Skeleton-based edge bundling for graph visualization

In this paper, we present a novel approach for constructing bundled layouts of general graphs. As layout cues for bundles, we use medial axes, or skeletons, of edges which are similar in terms of position information. We combine edge clustering, distance fields, and 2D skeletonization to construct progressively bundled layouts for general graphs by iteratively attracting edges towards the centerlines of level sets of their distance fields. Apart from clustering, our entire pipeline is image-based with an efficient implementation in graphics hardware. Besides speed and implementation simplicity, our method allows explicit control of the emphasis on structure of the bundled layout, i.e. the creation of strongly branching (organic-like) or smooth bundles. We demonstrate our method on several large real-world graphs.     

Particle swarm optimization based inverter design considering transient performance

Evolutionary computation is an efficient tool for automated design of digital integrated circuits. Demand for electronic circuit automation has increased due to complexity growth in VLSI circuits. Since circuit design deals with highly complicated nonlinear equations, obtaining optimal solution of these equations due to particular constraints in short time and disregardable error is of prime concern. Simpler structure and better result providing in case of parameter growth makes particle swarm optimization (PSO) an ideal candidate for optimal design of circuit topologies. In this work, usage of PSO algorithm in digital electronic circuit design has been investigated. For this purpose, the performance of the algorithm has been tested on the design of an inverter considering transient performance. Performance criteria of inverter constitute the constraints of PSO. Obtained results show that theoretical design of inverter is matched with PSO based design.     

An Intuitive Modelling Interface for Systems Biology

We introduce a natural language interface for building stochastic \pi calculus models of biological systems. In this language, complex constructs describing biochemical events are built from basic primitives of association, dissociation and transformation. This language thus allows us to model biochemical systems modularly by describing their dynamics in a narrative-style language, while making amendments, refinements and extensions on the models easy. We give a formal semantics for this language and a translation algorithm into stochastic \pi calculus that delivers this semantics. We demonstrate the language on a model of Fcr receptor phosphorylation during phagocytosis. We provide a tool implementation of the translation into a stochastic \pi calculus language, Microsoft Research''s SPiM, which can be used for simulation and analysis.     

Multimodal concept detection in broadcast media: KavTan

Concept detection stands as an important problem for efficient indexing and retrieval in large video archives. In this work, the KavTan System, which performs high-level semantic classification in one of the largest TV archives of Turkey, is presented. In this system, concept detection is performed using generalized visual and audio concept detection modules that are supported by video text detection, audio keyword spotting and specialized audio-visual semantic detection components. The performance of the presented framework was assessed objectively over a wide range of semantic concepts (5 high-level, 14 visual, 9 audio, 2 supplementary) by using a significant amount of precisely labeled ground truth data. KavTan System achieves successful high-level concept detection performance in unconstrained TV broadcast by efficiently utilizing multimodal information that is systematically extracted from both spatial and temporal extent of multimedia data.     

Rumeli fortress from the perspective of architecture history

The Rumeli Fortress has a unique place in world history. This study presents information on the castle and Fatih period, explains the aspects of castle thought to be important, and discusses the gradually ruined areas of the castle.     

Utilization of Olive-Pomace Oil for Enzymatic Production of Cocoa Butter-like Fat

Refined olive-pomace oil (ROPO) was utilized as a source for the production of a cocoa butter (CB)-like fat. Immobilized sn-1,3 specific lipase-catalyzed acidolysis of ROPO with palmitic (PA) and stearic (SA) acids was performed at various substrate mole ratios (ROPO:PA:SA) to produce major triacylglycerols (TAGs) of CB. Products obtained for various substrate mole ratios were compared to a commercial CB in terms of TAG content, melting profile, solid fat content (SFC) and microstructure. The fat produced at a substrate mole ratio of 1:2:6 was the most similar to CB. The product contained 11% POP, 21.8% POS, 15.7% SOS while commercial CB contained 18.9% POP, 33.1% POS and 24.7% SOS. The product had a melting peak of 29.9 °C while CB had one of 28.5 °C. Polarized light microscope (PLM) images showed that fat crystal network microstructures of this product and CB were very similar.     

