File Secrecy in a Multi-User Environment

This paper deals with a method that provides in a multi-user environment file security of the order that even the system's people will be unable to break. The technique dealt with here is ASCII character by character encrypting of file using a KEY that is not physically stored anywhere in the magnetic media. This paper also covers problems encountered in the computer environment when using this technique

Estimating standard errors for importance sampling estimators with multiple Markov chains

The naive importance sampling estimator based on the samples from a single importance density can be extremely numerically unstable. We consider multiple distributions importance sampling estimators where samples from more than one probability distributions are combined to consistently estimate means with respect to given target distributions. These generalized importance sampling estimators provide more stable estimators than the naive importance sampling estimators. Importance sampling estimators can also be used in the Markov chain Monte Carlo (MCMC) context, that is, where iid samples are replaced with positive Harris Markov chains with invariant importance distributions. If these Markov chains converge to their respective target distributions at a geometric rate, then under two finite moment conditions a central limit theorem (CLT) holds for the importance sampling estimators. In order to calculate valid asymptotic standard errors, it is required to consistently estimate the asymptotic variance in the CLT. Recently Tan and Doss and Hobert (2015) developed an approach based on regenerative simulation for obtaining consistent estimators of the asymptotic variance. It is well-known that in practice it is often difficult to construct a useful minorization condition that is required in Tan and Doss and Hobert ’s (2015) regenerative simulation method. We provide an alternative estimator for these standard errors based on the easy to implement batch means methods. The multi-chain importance sampling estimators depend on Geyer’s (1994) reverse logistic estimator (of ratios of normalizing constants) which has wide applications, in its own right, in both frequentist and Bayesian inference. We also provide batch means estimator for calculating asymptotically valid standard errors of Geyer’s (1994) reverse logistic estimator. We illustrate the method with an application in Bayesian variable selection in linear regression. In particular, the multi-chain importance sampling estimator is used to perform empirical Bayes variable selection and the batch means estimator is used to obtain standard errors in the large p situation where regenerative method is not applicable

Android App for Argo Floats

INCOIS has deployed more than 400 Argo floats till now and soon reaching a special milestone of 500 Indian Argo floats. In this context there is a necessity to have a unique application by which scientists can effectively and efficiently track all the information of these floats and also monitor the active floats among them regularly. The present work describes about an Android application or app which eases the work of researchers to track the information of these Argo floats as well as monitor them regularly. This app is designed and developed to give all the information related to Argo floats like its various types, its deployed positions, its current positions, its functionality, search option, etc., in the form of maps and charts in turn uses real time data to give latest status of Argo floats. In addition to it, this app is also useful in advising the scientists involved in Argo program about the floats in danger of getting grounded or beached that need immediate attention. This app is a very useful tool for the scientists to check the current status of Argo floats from anywhere or anytime using a smart phone

Detection of pathological high-frequency oscillations in refractory epilepsy patients undergoing simultaneous stereo-electroencephalography and magnetoencephalography

BACKGROUND: Stereo-electroencephalography (SEEG) and magnetoencephalography (MEG) have generally been used independently as part of the pre-surgical evaluation of drug-resistant epilepsy (DRE) patients. However, the possibility of simultaneously employing these recording techniques to determine whether MEG has the potential of offering the same information as SEEG less invasively, or whether it could offer a greater spatial indication of the epileptogenic zone (EZ) to aid surgical planning, has not been previously evaluated. METHODS: Data from 24 paediatric and adult DRE patients, undergoing simultaneous SEEG and MEG as part of their pre-surgical evaluation, was analysed employing manual and automated high-frequency oscillations (HFOs) detection, and spectral and source localisation analyses. RESULTS: Twelve patients (50%) were included in the analysis (4 males; mean age=25.08 years) and showed interictal SEEG and MEG HFOs. HFOs detection was concordant between the two recording modalities, but SEEG displayed higher ability of differentiating between deep and superficial epileptogenic sources. Automated HFO detector in MEG recordings was validated against the manual MEG detection method. Spectral analysis revealed that SEEG and MEG detect distinct epileptic events. The EZ was well correlated with the simultaneously recorded data in 50% patients, while 25% patients displayed poor correlation or discordance. CONCLUSIONS: MEG recordings can detect HFOs, and simultaneous use of SEEG and MEG HFO identification facilitates EZ localisation during the presurgical planning stage for DRE patients. Further studies are necessary to validate these findings and support the translation of automated HFO detectors into routine clinical practice

