Abstract:
Human navigation has been of interest to psychologists and cognitive scientists since the past few decades. It was in the recent past that a study of human navigational strategies was initiated with a network analytic approach, instigated mainly by Milgrams small world experiment. We brief the work in this direction and provide answers to the algorithmic questions raised by the previous study. It is noted that humans have a tendency to navigate using centers of the network - such paths are called the center-strategic-paths. We show that the problem of finding a center-strategic-path is an easy one. We provide a polynomial time algorithm to find a center-strategic-path between a given pair of nodes. We apply our finding in empirically checking the navigability on synthetic networks and analyze few special types of graphs.

Abstract:
Human navigation has been a topic of interest in spatial cognition from the past few decades. It has been experimentally observed that humans accomplish the task of way-finding a destination in an unknown environment by recognizing landmarks. Investigations using network analytic techniques reveal that humans, when asked to way-find their destination, learn the top ranked nodes of a network. In this paper we report a study simulating the strategy used by humans to recognize the centers of a network. We show that the paths obtained from our simulation has the same properties as the paths obtained in human based experiment. The simulation thus performed leads to a novel way of path-finding in a network. We discuss the performance of our method and compare it with the existing techniques to find a path between a pair of nodes in a network.

Abstract:
The current paper is an investigation towards understanding the navigational performance of humans on a network when the "landmark" nodes are blocked. We observe that humans learn to cope up, despite the continued introduction of blockages in the network. The experiment proposed involves the task of navigating on a word network based on a puzzle called the wordmorph. We introduce blockages in the network and report an incremental improvement in performance with respect to time. We explain this phenomenon by analyzing the evolution of the knowledge in the human participants of the underlying network as more and more landmarks are removed. We hypothesize that humans learn the bare essentials to navigate unless we introduce blockages in the network which would whence enforce upon them the need to explore newer ways of navigating. We draw a parallel to human problem solving and postulate that obstacles are catalysts for humans to innovate techniques to solve a restricted variant of a familiar problem.

Abstract:
Centrality measures, erstwhile popular amongst the sociologists and psychologists, have seen wide and increasing applications across several disciplines of late. In conjunction with the big data problems there came the need to analyze big networks and in this connection, centrality measures became of great interest to the community of mathematicians, computer scientists and physicists. While it is an important question to ask how one can rank vertices based on their importance in a network, there hasn't been a commonly accepted definition, mainly due to the subjectivity of the term "importance". Amongst a plethora of application specific definitions available in the literature to rank the vertices, closeness centrality, betweenness centrality and eigenvector centrality (page-rank) have been the most important and widely applied ones. In the current paper, we formulate a method to determine the betweenness ordering of $k$ vertices without exactly computing their betweenness indices - which is a daunting task for networks of large size. The method results very efficient ordering even when runs for linear time in the number of edges. We apply our approach to find the betweenness ordering of $k$ vertices in several synthetic and real world graphs. We compare our method with the available techniques in the literature and show that our method fares several times better than the currently known techniques. We further show that the accuracy of our algorithm gets better with the increase in size and density of the network.

Abstract:
Representation of intracellular signaling networks as directed graphs allows for the identification of regulatory motifs. Regulatory motifs are groups of nodes with the same connectivity structure, capable of processing information. The bifan motif, made of two source nodes directly cross-regulating two target nodes, is an over-represented motif in a mammalian cell signaling network and in transcriptional networks. One example of a bifan is the two MAP-kinases, p38 and JNK that phosphorylate and activate the two transcription factors ATF2 and Elk-1. We have used a system of coupled ordinary differential equations to analyze the regulatory capability of this bifan motif by itself, and when it interacts with other motifs such as positive and negative feedback loops. Our results indicate that bifans provide temporal regulation of signal propagation and act as signal sorters, filters, and synchronizers. Bifans that have OR gate configurations show rapid responses while AND gate bifans can introduce delays and allow prolongation of signal outputs. Bifans that are AND gates can filter noisy signal inputs. The p38/JNK-ATF2/Elk-1bifan synchronizes the output of activated transcription factors. Synchronization is a robust property of bifans and is exhibited even when the bifan is adjacent to a positive feedback loop. The presence of the bifan promotes the transcription and translation of the dual specificity protein phosphatase MKP-1 that inhibits p38 and JNK thus enabling a negative feedback loop. These results indicate that bifan motifs in cell signaling networks can contribute to signal processing capability both intrinsically and by enabling the functions of other regulatory motifs.

Abstract:
The Betweenness Centrality index is a very important centrality measure in the analysis of a large number of networks. Despite its significance in a lot of interdisciplinary applications, its computation is very expensive. The fastest known algorithm presently is by Brandes which takes O(|V || E|) time for computation. In real life scenarios, it happens very frequently that a single vertex or a set of vertices is sequentially removed from a network. The recomputation of Betweenness Centrality on removing a single vertex becomes expensive when the Brandes algorithm is repeated. It is to be understood that as the size of the network increases, Betweenness Centrality calculation becomes more and more expensive and even a decrease in running time by a small fraction results in a phenomenal decrease in the actual running time. The algorithm introduced in this paper achieves the same in a significantly lesser time than repetition of the Brandes algorithm. The algorithm can also be extended to a general case.

