlx (7≤x≤15) and In15Se85-xTlx (2≤x≤10) are synthesized by melt quenching technique. The FT-IR transmission spectroscopy studies using KBr pellet method in the wavelength range 400-4000 cm-1 has been carried out. The In-Se-Tl glasses studies shows good transparency in the entire spectral range. There is an increase in percentage of transmittance values with increase in the Tl content. In the transmittance curve various absorption bands are seen, which are related to chemical bonds of different extrinsic impurities present in the glassy material. The vibrational properties of the impurities in the powdered samples are measured. Vibrational modes attributed to O-H hydroxyl groups, molecular H2O and carbon impurity atoms were detected in the mid-IR spectra

Effect Of Thallium Additive On Heat Capacities Of In-Se Bulk Chalcogenide Glasses

Chalcogenide glasses are promising materials for optoelectronic device applications. Heat capacity of such materials is the essential physical parameter to estimate the energy/data storage capacity. In the present work, the effect of Tl incorporation on heat capacities ΔCpg, ΔCpc and ΔCpm of In10Se90-xTl x (7≤x≤15) and In15Se85-xTlx (2≤x≤10) bulk glasses have been investigated by analyzing the Differential scanning calorimetry (DSC) thermogram plots. Composition dependence of heat capacities of In-Se-Tl glassy systems have been obtained at the peaks of the glass transitions, crystallizations and melting temperatures (Tg, Tc and Tm). It is found that the heat capacities of In10Se90-xTl x and In15Se85-xTlx glasses increases initially with the incorporation of thallium (up to x≤13 and x≤6) and reaches to maximum at x=13 and x=6 respectively beyond which it decreases. This behavior seems to follow the change in network connectivity and rigidity and may be explained with the help of chemical bond theory of solids. Further in these glassy materials, at the average coordination =2.46 (x=13) and = 2.42 (x=6) a sharp slope change is seen in the composition dependence of heat capacity of both the series which is attributed to the rigidity percolation threshold

A Three Dimensional Lattice of Ion Traps

We propose an ion trap configuration such that individual traps can be stacked together in a three dimensional simple cubic arrangement. The isolated trap as well as the extended array of ion traps are characterized for different locations in the lattice, illustrating the robustness of the lattice of traps concept. Ease in the addressing of ions at each lattice site, individually or simultaneously, makes this system naturally suitable for a number of experiments. Application of this trap to precision spectroscopy, quantum information processing and the study of few particle interacting system are discussed.Comment: 4 pages, 4 Figures. Fig 1 appears as a composite of 1a, 1b, 1c and 1d. Fig 2 appears as a composite of 2a, 2b and 2

First Report of Fusarium proliferatum Causing Rot of Onion Bulbs (Allium cepa L.) in India

A rot disease was observed on onion bulbs in major growing areas of Kadapa and Kurnool districts of Andhra Pradesh, India during 2010 to 2012. Based on pathogenicity, morphology and ribosomal DNA spacer sequences, the pathogen was identified as Fusarium proliferatum (Matsushima) Nirenberg. The fungus was isolated from onion bulbs presenting purple and reddish lesions, obtaining F. proliferatum consistently. The fungus produced effuse white colonies, branched hyphae, short conidiophores, slightly curved macroconidia, and single celled microconidia measuring 5.6-10.5 X 2.0-3.5 μm in diameter. Morphological identification of the fungus was confirmed using ribosomal DNA sequence data. Kotch’s postulates were confirmed by performing pathogenicity test on healthy onion bulbs. This is the first report of F. proliferatum causing rot disease on onion bulbs in India; although it had already been reported for onion in the USA and Serbia.Keywords: Onion bulbs; Rot disease; Fusarium proliferatum; Pathogenicity; rDNA - IT