Alzheimer’s And Parkinson’s Disease Classification Using Deep Learning Based On MRI: A Review

Neurodegenerative disorders present a current challenge for accurate diagnosis and for providing precise prognostic information. Alzheimer’s disease (AD) and Parkinson's disease (PD), may take several years to obtain a definitive diagnosis. Due to the increased aging population in developed countries, neurodegenerative diseases such as AD and PD have become more prevalent and thus new technologies and more accurate tests are needed to improve and accelerate the diagnostic procedure in the early stages of these diseases. Deep learning has shown significant promise in computer-assisted AD and PD diagnosis based on MRI with the widespread use of artificial intelligence in the medical domain. This article analyses and evaluates the effectiveness of existing Deep learning (DL)-based approaches to identify neurological illnesses using MRI data obtained using various modalities, including functional and structural MRI. Several current research issues are identified toward the conclusion, along with several potential future study directions

Prompt emission polarimetry of Gamma Ray Bursts with ASTROSAT CZT-Imager

X-ray and Gamma-ray polarization measurements of the prompt emission of Gamma-ray bursts (GRBs) are believed to be extremely important for testing various models of GRBs. So far, the available measurements of hard X-ray polarization of GRB prompt emission have not significantly constrained the GRB models, particularly because of the difficulty of measuring polarization in these bands. The CZT Imager (CZTI) onboard {\em AstroSat} is primarily an X-ray spectroscopic instrument that also works as a wide angle GRB monitor due to the transparency of its support structure above 100 keV. It also has experimentally verified polarization measurement capability in the 100 $-$ 300 keV energy range and thus provides a unique opportunity to attempt spectro-polarimetric studies of GRBs. Here we present the polarization data for the brightest 11 GRBs detected by CZTI during its first year of operation. Among these, 5 GRBs show polarization signatures with $\gtrapprox$3$\sigma$, and 1 GRB shows $\>$2$\sigma$ detection significance. We place upper limits for the remaining 5 GRBs. We provide details of the various tests performed to validate our polarization measurements. While it is difficult yet to discriminate between various emission models with the current sample alone, the large number of polarization measurements CZTI expects to gather in its minimum lifetime of five years should help to significantly improve our understanding of the prompt emission.Comment: Accepted for Publication in ApJ ; a figure has been update

Analytical Study of Base Isolation- A Review

Now a days the rate of happening of seismic events increasing and due to that so many structures got collapsed or damaged. In order to reduce the damage to structures during earthquakes, now a days the base isolation system is widely adopted and used over the world. This paper makes a wide review on the various base isolation techniques adopted and used. Different types of isolating bearings and materials used in it are reviewed. Here the review is done for the isolation system in normal R.C buildings (regular and irregular in plan) and also for bridges. The effect of base isolation system on some historic structures is also reviewed. The various advantages and disadvantages of different isolating bearings are reviewed. Here the effect of temperature on some isolating devices are also reviewed

Time-varying polarized gamma-rays from GRB 160821A: evidence for ordered magnetic fields

GRB 160821A is the third most energetic gamma-ray burst observed by the Fermi gamma-ray space telescope. Based on the observations made by the Cadmium Zinc Telluride Imager on board AstroSat, here we report the most conclusive evidence to date of (i) high linear polarization ( detection), and (ii) variation of polarization angle with time, occurring twice during the rise and decay phase of the burst at 3.5σ and 3.1σ detections, respectively. All confidence levels are reported for two parameters of interest. These observations strongly suggest synchrotron radiation produced in magnetic field lines that are highly ordered on angular scales of 1/Γ, where Γ is the Lorentz factor of the outflow

