Smart Metro - Rail System

Railway transport system has proved to be a very sturdy and convenient mode of transport over the centuries. It still serves as the economic and most efficient means of mass transport in many countries. It is a widespread practice even today that most operations are manually carried out, leading to several dangerous accidents and mismanagement of the system. When it comes to the matter of scores of lives, error margin is of utmost importance to ensure an efficient and safe mode of travel. There is an utter need for a system that provides automation of the critical systems that play a pivotal role in the smooth functioning. The focus remains on certain key functions including locomotion, data logging for position, speed and health of he locomotive. This can increase the safety levels, while also reducing the time for relief in-case of unfortunate emergencies

Spectral signatures of reorganised brain networks in disorders of consciousness.

Theoretical advances in the science of consciousness have proposed that it is concomitant with balanced cortical integration and differentiation, enabled by efficient networks of information transfer across multiple scales. Here, we apply graph theory to compare key signatures of such networks in high-density electroencephalographic data from 32 patients with chronic disorders of consciousness, against normative data from healthy controls. Based on connectivity within canonical frequency bands, we found that patient networks had reduced local and global efficiency, and fewer hubs in the alpha band. We devised a novel topographical metric, termed modular span, which showed that the alpha network modules in patients were also spatially circumscribed, lacking the structured long-distance interactions commonly observed in the healthy controls. Importantly however, these differences between graph-theoretic metrics were partially reversed in delta and theta band networks, which were also significantly more similar to each other in patients than controls. Going further, we found that metrics of alpha network efficiency also correlated with the degree of behavioural awareness. Intriguingly, some patients in behaviourally unresponsive vegetative states who demonstrated evidence of covert awareness with functional neuroimaging stood out from this trend: they had alpha networks that were remarkably well preserved and similar to those observed in the controls. Taken together, our findings inform current understanding of disorders of consciousness by highlighting the distinctive brain networks that characterise them. In the significant minority of vegetative patients who follow commands in neuroimaging tests, they point to putative network mechanisms that could support cognitive function and consciousness despite profound behavioural impairment.This work was supported by grants from the Wellcome Trust [WT093811MA to T.B.]; the James S. McDonnell Foundation [to A.M.O. and J.D.P.]; the UK Medical Research Council [U.1055.01.002.00001.01 to A.M.O. and J.D.P.]; the Canada Excellence Research Chairs program [to A.M.O.]; the National Institute for Health Research Cambridge Biomedical Research Centre [to J.D.P.]; and the National Institute for Health Research Senior Investigator and Healthcare Technology Cooperative awards [to J.D.P.].This is the final version of the article. It first appeared from PLOS via http://dx.doi.org

Genome-Wide Association Data Reveal a Global Map of Genetic Interactions among Protein Complexes

This work demonstrates how gene association studies can be analyzed to map a global landscape of genetic interactions among protein complexes and pathways. Despite the immense potential of gene association studies, they have been challenging to analyze because most traits are complex, involving the combined effect of mutations at many different genes. Due to lack of statistical power, only the strongest single markers are typically identified. Here, we present an integrative approach that greatly increases power through marker clustering and projection of marker interactions within and across protein complexes. Applied to a recent gene association study in yeast, this approach identifies 2,023 genetic interactions which map to 208 functional interactions among protein complexes. We show that such interactions are analogous to interactions derived through reverse genetic screens and that they provide coverage in areas not yet tested by reverse genetic analysis. This work has the potential to transform gene association studies, by elevating the analysis from the level of individual markers to global maps of genetic interactions. As proof of principle, we use synthetic genetic screens to confirm numerous novel genetic interactions for the INO80 chromatin remodeling complex

Detecting Awareness in the Vegetative State: Electroencephalographic Evidence for Attempted Movements to Command

