Embedding Spatial Software Visualization in the IDE: an Exploratory Study

Software visualization can be of great use for understanding and exploring a software system in an intuitive manner. Spatial representation of software is a promising approach of increasing interest. However, little is known about how developers interact with spatial visualizations that are embedded in the IDE. In this paper, we present a pilot study that explores the use of Software Cartography for program comprehension of an unknown system. We investigated whether developers establish a spatial memory of the system, whether clustering by topic offers a sound base layout, and how developers interact with maps. We report our results in the form of observations, hypotheses, and implications. Key findings are a) that developers made good use of the map to inspect search results and call graphs, and b) that developers found the base layout surprising and often confusing. We conclude with concrete advice for the design of embedded software maps

Intraoperative Patient-Specific Reconstruction of Partial Bone Flap Defects After Convexity Meningioma Resection

OBJECTIVE: To evaluate implant accuracy and cosmetic outcome of a new intraoperative patient-specific cranioplasty method after convexity meningioma resection. METHODS: The patient's own bone flap served as a template to mold a negative form with the use of polymethyl methacrylate (PMMA). The area of bone invasion was determined and broadly excised under white light illumination with a safety margin of at least 1 cm. The definitive replica was cast within the remaining bone flap frame and the imprint. Clinical and radiologic follow-up examinations were performed 3 months after surgery. RESULTS: Four women and two men (mean age 51.4 years ± 12.8) underwent reconstruction of bone flap defects after meningioma resection. Mean duration of intraoperative reconstruction of the partial bone flap defects was 19 minutes ± 4 (range 14-24 minutes). Implant sizes ranged from 17-35 cm(2) (mean size 22 cm(2) ± 8). Radiologic and clinical follow-up examinations revealed excellent implant alignment and favorable cosmesis (visual analogue scale for cosmesis [VASC] = 97 ± 5) in all patients. CONCLUSIONS: Patient-specific reconstruction of partial bone flap defects after convexity meningioma resection using the presented intraoperative PMMA cast method resulted in excellent bony alignment and a favorable cosmetic outcome. Relatively low costs and minimized operation time for adjustment and insertion of the cranioplasty implant justify use of this method in small bony defects as well.

Validated capillary electrophoresis assay for the simultaneous enantioselective determination of propafenone and its major metabolites in biological samples

A robust, inexpensive, and fully validated CE method for the simultaneous determination of the enantiomers of propafenone (PPF), 5-hydroxy-propafenone (5OH-PPF) and N-despropyl-propafenone (NOR-PPF) in serum and in in vitro media is described. It is based upon liquid-liquid extraction at alkaline pH followed by analysis of the reconstituted extract by CE in presence of a pH 2.0 running buffer composed of 100 mM sodium phosphate, 19% methanol, and 0.6% highly sulfated beta-CD. For each compound, the S-enantiomers are shown to migrate ahead of their antipodes, and the overall run time is about 30 min. Enantiomer levels between 25 and 1000 ng/mL provide linear calibration graphs, and the LOD for all enantiomers is between 10 and 12 ng/mL. The assay is shown to be suitable for the determination of the enantiomers of PPF and its metabolites in in vitro incubations comprising human liver microsomes or single CYP450 enzymes (SUPERSOMES). Incubations with CYP2D6 SUPERSOMES revealed, for the first time, the simultaneous formation of the enantiomers of 5OH-PPF and NOR-PPF with that enzyme. CE data can be used for the evaluation of the enzymatic N-dealkylation and hydroxylation rates.

Characterization of the stereoselective biotransformation of ketamine to norketamine via determination of their enantiomers in equine plasma by capillary electrophoresis

A robust CE method for the simultaneous determination of the enantiomers of ketamine and norketamine in equine plasma is described. It is based upon liquid-liquid extraction of ketamine and norketamine at alkaline pH from 1 mL plasma followed by analysis of the reconstituted extract by CE in the presence of a pH 2.5 Tris-phosphate buffer containing 10 mg/mL highly sulfated beta-CD as chiral selector. Enantiomer plasma levels between 0.04 and 2.5 microg/mL are shown to provide linear calibration graphs. Intraday and interday precisions evaluated from peak area ratios (n = 5) at the lowest calibrator concentration are < 8 and < 14%, respectively. The LOD for all enantiomers is 0.01 microg/mL. After i.v. bolus administration of 2.2 mg/kg racemic ketamine, the assay is demonstrated to provide reliable data for plasma samples of ponies under isoflurane anesthesia, of ponies premedicated with xylazine, and of one horse that received romifidine, L-methadone, guaifenisine, and isoflurane. In animals not premedicated with xylazine, the ketamine N-demethylation is demonstrated to be enantioselective. The concentrations of the two ketamine enantiomers in plasma are equal whereas S-norketamine is found in a larger amount than R-norketamine. In the group receiving xylazine, data obtained do not reveal this stereoselectivity.

Applied Graph Theory in Computer Vision and Pattern Recognition

This book will serve as a foundation for a variety of useful applications of graph theory to computer vision, pattern recognition, and related areas. It covers a representative set of novel graph-theoretic methods for complex computer vision and pattern recognition tasks. The first part of the book presents the application of graph theory to low-level processing of digital images such as a new method for partitioning a given image into a hierarchy of homogeneous areas using graph pyramids, or a study of the relationship between graph theory and digital topology. Part II presents graph-theoretic learning algorithms for high-level computer vision and pattern recognition applications, including a survey of graph based methodologies for pattern recognition and computer vision, a presentation of a series of computationally efficient algorithms for testing graph isomorphism and related graph matching tasks in pattern recognition and a new graph distance measure to be used for solving graph matching problems. Finally, Part III provides detailed descriptions of several applications of graph-based methods to real-world pattern recognition tasks. It includes a critical review of the main graph-based and structural methods for fingerprint classification, a new method to visualize time series of graphs, and potential applications in computer network monitoring and abnormal event detection.