A Tale of Two Transients: GW 170104 and GRB 170105A

We present multi-wavelength follow-up campaigns by the AstroSat CZTI and GROWTH collaborations in search of an electromagnetic counterpart to the gravitational wave event GW 170104. At the time of the GW 170104 trigger, the AstroSat CZTI field of view covered 50.3% of the sky localization. We do not detect any hard X-ray (>100 keV) signal at this time, and place an upper limit of $\approx 4.5\times {10}^{-7}\,\mathrm{erg}\,{\mathrm{cm}}^{-2}\,{{\rm{s}}}^{-1}$, for a 1 s timescale. Separately, the ATLAS survey reported a rapidly fading optical source dubbed ATLAS17aeu in the error circle of GW 170104. Our panchromatic investigation of ATLAS17aeu shows that it is the afterglow of an unrelated long, soft GRB 170105A, with only a fortuitous spatial coincidence with GW 170104. We then discuss the properties of this transient in the context of standard long GRB afterglow models

AN INSIGHT ON ALGAL CELL DISRUPTION FOR BIODIESEL PRODUCTION

 Objective: This review article deals with the effect that various cell disruption techniques have on the efficiency of lipid extraction. We have reviewed existing algal cell disruption techniques that aid the biodiesel production process.Methods: Current rise in demand for energy has led the researcher to focus on the production of sustainable fuels, among which biodiesel has received greater attention. This is due to its larger lipid content, higher growth rate, larger biomass production, and lower land use. Extraction of lipid from algae (micro and macro) for the production of biodiesel involves numerous downstream processing steps, of which cell wall disruption is a crucial step. Bead milling, high-pressure homogenization, ultra-sonication, freeze-drying, acid treatment, and enzymatic lysis are some methods of cell disruption. The cell disruption technique needs to be optimized based on the structure and biochemical composition of algae.Result: The lipid extraction efficiency varies depending on the algal species and the cell disruption technique used.Conclusion: In-depth research and development of new techniques are required to further enhance the cell disruption of the algal cell wall for the enhanced recovery of lipids. In addition, the operating costs and energy consumption should also be optimized for the cost-effective recovery

A Machine Learning Way to Classify Autism Spectrum Disorder

In recent times Autism Spectrum Disorder (ASD) is picking up its force quicker than at any other time. Distinguishing autism characteristics through screening tests is over the top expensive and tedious. Screening of the same is a challenging task, and classification must be conducted with great care. Machine Learning (ML) can perform great in the classification of this problem. Most researchers have utilized the ML strategy to characterize patients and typical controls, among which support vector machines (SVM) are broadly utilized. Even though several studies have been done utilizing various methods, these investigations didn't give any complete decision about anticipating autism qualities regarding distinctive age groups. Accordingly, this paper plans to locate the best technique for ASD classi-fication out of SVM, K-nearest neighbor (KNN), Random Forest (RF), Naïve Bayes (NB), Stochastic gradient descent (SGD), Adaptive boosting (AdaBoost), and CN2 Rule Induction using 4 ASD datasets taken from UCI ML repository. The classification accuracy (CA) we acquired after experimentation is as follows: in the case of the adult dataset SGD gives 99.7%, in the adolescent dataset RF gives 97.2%, in the child dataset SGD gives 99.6%, in the toddler dataset Ada-Boost gives 99.8%. Autism spectrum quotients (AQs) varied among several sce-narios for toddlers, adults, adolescents, and children that include positive predic-tive value for the scaling purpose. AQ questions referred to topics about attention to detail, attention switching, communication, imagination, and social skills

Hypopituitarism as unusual sequelae to central nervous system tuberculosis

Neurological tuberculosis can very rarely involve the hypophysis cerebri. We report a case of an eighteen year old female who presented with five months duration of generalised apathy, secondary amenorrhea and weight gain. She was on irregular treatment for tuberculosis of the central nervous system for the last five months. Neuroimaging revealed sellar and suprasellar tuberculomas and communicating hydrocephalus requiring emergency decompression. Endocrinological investigation showed hypopituitarism manifesting as pituitary hypothyroidism, hypocortisolism, hypogonadotropic hypogonadism, and hyperprolactinemia. Restarting anti-tuberculosis treatment, hormone replacement therapy, and a ventriculo-peritoneal shunt surgery led to remarkable improvement in the general condition of the patient