Content-based copy detection by a subspace learning based video fingerprinting scheme

We propose a video copy detection scheme that employs a transform domain global video fingerprinting method. Video fingerprinting has been performed by the subspace learning based on nonnegative matrix factorization (NMF). It is shown that the binary video fingerprints extracted from the basis and gain matrices of the NMF representation enable us to efficiently represent the spatial and temporal content of a video segment respectively. An extensive performance evaluation has been carried out on the query and reference dataset of CBCD task of TRECVID 2011. Our results are compared with the average and the best performance reported for the task. Also NDCR and F1 rates are reported in comparison to the performance achieved via the global methods designed by the TRECVID 2011 participants. Results demonstrate that the proposed method achieves higher correct detection rates with good localization capability for the transformation of text/logo insertion, strong re-encoding, frame dropping, noise addition, gamma change or their mixtures; however there is still potential for improvement to detect copies with picture-in-picture transformations. It is also concluded that the introduced binary fingerprinting scheme is superior to the existing transform based methods in terms of the compactness.     

Two Different Approaches for Oral Administration of Voriconazole Loaded Formulations: Electrospun Fibers versus β-Cyclodextrin Complexes

In this work, a comparison between two different preparation methods for the improvement of dissolution rate of an antifungal agent is presented. Poly(ε-caprolactone) (PCL) electrospun fibers and β-cyclodextrin (β-CD) complexes, which were produced via an electrospinning process and an inclusion complexation method, respectively, were addressed for the treatment of fungal infections. Voriconazole (VRCZ) drug was selected as a model drug. PCL nanofibers were characterized on the basis of morphology while phase solubility studies for β-CDs complexes were performed. Various concentrations (5, 10, 15 and 20 wt %) of VRCZ were loaded to PCL fibers and β-CD inclusions to study the in vitro release profile as well as in vitro antifungal activity. The results clearly indicated that all formulations showed an improved VRCZ solubility and can inhibit fungi proliferation.     

Performance assessment and optimization of industrial pasta drying

Drying is a high‐energy‐intensive operation and an important step in the pasta production. In this study, exergy analysis of a four‐step drying system in a farfalle pasta production line using actual operational data obtained from a plant located in Izmir, Turkey, was performed. Exergy loss rates, evaporation rates, exergy efficiencies, and improvement in potential rates for each dryer section were determined in this drying system. The exergy efficiency values varied between 0.25% and 5.27% from the predrying to the final drying section. The exergy efficiency value for the entire drying system was calculated to be 2.96%, and the highest exergetic improvement in potential rate was 165.54 kW for the first dryer section. Copyright © 2013 John Wiley & Sons, Ltd.     

A highly novel dinickel complex: A hydrogen-bonded anti-skew carboxylate bridge and a 2D supramolecular structure

Reaction of the tridentate Schiff base ligands obtained from 2,4-dihydroxybenzaldehyde and either l-isoleucine or l-tert-leucine with Ni(NO₃)₂ in methanol/water solution in the presence of base afforded dinickel complexes. The crystal structure of the product derived from l-tert-leucine has been determined by X-ray crystallography. The octahedrally coordinated two Ni centers were found to be bridged by a single carboxylate group in an extremely unusual non-planar fashion. A 2D supramolecular structure, constructed by infinite hydrogen-bonded complex sheets parallel to the ab-plane of the unit cell, arises from intermolecular O–H?O hydrogen bonds.     

Comparison of Artificial Neural Network Methods with L-moments for Estimating Flood Flow at Ungauged Sites: the Case of East Mediterranean River Basin, Turkey

