Multichromic polymers based on pyrene clicked thienylpyrrole

In this study, the effect of pendant pyrene on the optical and electronic properties of poly(2,5‐dithienylpyrrole)s was studied. For this purpose a new pyrene coupled 2,5‐dithienylpyrrole derivative (SNS‐pyrene) was synthesized through click reaction. SNS‐pyrene was electrochemically polymerized and its electrochemical and optical properties were investigated by electrochemical and optical techniques. The polymer had a band gap of 3.36 eV and displayed light green to blue color variation upon oxidation in less than 2.48 s. Additionally, electrochemical copolymerization of SNS‐pyrene with 3,4‐ethylenedioxythiophene was achieved whilst a detailed investigation was performed on the effect of electrochemical polymerization conditions on the optoelectronic properties of the copolymers. Studies revealed that the copolymers exhibit multichromic reversible redox behavior with lower band gaps and shorter switching times than their parent polymer, P(SNS‐pyrene) © 2014 Society of Chemical Industry.     

On the mechanisms of adenosine induced pulmonary vasoconstriction in rats

The effect of adenosine on pulmonary vessels was studied in isolated perfused rat lungs. Drugs were administered intra-arterially in a fixed volume of 0.1 ml Krebs solution as bolus injections. Adenosine responses were obtained before and 10 min after drug injections. When applied in logarithmically increasing doses (1-100 micrograms/ml), adenosine caused dose-dependent increases in pulmonary perfusion pressure (e.g. pulmonary vasoconstriction) which were readily reversible. Challenging adenosine with quinidine, dihydroergocristine and cyproheptadine (2 micrograms/ml each) did not significantly alter adenosine responses. Pretreatment of lungs with 0.5 mM theophylline, 10 micrograms/ml indomethacin, 30 micrograms/ml tebokan (a PAF antagonist) or 1 microgram/ml methylene blue for 10 min, however, antagonized the vasoconstrictor effect of the drug significantly. From these experiments, it was concluded that the mechanisms underlying the pulmonary vasoconstrictor action of adenosine are complex, and that both types of purinoceptors, prostaglandins, PAF and other vascular endothelial hormones might be involved.     

Enhancing electrochromic properties of polypyrrole by silsesquioxane nanocages

A new monomer, octa(thiophenephenyl)silsesquioxane (OThiophenePS) was synthesized via click chemistry. The chemical structure of OThiophenePS was characterized by nuclear magnetic resonance (¹H NMR) and Fourier transform infrared (FT-IR) spectroscopies. Electrochemical polymerization of pyrrole with OThiophenePS was performed resulting in polypyrrole-attached, polyhedral oligomeric silsesquioxane (OPS–PPy). The spectroelectrochemical studies show that the electrochromic properties of (OPS–PPy) are superior to those of polypyrrole (PPy). This great improvement can be attributed to the more accessible doping sites and the facile ion movement during the redox switching brought by the loose packing of the PPy chains.     

Energy Metabolites as Biomarkers in Ischemic and Dilated Cardiomyopathy

With more than 25 million people affected, heart failure (HF) is a global threat. As energy production pathways are known to play a pivotal role in HF, we sought here to identify key metabolic changes in ischemic- and non-ischemic HF by using a multi-OMICS approach. Serum metabolites and mRNAseq and epigenetic DNA methylation profiles were analyzed from blood and left ventricular heart biopsy specimens of the same individuals. In total we collected serum from n = 82 patients with Dilated Cardiomyopathy (DCM) and n = 51 controls in the screening stage. We identified several metabolites involved in glycolysis and citric acid cycle to be elevated up to 5.7-fold in DCM (p = 1.7 × 10⁻⁶). Interestingly, cardiac mRNA and epigenetic changes of genes encoding rate-limiting enzymes of these pathways could also be found and validated in our second stage of metabolite assessment in n = 52 DCM, n = 39 ischemic HF and n = 57 controls. In conclusion, we identified a new set of metabolomic biomarkers for HF. We were able to identify underlying biological cascades that potentially represent suitable intervention targets.     

The influence of initial water curing on the strength development of ordinary portland and pozzolanic cement concretes

The effect of initial water-curing period on the strength properties of concretes was investigated. Three types of cement, one ordinary Portland cement (OPC) and two natural pozzolanic cements (blended and trass cements), were used in the concrete mixtures. Six different curing regimes were applied to the specimens, the first of which was continuous water storing, and the second continuous air storing. In the remaining four regimes, the specimens were stored under varying initial water-curing periods of 3, 7, 14, and 28 days, respectively. The compressive strength tests were carried out on the cubic specimens at the ages of 7, 14, 28, 90, and 180 days. The variation of compressive strength with time was evaluated by using a semilogarithmic function and the strength-gaining rates were calculated by using this equation for different curing conditions. It was found that poor curing conditions are more adversely effective on the strength of concretes made by pozzolanic cements than that of OPC, and it is necessary to apply water curing to the former concretes at least for the initial 7 days to expose the pozzolanic activity. However, when the pozzolanic cement concretes have sufficient initial curing, they can reach the strength of OPC concretes in reasonable periods of time.     