Smart Cities: An In-Depth Study of AI Algorithms and Advanced Connectivity

The goal of smart city development is to improve the quality of life by incorporating technology into daily activities. Artificial intelligence (AI) is critical to the ongoing development of future smart cities. The Internet of Things (IoT) idea connects every internet-enabled device for improved access and control. AI in various domains has changed ordinary towns into highly equipped smart cities. Machine learning and deep learning algorithms have proven indispensable in a variety of industries, and they are now being implemented into smart city concepts to automate and improve urban activities and operations on a large scale. IoT and machine learning technology are frequently used in smart cities to collect data from various sources. This article delves deeply into the significance, scope, and developments of AI-based smart cities. It also addresses some of the difficulties and restrictions associated with smart cities powered by AI. The goal of the study is to inspire and encourage academics to create original smart city solutions based on AI technologies

Ammonia: what adult neurologists need to know

Hyperammonaemia is often encountered in acute neurology and can be the cause of acute or chronic neurological symptoms. Patients with hyperammonaemia may present with seizures or encephalopathy, or may be entirely asymptomatic. The underlying causes are diverse but often straightforward to diagnose, although sometimes require specialist investigations. Haemodialysis or haemo(dia)filtration is the first-line treatment for acute severe hyperammonaemia (of any cause) in an adult. Here we discuss our approach to adult patients with hyperammonaemia identified by a neurologist

Preparation of dissociated mouse primary neuronal cultures from long-term cryopreserved brain tissue

BACKGROUND: Dissociated primary neuronal cultures are widely used as a model system to investigate the cellular and molecular properties of diverse neuronal populations and mechanisms of action potential generation and synaptic transmission. Typically, rodent primary neuronal cultures are obtained from freshly-dissociated embryonic or postnatal brain tissue, which often requires intense animal husbandry. This can strain resources when working with genetically modified mice. NEW METHOD: Here we describe an experimental protocol for frozen storage of mouse hippocampi, which allows fully functional dissociated primary neuronal cultures to be prepared from cryopreserved tissue. RESULTS: We show that thawed hippocampal neurons have functional properties similar to those of freshly dissociated neurons, including neuronal morphology, excitability, action potential waveform and synaptic neurotransmitter release, even after cryopreservation for several years. COMPARISON TO THE EXISTING METHODS: In contrast to the existing methods, the protocol described here allows for efficient long-term storage of samples, allowing researchers to perform functional experiments on neuronal cultures from brain tissue collected in other laboratories. CONCLUSIONS: We anticipate that this method will facilitate collaborations among laboratories based at distant locations and will thus optimise the use of genetically modified mouse models, in line with the 3Rs (Replacement, Reduction and Refinement) recommended for scientific use of animals in research

Case Report of Fibrodysplasia Ossificans Progressiva

Fibrodysplasia ossificans progressiva is a rare genetic disease characterized by widespread soft tissue ossification and congenital stigmata of the extremities. We report a male patient who had bilateral hallux valgus since birth. Other noticed anomalies included multiple swellings over the back, stiffness of lower back area, multiple joints, restricting movement of spine, shoulders, elbows, and right hip and right knee. Patient was not able to bend forward, squat or turn head to either side. Patient also had multiple foci of ossification developed over left knee, and back region. All swellings and restrictions were painless