Detection and Identification of Probiotic Lactobacillus plantarum Strains by Multiplex PCR Using RAPD-Derived Primers

Lactobacillus plantarum 2035 and Lactobacillus plantarum ACA-DC 2640 are two lactic acid bacteria (LAB) strains that have been isolated from Feta cheese. Both display significant potential for the production of novel probiotic food products. The aim of the present study was the development of an accurate and efficient method for the molecular detection and identification of the above strains in a single reaction. A multiplex PCR assay was designed for each strain, based on specific primers derived from Random Amplified Polymorphic DNA (RAPD) Sequenced Characterized Amplified Region (SCAR) analysis. The specificity of the assay was tested with a total of 23 different LAB strains, for L. plantarum 2035 and L. plantarum ACA-DC 2640. The multiplex PCR assay was also successfully applied for the detection of the above cultures in yogurt samples prepared in our lab. The proposed methodology may be applied for monitoring the presence of these strains in food products, thus evaluating their probiotic character. Moreover, our strategy may be adapted for other novel LAB strains with probiotic potential, thus providing a powerful tool for molecular discrimination that could be invaluable to the food industry.     

The Effect of Nanoparticle Shape on the Photocarrier Dynamics and Photovoltaic Device Performance of Poly(3‐hexylthiophene):CdSe Nanoparticle Bulk Heterojunction Solar Cells

The charge separation and transport dynamics in CdSe nanoparticle:poly(3‐hexylthiophene) (P3HT) blends are reported as a function of the shape of the CdSe‐nanoparticle electron acceptor (dot, rod, and tetrapod). For optimization of organic photovoltaic device performance it is crucial to understand the role of various nanostructures in the generation and transport of charge carriers. The sample processing conditions are carefully controlled to eliminate any processing‐related effects on the carrier generation and on device performance with the aim of keeping the conjugated polymer phase constant and only varying the shape of the inorganic nanoparticle acceptor phase. The electrodeless, flash photolysis time‐resolved microwave conductivity (FP‐TRMC) technique is used and the results are compared to the efficiency of photovoltaic devices that incorporate the same active layer. It is observed that in nanorods and tetrapods blended with P3HT, the high aspect ratios provide a pathway for the electrons to move away from the dissociation site even in the absence of an applied electric field, resulting in enhanced carrier lifetimes that correlate to increased efficiencies in devices. The processing conditions that yield optimum performance in high aspect ratio CdSe nanoparticles blended with P3HT result in poorly performing quantum dot CdSe:P3HT devices, indicating that the latter devices are inherently limited by the absence of the dimensionality that allows for efficient, prolonged charge separation at the polymer:CdSe interface.     

Rate-distortion driven decoder-side bitplane mode decision for distributed video coding

Distributed video coding (DVC) features simple encoders but complex decoders, which lies in contrast to conventional video compression solutions such as H.264/AVC. This shift in complexity is realized by performing motion estimation at the decoder side instead of at the encoder, which brings a number of problems that need to be dealt with. One of these problems is that, while employing different coding modes yields significant coding gains in classical video compression systems, it is still difficult to fully exploit this in DVC without increasing the complexity at the encoder side. Therefore, in this paper, instead of using an encoder-side approach, techniques for decoder-side mode decision are proposed. A rate-distortion model is derived that takes into account the position of the side information in the quantization bin. This model is then used to perform mode decision at the coefficient level and bitplane level. Average rate gains of 13–28% over the state-of-the-art DISCOVER codec are reported, for a GOP of size four, for several test sequences.     

Barcode High Resolution Melting (Bar-HRM) analysis for detection and quantification of PDO “Fava Santorinis” (Lathyrus clymenum) adulterants

Legumes considered as one of the most important crops worldwide. Due to high price as a PDO product, commercial products of “Fava Santorinis” are often subjected to adulterations from other legume products coming from other Lathyrus or Vicia and Pisum species. Using plant DNA barcoding regions (trnL and rpoC) coupled with High Resolution Melting (Bar-HRM) we have developed a method allowing us to detect and authenticate PDO “Fava Santorinis”. Bar-HRM proved to be a very sensitive tool able to genotype Lathyrus and its closed relative species and to detect admixtures, being sensitive enough to as low as 1:100 of non-“Fava Santorinis” in “Fava Santorinis” commercial products. In conclusion, Bar-HRM analysis can be a faster, with higher resolution and cost effectiveness alternative method to authenticate PDO “Fava Santorinis” and to quantitatively detect adulterations in “Fava Santorinis” with other relative commercial “Fava” food products.     

