Bond strength of repaired composite resins: surface treatments,adhesive systems,and composite type

The aim of the present study was to investigate the effects of three different surface treatments and two different adhesives on the microtensile bond strength (μTBS) of repaired composites using the same or different type of resin. Twenty-four nano-hybrid (Ceram X mono-C) and 24 nanofilled (Filtek Ultimate-F) composite discs were prepared. The specimens were aged with 5000 thermocycles and randomly divided into groups according to the surface treatment methods: (a) phosphoric acid (b) Er:YAG laser and (c) aluminum trioxide particle (air abrasion). Fresh composite resins (C and F) were added to the treated surfaces with two different adhesives (two-step and one-step self-etch adhesives). Then, the specimens were aged again. The stick-shaped specimens were prepared from the discs (n = 25) and the sticks were subjected to the μTBS test. Results indicated that significant differences were found in μTBS values among the surface treatment methods. In the C groups, the highest μTBS value (41.3 ± 8.3 MPa) was recorded in the air abrasion and one-step self-etch adhesive group, which were repaired with the same kind of composite. In the F groups, the highest μTBS value was observed in the air abrasion and one-step self-etch adhesive (37.6 ± 12.3 MPa) group. The treatment with air abrasion is more effective than the others, and it may be suggested for composite repair.     

The use of thyme and laurel essential oil treatments to extend the shelf life of bluefish (Pomatomus saltatrix) during storage in ice

The objective of this investigation was to study the effect of thyme and laurel essential oil treatments on the quality of bluefish during storage in ice for 13?days. The quality of bluefish during storage time was evaluated by sensory, chemical, physical, physicochemical and microbiological analysis. According to the sensory evaluation results, shelf life of control and treated bluefish samples stored in ice were 9 and 11?days, respectively. Total volatile base nitrogen and trimethylamine values gave acceptable results for up to 9?days for the control groups samples and 13?days for treated groups. Free fatty acid, peroxide and thiobarbituric acid values for treated samples were lower than the control. Microbial growth during storage in ice for control samples was higher than treated samples. The results obtained from this study showed that the shelf life of stored bluefish in ice has extended by 3?C4?days compare to the control samples.     

Characterization of Red Raspberry (Rubus idaeus L.) Genotypes for Their Physicochemical Properties

ABSTRACT:  The worldwide tendency for growing more small fruits, including raspberries, shows permanent increase because this group of fruits has a relatively higher content of bioactive nutrients. To study the health benefits of red raspberry fruits, 11 preselected wild-grown and 1 well-known cultivar, Heritage, were evaluated for some of their physicochemical properties such as fruit weight, total antioxidant capacity (measured by β-carotene bleaching and FRAP assays), total phenolics, ascorbic acid, soluble solid content (SSC), and acidity. Fruit weight, SSC, and ascorbic acid contents were between 1.47 and 2.32 g, 10.87% and 13.60%, and 21 and 36 mg/100 g, respectively. Antioxidant activity and total phenolic content varied among genotypes and the ERZ5 genotype had the highest antioxidant capacity as ascertained by both methods. This genotype also had the highest total phenolic (2031 μg GAE/g FW) content. There are linear relationships between antioxidant capacities and total phenols. The present study demonstrates the potential of certain wild genotypes, notably ERZ5, for improving the nutritional value through germplasm enhancement programs.     

A systematic literature review on the applications of Bayesian networks to predict software quality

Bayesian networks (BN) have been used for decision making in software engineering for many years. In other fields such as bioinformatics, BNs are rigorously evaluated in terms of the techniques that are used to build the network structure and to learn the parameters. We extend our prior mapping study to investigate the extent to which contextual and methodological details regarding BN construction are reported in the studies. We conduct a systematic literature review on the applications of BNs to predict software quality. We focus on more detailed questions regarding (1) dataset characteristics, (2) techniques used for parameter learning, (3) techniques used for structure learning, (4) use of tools, and (5) model validation techniques. Results on ten primary studies show that BNs are mostly built based on expert knowledge, i.e. structure and prior distributions are defined by experts, whereas authors benefit from BN tools and quantitative data to validate their models. In most of the papers, authors do not clearly explain their justification for choosing a specific technique, and they do not compare their proposed BNs with other machine learning approaches. There is also a lack of consensus on the performance measures to validate the proposed BNs. Compared to other domains, the use of BNs is still very limited and current publications do not report enough details to replicate the studies. We propose a framework that provides a set of guidelines for reporting the essential contextual and methodological details of BNs. We believe such a framework would be useful to replicate and extend the work on BNs.     

