TopCom: Index for Shortest Distance Query in Directed Graph

Finding shortest distance between two vertices in a graph is an important problem due to its numerous applications in diverse domains, including geo-spatial databases, social network analysis, and information retrieval. Classical algorithms (such as, Dijkstra) solve this problem in polynomial time, but these algorithms cannot provide real-time response for a large number of bursty queries on a large graph. So, indexing based solutions that pre-process the graph for efficiently answering (exactly or approximately) a large number of distance queries in real-time is becoming increasingly popular. Existing solutions have varying performance in terms of index size, index building time, query time, and accuracy. In this work, we propose T OP C OM , a novel indexing-based solution for exactly answering distance queries. Our experiments with two of the existing state-of-the-art methods (IS-Label and TreeMap) show the superiority of T OP C OM over these two methods considering scalability and query time. Besides, indexing of T OP C OM exploits the DAG (directed acyclic graph) structure in the graph, which makes it significantly faster than the existing methods if the SCCs (strongly connected component) of the input graph are relatively small

Entropy Balance and Dispersive Oscillations in Lattice Boltzmann Models

We conduct an investigation into the dispersive post-shock oscillations in the entropic lattice-Boltzmann method (ELBM). To this end we use a root finding algorithm to implement the ELBM which displays fast cubic convergence and guaranties the proper sign of dissipation. The resulting simulation on the one-dimensional shock tube shows no benefit in terms of regularization from using the ELBM over the standard LBGK method. We also conduct an experiment investigating of the LBGK method using median filtering at a single point per time step. Here we observe that significant regularization can be achieved.Comment: 18 pages, 4 figures; 13/07/2009 Matlab code added to appendi

In Vitro Evaluation of Eslicarbazepine Delivery via Enteral Feeding Tubes

Purpose: The feasibility of preparing an eslicarbazepine acetate suspension using Aptiom tablets for administration via enteral feeding tubes was evaluated. Methods: Eslicarbazepine acetate suspension (40 mg/mL) was prepared using Aptiom tablets after optimizing the tablet crushing methods and the vehicle composition. A stability-indicating high-performance liquid chromatography (HPLC) method was developed to monitor the eslicarbazepine stability in the prepared suspension. Three enteric feeding tubes of various composition and dimensions were evaluated for the delivery of the suspensions. The suspension was evaluated for the physical and chemical stability for 48 hours. Results: The reproducibility and consistency of particle size reduction was found to be best with standard mortar/pestle. The viscosity analysis and physical stability studies showed that ORA-Plus:water (50:50 v/v) was optimal for suspending ability and flowability of suspension through the tubes. The developed HPLC method was found to be stability indicating and suitable for the assay of eslicarbazepine acetate in the prepared suspension. The eslicarbazepine concentrations in separately prepared suspensions were within acceptable range (±3%), indicating accuracy and reproducibility of the procedure. The eslicarbazepine concentrations in suspensions before and after delivery through the enteric feeding tubes were within acceptable range (±4%), indicating absence of any physical/chemical interactions of eslicarbazepine with the tubes and a successful delivery of eslicarbazepine dosage via enteric feeding tubes. The stability study results showed that eslicarbazepine concentration in the suspension remained unchanged when stored at room temperature for 48 hours. Conclusion: The study presents a convenient procedure for the preparation of a stable suspension of eslicarbazepine acetate (40 mg/mL) using Aptiom tablets, for administration via enteral feeding tubes

Overview of building information modelling in healthcare projects

In this paper, we explore how BIM functionalities together with novel management concepts and methods have been utilized in thirteen hospital projects in the United States and the United Kingdom. Secondary data collection and analysis were used as the method. Initial findings indicate that the utilization of BIM enables a holistic view of project delivery and helps to integrate project parties into a collaborative process. The initiative to implement BIM must come from the top down to enable early involvement of all key stakeholders. It seems that it is rather resistance from people to adapt to the new way of working and thinking than immaturity of technology that hinders the utilization of BIM

The Study of the Influence of Formulation and Process Variables on the properties of Simvastatin-Phospholipid Complex

