In the management of deep-partial or full-thickness palmar skin burns in the pediatric population that require grafting, the use of plantar glabrous skin grafts offers a reliable option for coverage. The aesthetic and functional results are improved over standard techniques.

Aim: To study the effect of Triflupromazine Hcl and diazepam in combination with propofol as preanaesthetic on haematobiochemical parameters in dogs was carried out. Materials and Methods: 16 clinical cases of dogs undergoing different surgical interventions irrespective of age, sex and breed were allotted randomly in to two groups viz., Group A (Triflupromazine Hcl -propofol) and Group B (diazepampropofol) consisting eight dogs each. Blood samples were collected at different intervals from both the Groups in heparinised syringes as follows: Prior to premedication, fifteen minutes after premedication, fifteen minutes, one hour, six hour, 24 hour and 48 hour after induction with Propofol. The samples were subjected for various hematological and biochemical analysis. Results: Hematology revealed a significant (P 0.05) fall in total erythrocyte count (TEC), packed cell volume (PCV) and haemoglobin (Hb), whereas TLC showed a non significant decrease in both the groups throughout the observation period of 48 hours. In the present study blood glucose level was significantly increased between 15 min to one hour in Group A and 15 min to 6 hours of observation period of the study in Group B. The total plasma protein (TPP), alanine amino transferase (ALT),alkaline phosphatase (AP) and creatinine levels did not differ significantly in both the groups throughout the observation period of 48 hours. Conclusion: Both the anaesthetic combinations were found to be safe and effective with smooth and stress free recovery. However triflupromazine Hcl premedication proved to be better with quick sedative effect, long duration of anaesthesia with less induction dose of propofol and shorter recovery time than diazepam.

We address the problem of hierarchical segmentation of sequential grouped data, such as a collection of textual documents, and propose a Bayesian nonparametric approach for this problem. Existing Bayesian nonparametric models such as the sticky HDP-HMM are suitable only for single-layer segmentation. We propose the Layered Dirichlet Process (LaDP), where each layer has a countable set of Dirichlet Processes, draws from which define a distribution over the countable set of Dirichlet Processes at the next layer. Each data item gets assigned to a distribution (index) from each layer of the hierarchy, leading to hierarchical segmentation of the sequence. The complexity of inference depends upon the exchangeability assumptions for the measures at different layers. We propose a new notion of exchangeability called Block Exchangeability, which lies between Markov Exchangeability (used in HDP-HMM) and Complete Group Exchangeability (used in HDP), and allows for faster inference than Markov Exchangeability. Using experiments on a news transcript dataset and a product review dataset, we show that LaDP generalizes better than existing non-parametric models for sequential data, and by simultaneously segmenting at multiple levels, outperforms existing models in terms of single-layer segmentation. We also show empirically that using Block Exchangeability greatly speeds up inference and allows trading off accuracy for execution time.

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