Global structure constrained local shape prior estimation for medical image segmentation

Organ shape plays an important role in clinical diagnosis, surgical planning and treatment evaluation. Shape modeling is a critical factor affecting the performance of deformable model based segmentation methods for organ shape extraction. In most existing works, shape modeling is completed in the original shape space, with the presence of outliers. In addition, the specificity of the patient was not taken into account. This paper proposes a novel target-oriented shape prior model to deal with these two problems in a unified framework. The proposed method measures the intrinsic similarity between the target shape and the training shapes on an embedded manifold by manifold learning techniques. With this approach, shapes in the training set can be selected according to their intrinsic similarity to the target image. With more accurate shape guidance, an optimized search is performed by a deformable model to minimize an energy functional for image segmentation, which is efficiently achieved by using dynamic programming. Our method has been validated on 2D prostate localization and 3D prostate segmentation in MRI scans. Compared to other existing methods, our proposed method exhibits better performance in both studies.     

Behaviour of sand–clay mixtures for road pavement subgrade

Materials forming sand grains and colluvial soil deposits have a distinct structure, consisting of a composite matrix of coarse and fine soil grains. The influence of sand grains content on the behaviour of sand–clay mixtures was investigated by a series of intensive laboratory experiments. The California bearing ratio (CBR), unconfined compression strength (UCS) and compaction tests were carried out on various contents of sand and clay mixtures. The sand–clay mixtures were prepared with sand contents of 0, 10, 20, 30, 40, and 50% by weight. The laboratory tests on these mixtures have indicated that their behaviour will depend on the relative concentration of the sand and clay samples. The results of the tests showed a decrease in the UCS, and an increase the CBR values with an increase in the amount of sand. An increase in dry unit weight and a decrease in respective moisture content by an increase in the amount of sand were observed in the compaction tests.     

TORC: test plan optimization by requirements clustering

Acceptance testing is a time-consuming task for complex software systems that have to fulfill a large number of requirements. To reduce this effort, we have developed a widely automated method for deriving test plans from requirements that are expressed in natural language. It consists of three stages: annotation, clustering, and test plan specification. The general idea is to exploit redundancies and implicit relationships in requirements specifications. Multi-viewpoint techniques based on RM-ODP (Reference Model for Open Distributed Processing) are employed for specifying the requirements. We then use linguistic analysis techniques, requirements clustering algorithms, and pattern-based requirements collection to reduce the total effort of testing against the requirements specification. In particular, we use linguistic analysis for extracting and annotating the actor, process and object of a requirements statement. During clustering, a similarity function is computed as a measure for the overlap of requirements. In the test plan specification stage, our approach provides capabilities for semi-automatically deriving test plans and acceptance criteria from the clustered informal textual requirements. Two patterns are applied to compute a suitable order of test activities. The generated test plans consist of a sequence of test steps and asserts that are executed or checked in the given order. We also present the supporting prototype tool TORC, which is available open source. For the evaluation of the approach, we have conducted a case study in the field of acceptance testing of a national electronic identification system. In summary, we report on lessons learned how linguistic analysis and clustering techniques can help testers in understanding the relations between requirements and for improving test planning.     

Genetic programming-based attenuation relationship: An application of recent earthquakes in turkey

This study investigates an application of genetic programming (GP) for the prediction of peak ground acceleration (PGA) using strong-ground-motion data from Turkey. The input variables in the developed GP model are the average shear-wave velocity, earthquake source to site distance and earthquake magnitude, and the output is the PGA values. The proposed GP model is based on the most reliable database compiled for earthquakes in Turkey. The results show that the consistency between the observed PGA values and the predicted ones by the GP model yields relatively high correlation coefficients (R²=0.75). The proposed model is also compared with an existing attenuation relationship and found to be more accurate.     

Generalized Regression Neural Networks and Feed Forward Neural Networks for prediction of scour depth around bridge piers

In this study, Generalized Regression Neural Networks (GRNN) and Feed Forward Neural Networks (FFNN) approaches are used to predict the scour depth around circular bridge piers. Hundred and sixty five data collected from various experimental studies, are used to predict equilibrium scour depth. The model consisting of the combination of dimensional data involving the input variables is constructed. The performance of the models in training and testing sets are compared with observations. Then, the model is also tested by Multiple Linear Regression (MLR) and empirical formula. The results of all approaches are compared in order to get more reliable comparison. The results indicated that GRNN can be applied successfully for prediction of scour depth around circular bridge piers.