Leveraging Friendship Networks for Dynamic Link Prediction in Social Interaction Networks

On-line social networks (OSNs) often contain many different types of relationships between users. When studying the structure of OSNs such as Facebook, two of the most commonly studied networks are friendship and interaction networks. The link prediction problem in friendship networks has been heavily studied. There has also been prior work on link prediction in interaction networks, independent of friendship networks. In this paper, we study the predictive power of combining friendship and interaction networks. We hypothesize that, by leveraging friendship networks, we can improve the accuracy of link prediction in interaction networks. We augment several interaction link prediction algorithms to incorporate friendships and predicted friendships. From experiments on Facebook data, we find that incorporating friendships into interaction link prediction algorithms results in higher accuracy, but incorporating predicted friendships does not when compared to incorporating current friendships.Comment: To appear in ICWSM 2018. This version corrects some minor errors in Table 1. MATLAB code available at https://github.com/IdeasLabUT/Friendship-Interaction-Predictio

Emperipolesis in a Case of Adult T Cell Lymphoblastic Lymphoma (Mediastinal type)-Detected at FNAC and Imprint Cytology

Emperipolesis is a condition in which viable hematopoetic cells are seen intact in the cytoplasm of host cell without damage. This phenomenon is seen in many physiologic and pathologic conditions, its presence in Rosai Dorfman disease (RDD) is characteristic of the disease. However emperipolesis is an uncommon finding in malignant lymphoma both Hodgkins and non-Hodgkin’s lymphoma, wherein it has been described in bone marrow aspirate and tissue culture. In contrast there are only two case reports of emperipolesis phenomenon described in non-Hodgkin’s lymphoma in tissue sections. We report a case of an adult T cell lymphoblastic lymphoma (mediastinal type) with features of emperipolesis demonstrated at fine needle aspiration cytology (FNAC) and imprint cytology of cervical lymph nodes. To our knowledge, this is the first case report of emperipolesis in a case of adult T cell lymphoblastic lymphoma (mediastinal type)-detected at FNAC and imprint cytology

Transferable neural networks for enhanced sampling of protein dynamics

Variational auto-encoder frameworks have demonstrated success in reducing complex nonlinear dynamics in molecular simulation to a single non-linear embedding. In this work, we illustrate how this non-linear latent embedding can be used as a collective variable for enhanced sampling, and present a simple modification that allows us to rapidly perform sampling in multiple related systems. We first demonstrate our method is able to describe the effects of force field changes in capped alanine dipeptide after learning a model using AMBER99. We further provide a simple extension to variational dynamics encoders that allows the model to be trained in a more efficient manner on larger systems by encoding the outputs of a linear transformation using time-structure based independent component analysis (tICA). Using this technique, we show how such a model trained for one protein, the WW domain, can efficiently be transferred to perform enhanced sampling on a related mutant protein, the GTT mutation. This method shows promise for its ability to rapidly sample related systems using a single transferable collective variable and is generally applicable to sets of related simulations, enabling us to probe the effects of variation in increasingly large systems of biophysical interest.Comment: 20 pages, 10 figure

Comparative development of sorghum, redgram and rice breeding population of Sitophilus oryzae (L.) feeding on cereals and split redgram dhal

Rice weevil Sitophilus oryzae (L.) mainly attacks whole grains such as wheat, corn, barley and rice and have been found actively breeding in such foods. The host range of S. oryzae now extended to split pulses. An experiment was carried out at the Entomology Laboratory, TNAU, Coimbatore during 2014-2015 to study the comparative development of sorghum, redgram and rice breeding population of S. oryzae feeding on cereals and split redgram dhal. The assessed parameters were survival percentage, per cent mortality and F1 progeny. The per cent mortality was higher in sorghum breeding population while feeding on redgram (98.33%) and rice (44.67%). In case of redgram breeding population per cent mortality was maximum in rice (21.67%) and sorghum (19.67%). The survival percentage was maximum in sorghum population while feeding on sorghum (95 %). F1 progeny emergence of sorghum breeding population was higher while feeding on sorghum (75.67%) and rice (36.67%). In case redgram breeding population F1 progeny emergence was maximum in redgram (62.33%) and sorghum (15.33%), whereas in rice breeding population maximum progeny emergence was observed in rice (72.33%) and sorghum (65.67%). The cereal bred population did not survive on redgram, whereas redgram bred population able to survive on cereals, but the progeny emergence and their development was affected

The Block Point Process Model for Continuous-Time Event-Based Dynamic Networks

We consider the problem of analyzing timestamped relational events between a set of entities, such as messages between users of an on-line social network. Such data are often analyzed using static or discrete-time network models, which discard a significant amount of information by aggregating events over time to form network snapshots. In this paper, we introduce a block point process model (BPPM) for continuous-time event-based dynamic networks. The BPPM is inspired by the well-known stochastic block model (SBM) for static networks. We show that networks generated by the BPPM follow an SBM in the limit of a growing number of nodes. We use this property to develop principled and efficient local search and variational inference procedures initialized by regularized spectral clustering. We fit BPPMs with exponential Hawkes processes to analyze several real network data sets, including a Facebook wall post network with over 3,500 nodes and 130,000 events.Comment: To appear at The Web Conference 201