Background: The aim of this randomized prospective study was to evaluate the management protocol decided in the cases of Traumatic optic neuropathy. Subjects and Methods: All the cases with a diagnosis of Traumatic optic neuropathy were managed using medical management with the steroids and cases not responding were operated upon by transnasal trans sphenoidal optic nerve decompression and the results were evaluated. Results: Patients presenting early and those who were operated early in the course of their illness showed a better recovery. Conclusion: Early intervention and following a defined management protocol can help preventing the blindness in as many as 80% of the cases following the injury.
A wide range of social, technological and communication systems can be described as complex networks. Scale-free networks are one of the well known classes of complex networks in which nodes' degrees follow a power-law distribution. The design of scalable, adaptive and resilient routing schemes in such networks is very challenging. In this article we present an overview of required routing functionality, categorize the potential design dimensions of routing protocols among existing routing schemes, and analyze experimental results and analytical studies performed so far to identify the main trends/trade-offs and draw main conclusions. Besides traditional schemes such as hierarchical/shortest-path path-vector routing, the article pays attention to advances in compact routing and geometric routing since they are known to significantly improve scalability in terms of memory space. The identified trade-offs and the outcomes of this overview enable more careful conclusions regarding the (un-)suitability of different routing schemes to large-scale complex networks and provide a guideline for future routing research. IntroductIonComplex networks refer to large, dynamic networks consisting of potentially billions of nodes and links that are used to describe a wide range of social, biological, technological and communication systems. Scale-free networks as one well known/much studied class of complex networks have degree distribution 1 that follows a power-law function. In such networks, new nodes attach preferentially to already well-connected nodes. The network of autonomous systems 2 (ASes) forming the core of the Internet graph, is an example of such networks. 3 Routing 4 in these networks is challenging because of the size of the network, and the properties and performance expected from these networks, particularly, anyto-any connectivity, availability, and reliability.Routing research has evolved very pragmatically in communication networks from small scale to larger scale in technologies including wireless, ad-hoc/sensor networks, the Internet, and so on.Since new networks of increasing scale are popping up every day (e.g., Internet of Things), it is important to consider clean-slate approaches considering the entire design space of routing paradigms to avoid getting "trapped" again in legacy protocols/paradigms. In this article we try to open this design question by clearly and cautiously categorizing/grouping the potential design dimensions of routing protocols among existing routing schemes (traditional schemes as well as novel ones), analyzing experimental results performed so far, and drawing some main conclusions, guidelines and open challenges for routing schemes in future settings.This article synthesizes the fundamental aspects of routing schemes for complex networks, as well as lessons learned from experimental routing research stemming from the EULER project (http://www.euler-fire-project.eu/). Particular attention will be given to:• New classes of path-based routing schemes 5 .• New routing par...
This chapter surveys routing algorithms in Euclidean, virtual, and hyperbolic space for wireless sensor networks that use geometric structures for route decisions. Wireless sensor networks have a unique geographic nature as the sensor nodes are embedded and designed for employing in the geographic space. Thus, the various geometric abstractions of the network can be used for routing algorithm design, which can provide scalability and efficiency. This chapter starts with the importance and impulse of the geographical routing in wireless sensor networks that exploits location information of the nodes to determine the alternatives of the next hop node on the desired routing path. The scalability of geographical routing encourages more effort on the design of virtual coordinates system, with which geographical routing algorithms are built up and applied to route data packets in the network. The geometry of large sensor network motivates to calculate geometric abstractions in hyperbolic space. Thus the challenge is to embed the network virtually or hyperbolically, which affects the performance and efficiency in the geographical message delivery.
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