Mesh deformation-based multi-tissue mesh generation for brain images

Multi-tissue meshing is necessary for the realistic building of a biomechanical model of the brain, which has been widely used in brain surgery simulation, brain shift, and non-rigid registration. A two step multi-tissue mesher is developed. First, a coarse multi-tissue mesh is generated by redistributing labels of a body-centered cubic (BCC) mesh. Second, all the surfaces of the submeshes are deformed to their corresponding tissue boundaries. To deform the mesh, two strategies are developed. One is based on a point-based registration (PBR) and the other is based on a robust point matching (RPM). The PBR method explicitly calculates the correspondence, which takes both smoothing and quality into account, then resolves the displacement vector by minimizing an energy function. Unlike PBR method, RPM does not require the correspondence between the source points and the target points to be known in advance. To simultaneously resolve the displacement vector and the correspondence, the Expectation and Maximization optimization is employed to alternately estimate the correspondence and the displacement vector. To effectively cope with outliers, least trimmed square, a robust regression technique, is employed to correct the regression bias induced by outliers. Both methods are effective in deforming the multi-tissue mesh. However, the PBR method favors quality and smoothing, and the RPM method favors fidelity. The resulting mesh is characterized by its flexible control of four mesh properties: (1) tissue-dependent resolution, (2) fidelity to tissue boundaries, (3) smoothness of mesh surfaces, and (4) element quality. Each mesh property can be controlled on a tissue level. Our experiments conducted on synthetic data, clinic MRI, visible human data, and brain atlas effectively demonstrate these features of this multi-tissue mesher.     

Ultrasonic spray deposition for production of organic solar cells

Recent improvements of organic photovoltaic power conversion efficiencies have motivated development of scalable processing techniques. We compare chlorobenzene and p-xylene, as solvents with similar bulk properties, in a case study of ultrasonic spray depositions of bulk heterojunction layers in photovoltaic devices. Structure and morphology of spray-deposited films are investigated via small-angle X-ray diffraction and optical microscopy. Unique phases are observed in bulk heterostructure films sprayed from p-xylene. Films sprayed from chlorobenzene resulted in higher device efficiencies than p-xylene due to large differences in film morphologies. Carrier loss mechanisms are also investigated. Post-production annealing increases power conversion efficiency to 3.2% when chlorobenzene is used.     

Theoretical and methodological implications of designing and implementing multiuser location-based games

Multiuser location-aware applications present a new form of mediated communication that takes place within a digital as well as a physical spatial context. The inherently hybrid character of locative media use necessitates that the designers of such applications take into account the way communication and social interaction is influenced by contextual elements. In this paper, an investigation into the communicational and social practices of users who participate in a location-based game is presented, with an emphasis on group formation and dynamics, interpersonal communication, and experienced sense of immersion. This investigation employs a methodological approach that is reliant on both qualitative and quantitative data analysis. A series of this user experience study’s results are presented and discussed.     

Continuous spatial assignment of moving users

Consider a set of servers and a set of users, where each server has a coverage region (i.e., an area of service) and a capacity (i.e., a maximum number of users it can serve). Our task is to assign every user to one server subject to the coverage and capacity constraints. To offer the highest quality of service, we wish to minimize the average distance between users and their assigned server. This is an instance of a well-studied problem in operations research, termed optimal assignment. Even though there exist several solutions for the static case (where user locations are fixed), there is currently no method for dynamic settings. In this paper, we consider the continuous assignment problem (CAP), where an optimal assignment must be constantly maintained between mobile users and a set of servers. The fact that the users are mobile necessitates real-time reassignment so that the quality of service remains high (i.e., their distance from their assigned servers is minimized). The large scale and the time-critical nature of targeted applications require fast CAP solutions. We propose an algorithm that utilizes the geometric characteristics of the problem and significantly accelerates the initial assignment computation and its subsequent maintenance. Our method applies to different cost functions (e.g., average squared distance) and to any Minkowski distance metric (e.g., Euclidean, L ₁ norm, etc.).