Abstract:
Most of the networks observed in real life obey power-law degree distribution. It is hypothesized that the emergence of such a degree distribution is due to preferential attachment of the nodes. Barabasi-Albert model is a generative procedure that uses preferential attachment based on degree and one can use this model to generate networks with power-law degree distribution. In this model, the network is assumed to grow one node every time step. After the evolution of such a network, it is impossible for one to predict the exact order of node arrivals. We present in this article, a novel strategy to partially predict the order of node arrivals in such an evolved network. We show that our proposed method outperforms other centrality measure based approaches. We bin the nodes and predict the order of node arrivals between the bins with an accuracy of above 80%.

Abstract:
SNAVI is Windows-based desktop application that implements standard network analysis methods to compute the clustering, connectivity distribution, and detection of network motifs, as well as provides means to visualize networks and network motifs. SNAVI is capable of generating linked web pages from network datasets loaded in text format. SNAVI can also create networks from lists of gene or protein names.SNAVI is a useful tool for analyzing, visualizing and sharing cell signaling data. SNAVI is open source free software. The installation may be downloaded from: http://snavi.googlecode.com webcite. The source code can be accessed from: http://snavi.googlecode.com/svn/trunk webciteInteractions between signaling pathways in mammalian cells indicate that a large-scale complex network of interactions is involved in determining and controlling cellular phenotype [1-3]. To visualize and analyze these complex networks, the biochemical networks may be abstracted to directed graphs [4]. To understand the topology of such networks, graph-theory methodologies can be applied to analyze networks' global and local structural properties [5]. Additionally, the value of assembled network datasets is enhanced with network visualization software and web-based information systems. These systems provide summary information, order, and logic for interpretation of sparse experimental results [6,7]. Visualization tools and web-based navigation systems provide an integrative resource that aids in understanding the system under investigation and may lead to the development of new hypotheses.Graph-theory methods have been used in other scientific fields to analyze complex systems abstracted to networks. For example, Watts and Strogatz [8] defined a measure called the "clustering coefficient" (CC) for characterizing the level of clustered interactions within networks by measuring the abundance of triangles in networks (three interactions among three components). For instance, if a node has four

Abstract:
Sorption and desorption mechanisms of lead (Pb) were determined in four different soils collected from different agro-climatic regions of India. The soils were classified as: fine loamy mixed Typic- Dystrudepts, fine sandy loam Typic Ustochrepts, fine loamy Typic Ustochrept, and fine sandy loam Udic Haplustalfs. Seven different Pb solutions [Pb(NO3)2 dissolved in 0.01M Ca(NO3)2] in a range of 400 to 2000µgL-1 were applied to study the sorption amounts at 25(±2)oC and 45(±2)oC temperatures. With the increase in application rate and tempera-ture, sorption amounts of Pb increased; however, percentages of sorption of applied Pb were decreased. Sorptions were positively and significantly (p≤0.01) correlated with Langmuir adsorption isotherm. Thermodynamic parameters of sorption (i.e. Ko, ?Go, ?Ho, and ?So) were also determined at two tempera-tures, 25(±2)oC and 45(±2)oC. Increase in Ko with the increase in temperature indicated positive effect of temperature on Pb sorption. High absolute values of ?Go, and positive values of ?Ho, and ?So suggested that the sorption reaction was spontaneous and en-dothermic. Sorbed Pb were desorbed in Pb free 0.01M Ca(NO3)2 solutions at 25(±2)oC and 45(±2)oC. Desorption amounts increased with increase in the Pb application rate, but not always with the increase in temperature.

Abstract:
Anterior Cervical Discectomy and Fusion (ACDF) currently remains as the gold standard treatment for cervical disc herniation and Degenerative Disc Disease (DDD) refractory to conservative management. Even though anterior cervical fusion provides excellent clinical results, it has been implicated in abnormal kinematic strain on adjacent disc level resulting in symptomatic adjacent segment disease. Anterior cervical disc replacement (ACDR) is an alternative procedure to anterior cervical discectomy and fusion. The aims of cervical disc replacement were to preserve the motion at the index level and to protect the adjacent levels from accelerated symptomatic degeneration. The aim of this systematic review was to evaluate the outcomes of cervical disc replacement published in MEDLINE indexed literature. A literature search was carried out in medical electronic database MEDLINE. Keywords used for the search were Cervical vertebrae, Cervical spine, Neck, Intervertebral disc, Total disc replacement, Arthroplasty, Replacement, Treatment outcome. Two authors reviewed titles and abstracts of all two hundred and thirty six hits. The articles that satisfied the inclusion criteria were critically appraised while remaining articles were discarded. Anterior cervical disc replacement is a relatively new technology in spinal surgery.There are several short and intermediate term follow-up studies to prove the safety and efficacy of ACDR with satisfactory clinical and radiological outcomes. More intermediate to long-term follow-up studies are needed to prove the safety and efficacy of ACDR.