Preparation and characterization of a hydroxyapatite–collagen composite as component for injectable bone substitute

The paper presents an improved sol–gel technique for the preparation of hydroxyapatite–atelocollagen composites suitable as precursor for osseous regeneration. This technique includes a premineralization step of atelocollagen providing a suspension of microfibrils in which the synthesis of the inorganic component was conducted at low temperature. The characterization of the composite was performed by FTIR spectroscopy, X-ray diffraction and scanning electron microscopy. The particle size distribution and the zeta potential were determined by Zetasizer measurements. The time stability of the composite was evaluated by turbidimetric measurements and macroscopic observation. The composites can be stored for a long time in sterile liquid media without a major risk of aggregation or sedimentation. From the final composite a slurry was obtained by sedimentation in centrifugal field and oscillatory rheological experiments were made to get information about its flow behavior. The slurry could be used as an injectable osteoconductive component, able to act as stock form in orthopaedic kits.     

Innovation and Firm Growth: Is R&D Worth It?

The paper contributes to an emerging literature that critically questions the degree to which R&D, at the centre of national and transnational innovation policies, results in firm growth. The differences in how innovation affects firm growth is explored for small and large publicly quoted US pharmaceutical firms between 1950 and 2008. We observe that the positive impact of R&D on firm growth is highly conditional upon a combination of firm-specific characteristics such as firm size, patenting and persistence in patenting. For small firms, R&D boosts growth for only a subset of firms: namely, those that patent persistently for a minimum of five years. For large pharmaceutical firms, on the other hand, R&D may have a negative impact on growth; potentially resulting from the low R&D productivity these firms have suffered from since the mid-1990s. These results raise important issues around the R&D and firm growth relationship for small and large firms as well the role of persistence in innovation for boosting firm performance.     

Assessment of natural radioactivity concentrations and gamma dose rate levels in Kayseri, Turkey

This study assesses the level of background radiation for Kayseri province of Turkey. Natural radionuclide activity concentrations in soil samples were determined using high-resolution gamma spectroscopy. Outdoor gamma dose measurements in air at 1 m above ground level were determined using a portable gamma scintillation detector. The obtained results of uranium and thorium series as well as potassium ((40)K) are discussed. The present data were compared with the data obtained from different areas in Turkey. From the measured gamma-ray spectra, the average activity concentrations were determined for (238)U (range from 3.91 to 794.25 Bq kg(-1)), (232)Th (range from 0.68 to 245.55 Bq kg(-1)) and (40)K (range from 23.68 to 2718.71 Bq kg(-1)). The average activity concentrations of (238)U, (232)Th and (40)K were found to be 35.51, 37.27 and 429.66 Bq kg(-1), respectively, and 11.53 Bq kg(-1) for the fission product (137)Cs. The highest values of (238)U, (232)Th and (40)K concentrations (794.25 Bq kg(-1), 245.55 Bq kg(-1), 2718.71 Bq kg(-1), respectively) were observed in abnormal samples at Hayriye village. The average outdoor gamma dose rate in air at 1 m above the ground was determined as 114.43 nGy h(-1). Using the data obtained in this study, the average annual effective dose for a person living in Kayseri was found to be about 140.34 μSv.     

A genetic algorithm application using fuzzy processing times in non-identical parallel machine scheduling problem

There are many scheduling problems which are NP-hard in the literature. Several heuristics and dispatching rules are proposed to solve such hard combinatorial optimization problems. Genetic algorithms (GA) have shown great advantages in solving the combinatorial optimization problems in view of its characteristic that has high efficiency and that is fit for practical application [1]. Two different scale numerical examples demonstrate the genetic algorithm proposed is efficient and fit for larger scale identical parallel machine scheduling problem for minimizing the makespan. But, even though it is a common problem in the industry, only a small number of studies deal with non-identical parallel machines. In this article, a kind of genetic algorithm based on machine code for minimizing the processing times in non-identical machine scheduling problem is presented. Also triangular fuzzy processing times are used in order to adapt the GA to non-identical parallel machine scheduling problem in the paper. Fuzzy systems are excellent tools for representing heuristic, commonsense rules. That is why we try to use fuzzy systems in this study.     

Detection of sources using bootstrap techniques

Source detection in array processing can be viewed as a test for equality of eigenvalues. Such a test is proposed, based on a multiple test procedure that considers all pairwise comparisons between eigenvalues. Using the bootstrap to estimate the null distributions of the test statistics results in a procedure with minimal assumptions on the nature of the signal. Simulations show that the proposed test is superior to information theoretic criteria such as the MDL, which are based on Gaussian signals and large sample sizes. Performance in most cases exceeds the more powerful sphericity test     

A distribution network optimization problem for third party logistics service providers

Third party logistics service providers (3PLs) have an important role in supply chain management. Increasing cooperation with 3PLs is expanding in today’s business environment. Hence, 3PLs need to have an efficient distribution network to meet customer demands. Nevertheless, few researches have tried to propose a solution for distribution network problems of 3PLs. The optimization problem which is discussing in our study is solved in two stages. At the first stage, the assignment problem which includes assigning the order of the vehicles is solved with mixed integer programming by using GAMS 21.6/CPLEX. The output of the first stage is used as an input in the second stage. In this stage routes are determined for vehicles by developing a genetic algorithm by using C#.     

Aflatoxin M1 in raw milk and aflatoxin B1 in feed from household cows in Singida,Tanzania

Aflatoxin M₁ (AFM₁) contamination in raw milk from household cows fed with sunflower seedcakes or sunflower-based seedcake feeds was determined in 37 milk samples collected randomly from different locations in Singida region, Tanzania. Aflatoxin B₁ (AFB₁) contamination in sunflower-based seedcake feed was determined in 20 feed samples collected from the same household dairy farmers. The samples were analysed by RP-HPLC using fluorescent detection after immunoaffinity column clean-up. Recoveries were 88.0% and 94.5%, while the limits of detection (LOD) were 0.026 ng mL^?1 and 0.364 ng g^?1 for AFM₁ and AFB₁, respectively. Of the analysed cow’s milk samples, 83.8% (31/37) contained AFM₁, with levels ranging from LOD to 2.007 ng mL^?1, exceeding both the European Commission (EC) and Tanzania Food and Drug Authority (TFDA) limit of 0.05 ng mL^?1. Of the contaminated samples, 16.1% exceeded the Codex Alimentarius limit of 0.5 ng mL^?1. AFB₁ was present in 65% (13/20) of the feed samples with levels ranging from LOD to 20.47 ng g^?1, 61.53% exceeding the TFDA and EC maximum limits of 5 ng g^?1 for complete dairy animal feed. The observed AFM₁ and AFB₁ contamination necessitates the need to raise awareness to dairy farmers in Tanzania to safeguard the health of the end-users.