Objectives: The aim of the present study was to examine the influence of the formulation and process variables on the entrapment efficiency of simvastatin-phospholipid complex (SPC), prepared with a goal of improving the solubility and permeability of simvastatin. Method: The SPC was prepared using a solvent evaporation method. The influence of formulation and process variables on simvastatin entrapment was assessed using a central composite design. An additional SPC was prepared using the optimized variables from the developed quadratic model. This formulation was characterized for its physical-chemical properties. The functional attributes of the optimized SPC formulation were analyzed by apparent aqueous solubility analysis, in-vitro dissolution studies, dissolution efficiency analysis, and ex-vivo permeability studies. Results: The factors studied were found to significantly influence on the entrapment efficiency. The developed model was validated using the optimized levels of formulation and process variables. The physical-chemical characterization confirmed a formation of the complex. The optimized SPC demonstrated over 25-fold higher aqueous solubility of simvastatin, compared to that of pure simvastatin. The optimized SPC exhibited a significantly higher rate and extent of simvastatin dissolution (\u3e98%), compared to that of pure simvastatin (∼16%). The calculated dissolution efficiency was also found to be significantly higher for the SPC (∼54 %), compared to that of pure simvastatin (∼8%). Finally, the optimized SPC exhibited a significantly higher simvastatin permeability (\u3e78%), compared to that of pure simvastatin (∼11%). Implications: The present study shows that simvastatin-phospholipid complex can be a promising strategy for improving the delivery of simvastatin, and similar drugs with low aqueous solubility

Formulation and Stability Study of Eslicarbazepine Acetate Oral Suspensions for Extemporaneous Compounding

Eslicarbazepine acetate is an anticonvulsant drug with a recent U.S. Food and Drug Administration approval for expanded use in children and adolescents. Currently, eslicarbazepine acetate is only available in the U.S. as 200-mg to 800-mg strength tablets (Aptiom), which are not easy to administer for pediatric patients. This study was initiated to develop an oral suspension formulation for extemporaneous compounding by pharmacists and to generate stability data for storage recommendations. Nine suspension formulations of eslicarbazepine acetate were prepared from Aptiom tablets and commercially available liquid vehicles using the standard mortar/pestle method. The vehicles varied mainly in their solvents, viscosities, and sweeteners. The formulations were evaluated for ease of preparation, physical properties, and initial potency. Two lead formulations were selected for a two-month stability study at room temperature or under refrigeration (2°C to 8°C). The stability samples were withdrawn at pre-determined time points and analyzed by visual inspection, pH measurement, and a stability-indicating high-performance liquid chromatographic assay. The majority of the 9 formulations were found to be easy to prepare and administer at a concentration of 40-mg/mL eslicarbazepine acetate. Particle settling was observed in several formulations over time, but they were re-suspended satisfactorily upon shaking. Two suspensions in 50:50 v/v mixtures of Ora-Sweet or Ora-Sweet SF with Ora-Plus were selected as the lead formulations for the two-month stability study. At the initiation of the study, all samples appeared as white and smooth suspensions with pH ranging from 4.39 to 4.46. The high-performance liquid chromatographic results confirmed that the initial samples contained 100.4% to 102.2% of the label claim strength. Over two months of storage at room temperature or refrigeration, there were no significant changes in visual appearance, re-suspendability, pH, or potency for any samples. No new degradation peaks were observed in any highperformance liquid chromatograms. Based on the study results, two eslicarbazepine acetate suspensions are recommended for extemporaneous compounding from Aptiom tablets. The formulations consist of 40 mg/mL eslicarbazepine acetate in 50:50 v/v Ora-Sweet:Ora-Plus or Ora-Sweet SF:Ora-Plus. Once prepared, these suspensions can be stored at room temperature or under refrigeration for up to two months

Neural‑Brane: Neural Bayesian Personalized Ranking for Attributed Network Embedding

Network embedding methodologies, which learn a distributed vector representation for each vertex in a network, have attracted considerable interest in recent years. Existing works have demonstrated that vertex representation learned through an embedding method provides superior performance in many real-world applications, such as node classification, link prediction, and community detection. However, most of the existing methods for network embedding only utilize topological information of a vertex, ignoring a rich set of nodal attributes (such as user profiles of an online social network, or textual contents of a citation network), which is abundant in all real-life networks. A joint network embedding that takes into account both attributional and relational information entails a complete network information and could further enrich the learned vector representations. In this work, we present Neural-Brane, a novel Neural Bayesian Personalized Ranking based Attributed Network Embedding. For a given network, Neural-Brane extracts latent feature representation of its vertices using a designed neural network model that unifies network topological information and nodal attributes. Besides, it utilizes Bayesian personalized ranking objective, which exploits the proximity ordering between a similar node pair and a dissimilar node pair. We evaluate the quality of vertex embedding produced by Neural-Brane by solving the node classification and clustering tasks on four real-world datasets. Experimental results demonstrate the superiority of our proposed method over the state-of-the-art existing methods