Continuous production of fatty acid methyl esters from corn oil in a supercritical carbon dioxide bioreactor

Continuous production of fatty acid methyl esters (FAMEs) from corn oil was studied in a supercritical carbon dioxide (SC-CO₂) bioreactor using immobilized lipase (Novozym 435) as catalyst. Response surface methodology (RSM) based on central composite rotatable design (CCRD) was employed to investigate and optimize the reaction conditions: pressure (11-35 MPa), temperature (35-63 °C), substrate mole ratio (methanol:corn oil 1-9) and CO₂ flow rate (0.4-3.6 L/min, measured at ambient conditions). Increasing the substrate mole ratio increased the FAME content, whereas increasing pressure decreased the FAME content. Higher conversions were obtained at higher and lower temperatures and CO₂ flow rates compared to moderate temperatures and CO₂ flow rates. The optimal reaction conditions generated from the predictive model for the maximum FAME content were 19.4 MPa, 62.9 °C, 7.03 substrate mole ratio and 0.72 L/min CO₂ flow rate. The optimum predicted FAME content was 98.9% compared to an actual value of 93.3 ± 1.1% (w/w). The SC-CO₂ bioreactor packed with immobilized lipase shows great potential for biodiesel production.     

Effect of black tea and matrix metalloproteinase inhibitors on eroded dentin in situ

Purpose of this in situ study was to evaluate the surface properties of eroded dentin specimens activated with three different matrix metalloproteinase (MMP) inhibitors (chlorhexidine [CHX], fluoride, green tea), black tea, and water. One hundred eighty dentin samples were prepared from extracted third molars and then samples divided into six groups. Ten volunteers were carried three specimens of each group, on acrylic palatal appliances, which were fabricated exactly for them (n = 3). Erosive cycles were done by immersing appliances in cup containing Cola and was followed by rinsing with test solutions. Microhardness values were measured. Surface properties were investigated by atomic force microscopy (AFM). Lowest change in microhardness was shown in fluoride group whereas negative control group (water) had the highest change. There were no statistically significant differences among surface roughness changes (p > .05). The least change in microhardness was seen in the fluoride group (13.05 ± 8.07), while the control group showed the highest change (33.80 ± 12.42) and was statistically significant when compared to other groups (p < .05). Besides lowest depth, values were shown in fluoride group as well. AFM evaluations showed macromolecular deposits on surfaces of fluoride, CHX, and black tea groups. No superior results were detected in CHX + fluoride group and black tea showed similar surface characteristics as green tea. Mouthrinses containing not only green tea but also black tea could be beneficial for patients with exposed dentin surfaces. Catechines and theaflavins in teas could be useful for improving surface quality.     

Effects of the Lipid Profile,Type 2 Diabetes and Medication on the Metabolic Syndrome—Associated Gut Microbiome

Metabolic syndrome (MetSyn) is a major health problem affecting approximately 25% of the worldwide population. Since the gut microbiota is highly connected to the host metabolism, several recent studies have emerged to characterize the role of the microbiome in MetSyn development and progression. To this end, our study aimed to identify the microbiome patterns which distinguish MetSyn from type 2 diabetes mellitus (T2DM). We performed 16S rRNA amplicon sequencing on a cohort of 70 individuals among which 40 were MetSyn patients. The microbiome of MetSyn patients was characterised by reduced diversity, loss of butyrate producers (Subdoligranulum, Butyricicoccus, Faecalibacterium prausnitzii) and enrichment in the relative abundance of fungal populations. We also show a link between the gut microbiome and lipid metabolism in MetSyn. Specifically, low-density lipoproteins (LDL) and high-density lipoproteins (HDL) display a positive effect on gut microbial diversity. When interrogating the signature of gut microbiota in a subgroup of patients harbouring both MetSyn and T2DM conditions, we observed a significant increase in taxa such as Bacteroides, Clostridiales, and Erysipelotrichaceae. This preliminary study shows for the first time that T2DM brings unique signatures of gut microbiota in MetSyn patients. We also highlight the impact of metformin treatment on the gut microbiota. Metformin administration was linked to changes in Prevotellaceae, Rickenellaceae, and Clostridiales. Further research focusing on the microbiome-metabolome patterns is needed to clarify the exact association of various gut microbial communities with the progression of T2DM and the occurrence of various complications in MetSyn patients.