Social Attention: Modeling Attention in Human Crowds

Robots that navigate through human crowds need to be able to plan safe, efficient, and human predictable trajectories. This is a particularly challenging problem as it requires the robot to predict future human trajectories within a crowd where everyone implicitly cooperates with each other to avoid collisions. Previous approaches to human trajectory prediction have modeled the interactions between humans as a function of proximity. However, that is not necessarily true as some people in our immediate vicinity moving in the same direction might not be as important as other people that are further away, but that might collide with us in the future. In this work, we propose Social Attention, a novel trajectory prediction model that captures the relative importance of each person when navigating in the crowd, irrespective of their proximity. We demonstrate the performance of our method against a state-of-the-art approach on two publicly available crowd datasets and analyze the trained attention model to gain a better understanding of which surrounding agents humans attend to, when navigating in a crowd

Modeling Cooperative Navigation in Dense Human Crowds

For robots to be a part of our daily life, they need to be able to navigate among crowds not only safely but also in a socially compliant fashion. This is a challenging problem because humans tend to navigate by implicitly cooperating with one another to avoid collisions, while heading toward their respective destinations. Previous approaches have used hand-crafted functions based on proximity to model human-human and human-robot interactions. However, these approaches can only model simple interactions and fail to generalize for complex crowded settings. In this paper, we develop an approach that models the joint distribution over future trajectories of all interacting agents in the crowd, through a local interaction model that we train using real human trajectory data. The interaction model infers the velocity of each agent based on the spatial orientation of other agents in his vicinity. During prediction, our approach infers the goal of the agent from its past trajectory and uses the learned model to predict its future trajectory. We demonstrate the performance of our method against a state-of-the-art approach on a public dataset and show that our model outperforms when predicting future trajectories for longer horizons.Comment: Accepted at ICRA 201

Prevalence of ESBL-Producing Klebsiella pneumoniae Isolates in Tertiary Care Hospital

Extended-spectrum β lactamases (ESBLs) continue to be a major challenge in clinical setups world over, conferring resistance to the expanded-spectrum cephalosporins. An attempt was made to study the prevalence of ESBL-producing Klebsiella pneumoniae clinical isolates in a tertiary care hospital in Kurnool. A total of hundred collected isolates of Klebsiella pneumoniae was studied for their susceptibility patterns to various antibiotics and detection of ESBL producers by double disc synergy test (DDST) and phenotypic confirmatory disc diffusion test (PCDDT). Of the 100 isolates tested for their antibiogram, 61% isolates have shown susceptibility to 3rd-generation cepholosporins and 39% were resistant. Amoxycillin showed the highest percentage of resistance followed by tetracyclins and cotrimoxazole. Among 39 resistant isolates of Klebsiella pneumoniae, 17 were ESBL producers detected by DDST and PCDDT. ESBL producers were more in the hospital isolates (28%) compared to community isolates (6%). Maximum percentage of ESBL producers were noticed from blood sample with 57.14%. In the present study, a large number of isolates were found to be multidrug resistant and ESBL producers. PCDDT was found to be better than DDST in the detection of ESBLs. Continued monitoring of drug resistance is necessary in clinical settings for proper disease management

EXPLOITING N-GRAM IMPORTANCE AND ADDITIONAL KNOWEDGE BASED ON WIKIPEDIA FOR IMPROVEMENTS IN GAAC BASED DOCUMENT CLUSTERING

This paper provides a solution to the issue: “How can we use Wikipedia based concepts in document\ud clustering with lesser human involvement, accompanied by effective improvements in result?” In the\ud devised system, we propose a method to exploit the importance of N-grams in a document and use\ud Wikipedia based additional knowledge for GAAC based document clustering. The importance of N-grams\ud in a document depends on several features including, but not limited to: frequency, position of their\ud occurrence in a sentence and the position of the sentence in which they occur, in the document. First, we\ud introduce a new similarity measure, which takes the weighted N-gram importance into account, in the\ud calculation of similarity measure while performing document clustering. As a result, the chances of topical similarity in clustering are improved. Second, we use Wikipedia as an additional knowledge base both, to remove noisy entries from the extracted N-grams and to reduce the information gap between N-grams that are conceptually-related, which do not have a match owing to differences in writing scheme or strategies. Our experimental results on the publicly available text dataset clearly show that our devised system has a significant improvement in performance over bag-of-words based state-of-the-art systems in this area

Engineered mesenchymal stem cells with self-assembled vesicles for systemic cell targeting

Cell therapy has the potential to impact the quality of life of suffering patients. Systemic infusion is a convenient method of cell delivery; however, the efficiency of engraftment presents a major challenge. It has been shown that modification of the cell surface with adhesion ligands is a viable approach to improve cell homing, yet current methods including genetic modification suffer potential safety concerns, are practically complex and are unable to accommodate a wide variety of homing ligands or are not amendable to multiple cell types. We report herein a facile and generic approach to transiently engineer the cell surface using lipid vesicles to present biomolecular ligands that promote cell rolling, one of the first steps in the homing process. Specifically, we demonstrated that lipid vesicles rapidly fuse with the cell membrane to introduce biotin moieties on the cell surface that can subsequently conjugate streptavidin and potentially any biotinylated homing ligand. Given that cell rolling is a pre-requisite to firm adhesion for systemic cell homing, we examined the potential of immobilizing sialyl Lewis X (SLeX) on mesenchymal stem cells (MSCs) to induce cell rolling on a P-selectin surface, under dynamic flow conditions. MSCs modified with SLeX exhibit significantly improved rolling interactions with a velocity of 8 μm/s as compared to 61 μm/s for unmodified MSCs at a shear stress of 0.5 dyn/cm[superscript 2]. The cell surface modification does not impact the phenotype of the MSCs including their viability and multi-lineage differentiation potential. These results show that the transitory modification of cell surfaces with lipid vesicles can be used to efficiently immobilize adhesion ligands and potentially target systemically administered cells to the site of inflammation.American Heart Association (Grant 0970178N)National Institutes of Health (U.S.) (Grant DE019191

Human platelet lysate improves human cord blood derived ECFC survival and vasculogenesis in three dimensional (3D) collagen matrices

Human cord blood (CB) is enriched in circulating endothelial colony forming cells (ECFCs) that display high proliferative potential and in vivo vessel forming ability. Since diminished ECFC survival is known to dampen the vasculogenic response in vivo, we tested how long implanted ECFC survive and generate vessels in three-dimensional (3D) type I collagen matrices in vitro and in vivo. We hypothesized that human platelet lysate (HPL) would promote cell survival and enhance vasculogenesis in the 3D collagen matrices. We report that the percentage of ECFC co-cultured with HPL that were alive was significantly enhanced on days 1 and 3 post-matrix formation, compared to ECFC alone containing matrices. Also, co-culture of ECFC with HPL displayed significantly more vasculogenic activity compared to ECFC alone and expressed significantly more pro-survival molecules (pAkt, p-Bad and Bcl-xL) in the 3D collagen matrices in vitro. Treatment with Akt1 inhibitor (A-674563), Akt2 inhibitor (CCT128930) and Bcl-xL inhibitor (ABT-263/Navitoclax) significantly decreased the cell survival and vasculogenesis of ECFC co-cultured with or without HPL and implicated activation of the Akt1 pathway as the critical mediator of the HPL effect on ECFC in vitro. A significantly greater average vessel number and total vascular area of human CD31(+) vessels were present in implants containing ECFC and HPL, compared to the ECFC alone implants in vivo. We conclude that implantation of ECFC with HPL in vivo promotes vasculogenesis and augments blood vessel formation via diminishing apoptosis of the implanted ECFC