A regional flood frequency analysis based on the index flood method is applied using probability distributions commonly utilized for this purpose. The distribution parameters are calculated by the method of L-moments with the data of the annual flood peaks series recorded at gauging sections of 13 unregulated natural streams in the East Mediterranean River Basin in Turkey. The artificial neural networks (ANNs) models of (1) the multi-layer perceptrons (MLP) neural networks, (2) radial basis function based neural networks (RBNN), and (3) generalized regression neural networks (GRNN) are developed as alternatives to the L-moments method. Multiple-linear and multiple-nonlinear regression models (MLR and MNLR) are also used in the study. The L-moments analysis on these 13 annual flood peaks series indicates that the East Mediterranean River Basin is hydrologically homogeneous as a whole. Among the tried distributions which are the Generalized Logistic, Generalized Extreme Vaules, Generalized Normal, Pearson Type III, Wakeby, and Generalized Pareto, the Generalized Logistic and Generalized Extreme Values distributions pass the Z statistic goodness-of-fit test of the L-moments method for the East Mediterranean River Basin, the former performing yet better than the latter. Hence, as the outcome of the L-moments method applied by the Generalized Logistic distribution, two equations are developed to estimate flood peaks of any return periods for any un-gauged site in the study region. The ANNs, MLR and MNLR models are trained and tested using the data of these 13 gauged sites. The results show that the predicting performance of the MLP model is superior to the others. The application of the MLP model is performed by a special Matlab code, which yields logarithm of the flood peak, Ln(Q_T), versus a desired return period, T.     

Occurrence and antibiotic resistance of Escherichia coli,Staphylococcus aureus and Bacillus cereus in raw milk and dairy products in Turkey

In this survey, 150 samples of raw milk, white cheese and ice cream from three different dairy‐processing plants in Ankara were analysed to find out if they were contaminated with Escherichia coli, Staphylococcus aureus or Bacillus cereus. The highest contamination percentages were found in raw milk samples as follows: B. cereus (90%), E. coli (74%) and S. aureus (56%) followed by cheese (70% B. cereus, 60% E. coli, and 48% S. aureus) and ice cream (56% E. coli, 36% S. aureus and 20% B. cereus). The survey showed that 2% of cheese samples were contaminated with E. coli O157. It was also found that the numbers of S. aureus and E. coli in raw milk, cheese and ice cream samples exceeded the numbers permitted under the Turkish Food Codex (TFC). The number of B. cereus in raw milk, cheese and ice cream samples was lower than the limit given in the TFC standards. The study also showed that E. coli and S. aureus exhibit resistance to ampicillin, penicillin, tetracycline, erythromycin, gentamicin and trimethoprim/sulfamethoxazole. Escherichia coli isolates also showed resistance to chloramphenicol and ciprofloxacin but none of them exhibited resistance to cefotaxime. All S. aureus isolates were found to be susceptible to cefotaxime, chloramphenicol, and ciprofloxacin. Bacillus cereus isolates were found to be resistant to ampicillin, penicillin and trimethoprim/sulfamethoxazole and sensitive to cefotaxime, chloramphenicol, ciprofloxacin erythromycin, gentamicin and tetracycline.     

Comparison of dried sludge and sludge ash for phosphorus recovery with acidic and alkaline leaching

Nowadays, the recovery of phosphorus has been in the spotlight due to its importance for food security and depleting sources. In this study, phosphorus recovery from dried sewage sludge and sludge ash by acid and alkaline leaching was evaluated. Optimum extraction time and temperature were determined as two hours and ambient temperature. Results showed the superiority of strong acidic conditions for leaching; 75 ml/g with 0.4N HCl and 25 ml/g with 0.6N HCl were determined as optimum conditions to achieve efficient phosphorus dissolution from sludge ash (94.6%) and dried sludge (91.1%), respectively, with the lower heavy metal concentrations. Lower L/S ratio put forward the dried sludge as a more advantageous resource for phosphorus extraction. Besides, by alkaline leaching of sludge ash and dried sludge, 60.3 and 70.3% phosphorus dissolutions were achieved with 75 ml/g and 1N NaOH; and the leachate was a suitable product for phosphorus precipitation due to its high pH.     

Oxygen‐releasing biomaterials for tissue engineering

Due to the increasing demand to generate thick and vascularized tissue‐engineered constructs, novel strategies are currently being developed. An emerging example is the generation of oxygen‐releasing biomaterials to tackle mass transport and diffusion limitations within engineered tissue constructs. Biomaterials containing oxygen‐releasing molecules can be fabricated in various forms, such as hybrid thin films, microparticles or three dimensional scaffolds. In this perspective, we summarize various oxygen‐releasing reagents and their potential applications in regenerative engineering. Moreover, we review the main approaches for fabricating oxygen‐releasing biomaterials for a range of tissue engineering applications. © 2013 Society of Chemical Industry