Patients in the Vegetative State (VS) do not produce overt motor behavior to command and are therefore considered to be unaware of themselves and of their environments. However, we recently showed that high-density electroencephalography (EEG) can be used to detect covert command-following in some VS patients. Due to its portability and inexpensiveness, EEG assessments of awareness have the potential to contribute to a standard clinical protocol, thus improving diagnostic accuracy. However, this technique requires refinement and optimization if it is to be used widely as a clinical tool. We asked a patient who had been repeatedly diagnosed as VS for 12-years to try to move his left and right hands, between periods of rest, while EEG was recorded from four scalp electrodes. We identified appropriate and statistically reliable modulations of sensorimotor beta rhythms following commands to try to move, which could be significantly classified at a single-trial level. These reliable effects indicate that the patient attempted to follow the commands, and was therefore aware, but was unable to execute an overtly discernable action. The cognitive demands of this novel task are lower than those used previously and, crucially, allow for awareness to be determined on the basis of a 20-minute EEG recording made with only four electrodes. This approach makes EEG assessments of awareness clinically viable, and therefore has potential for inclusion in a standard assessment of awareness in the VS

Modular Verification of SRT Division

. We describe a formal specification and verification in PVS for the general theory of SRT division, and for the hardware design of a specific implementation. The specification demonstrates how attributes of the PVS language (in particular, predicate subtypes) allow the general theory to be developed in a readable manner that is similar to textbook presentations, while the PVS table construct allows direct specification of the implementation's quotient look-up table. Verification of the derivations in the SRT theory and for the data path and look-up table of the implementation are highly automated and performed for arbitrary, but finite precision; in addition, the theory is verified for general radix, while the implementation is specialized to radix 4. The effectiveness of the automation derives from PVS's tight integration of rewriting with decision procedures for equality, linear arithmetic over integers and rationals, and propositional logic. This example demonstrates t..

Accelerating invariant generation

Acceleration is a technique for summarising loops by computing a closed-form representation of the loop behaviour. The closed form can be turned into an accelerator, which is a code snippet that skips over intermediate states of the loop to the end of the loop in a single step. Program analysers rely on invariant generation techniques to reason about loops. The state-of-the-art invariant generation techniques, in practice, often struggle to find concise loop invariants, and, instead, degrade into unrolling loops, which is ineffective for non-trivial programs. In this paper, we evaluate experimentally whether loop accelerators enable existing program analysis algorithm to discover loop invariants more reliably and more efficiently. This paper is the first comprehensive study on the synergies between acceleration and invariant generation. We report our experience with a collection of safe and unsafe programs drawn from the Software Verification Competition and the literature

A Tutorial on Using PVS for Hardware Verification

PVS stands for "Prototype Verification System." It consists of a specification language integrated with support tools and a theorem prover. PVS tries to provide the mechanization needed to apply formal methods both rigorously and productively. This tutorial serves to introduce PVS and its use in the context of hardware verification. In the first section, we briefly sketch the purposes for which PVS is intended and the rationale behind its design, mention some of the uses that we and others are making of it. We give an overview of the PVS specification language and proof checker. The PVS language, system, and theorem prover each have their own reference manuals, which you will need to study in order to make productive use of the system. A pocket reference card, summarizing all the features of the PVS language, system, and prover is also available. The purpose of this tutorial is not to describe in detail the features of PVS and how to use the system. Rather, its purpose is to..

Accelerating invariant generation

Acceleration is a technique for summarising loops by computing a closed-form representation of the loop behaviour. The closed form can be turned into an accelerator, which is a code snippet that skips over intermediate states of the loop to the end of the loop in a single step. Program analysers rely on invariant generation techniques to reason about loops. The state-of-the-art invariant generation techniques, in practice, often struggle to find concise loop invariants, and, instead, degrade into unrolling loops, which is ineffective for non-trivial programs. In this paper, we evaluate experimentally whether loop accelerators enable existing program analysis algorithm to discover loop invariants more reliably and more efficiently. This paper is the first comprehensive study on the synergies between acceleration and invariant generation. We report our experience with a collection of safe and unsafe programs drawn from the Software Verification Competition and the literature