Intracellular Ca2+ elevation and contraction due to prostaglandin F2alpha in rat aorta

Prostaglandin F2alpha was tested to determine (a) whether its effect on intracellular Ca2+ levels ([Ca2+]i) and force in vascular smooth muscle was mediated through activation of the thromboxane A2 and/or prostaglandin receptor, and (b) the relative roles of Ca2+ influx via L-type and non-L-type Ca2+ channels in prostaglandin receptor-mediated contraction. [Ca2+]i and force were measured simultaneously in fura-2-loaded rat aortic strips. The thromboxane A2 receptor antagonist, SQ29548 ([1S]-1a,2b(5Z),3b,4a-7-(3-[2-[(phenylamino)carbonyl] hydrazinomethyl)-7-oxobicyclo-[2.2.1]hept-2-yl-5-heptenoic acid), prevented the prostaglandin F2alpha-induced plateau [Ca2+]i elevation and force by 80-90%, while abolishing these responses due to the thromboxane A2 receptor agonist, U46619 (9,11-dideoxy-9alpha,11alpha-methanoepoxy prostaglandin F2alpha). Prostaglandin F2alpha (+ SQ29548)-induced plateau [Ca2+]i elevation and force were not inhibited by verapamil. Ni2+, a non-selective cation channel blocker, in the presence of verapamil, abolished the prostaglandin F2alpha (+ SQ29548)-elevated [Ca2+]i, while the contraction was only partially inhibited. These results suggest that, in rat aorta, (1) elevated [Ca2+]i and force due to high prostaglandin F2alpha concentrations largely results from thromboxane A2 receptor activation, and (2) the prostaglandin component of the prostaglandin F2alpha-induced contraction is dependent on Ca2+ influx via non-L-type channels.     

Does Internet use reflect your personality? Relationship between Eysenck’s personality dimensions and Internet use

The aim of this study was to investigate the relationship between three Eysenckian personality dimensions – psychoticism, extroversion and neuroticism – and the Internet use. A sample of 427 Turkish university students completed the Eysenck’s Personality Questionnaire, an Internet survey which contained questions about interpersonal motives for Internet use and a scale for measuring the tendency for expressing one’s “true” self on the Internet. The results indicated that psychoticism was the only personality dimension related to establishing new relationships and having “Internet only” friends; and extroversion was the only personality dimension that is related to maintaining long-distance relationships, and supporting daily face-to-face relationships. The results supported the idea that for some individuals, Internet can be used as social substitute for face-to-face social interactions while for some others it can be used as a tool of social extension, depending on the user’s personality characteristics. Also, psychoticism and neuroticism were found to be positively associated with the expressing “true self” on the Internet, and it was shown that the relationship between psychoticism and Internet uses as social substitute is mediated by the tendency to express one’s true self on the Internet.     

Practical considerations in deploying statistical methods for defect prediction: A case study within the Turkish telecommunications industry

ContextBuilding defect prediction models in large organizations has many challenges due to limited resources and tight schedules in the software development lifecycle. It is not easy to collect data, utilize any type of algorithm and build a permanent model at once. We have conducted a study in a large telecommunications company in Turkey to employ a software measurement program and to predict pre-release defects. Based on our prior publication, we have shared our experience in terms of the project steps (i.e. challenges and opportunities). We have further introduced new techniques that improve our earlier results.ObjectiveIn our previous work, we have built similar predictors using data representative for US software development. Our task here was to check if those predictors were specific solely to US organizations or to a broader class of software.MethodWe have presented our approach and results in the form of an experience report. Specifically, we have made use of different techniques for improving the information content of the software data and the performance of a Naïve Bayes classifier in the prediction model that is locally tuned for the company. We have increased the information content of the software data by using module dependency data and improved the performance by adjusting the hyper-parameter (decision threshold) of the Naïve Bayes classifier. We have reported and discussed our results in terms of defect detection rates and false alarms. We also carried out a cost–benefit analysis to show that our approach can be efficiently put into practice.ResultsOur general result is that general defect predictors, which exist across a wide range of software (in both US and Turkish organizations), are present. Our specific results indicate that concerning the organization subject to this study, the use of version history information along with code metrics decreased false alarms by 22%, the use of dependencies between modules further reduced false alarms by 8%, and the decision threshold optimization for the Naïve Bayes classifier using code metrics and version history information further improved false alarms by 30% in comparison to a prediction using only code metrics and a default decision threshold.ConclusionImplementing statistical techniques and machine learning on a real life scenario is a difficult yet possible task. Using simple statistical and algorithmic techniques produces an average detection rate of 88%. Although using dependency data improves our results, it is difficult to collect and analyze such data in general. Therefore, we would recommend optimizing the hyper-parameter of the proposed technique, Naïve Bayes, to calibrate the defect prediction model rather than employing more complex classifiers. We also recommend that researchers who explore statistical and algorithmic methods for defect prediction should spend less time on their algorithms and more time on studying the pragmatic considerations of large organizations.