Should 3K zoom function be used for detection of pneumothorax in cesium iodide/amorphous silicon flat-panel detector radiographs presented on 1K-matrix soft copies?

The purpose of the study was to evaluate observer performance in the detection of pneumothorax with cesium iodide and amorphous silicon flat-panel detector radiography (CsI/a-Si FDR) presented as 1K and 3K soft-copy images. Forty patients with and 40 patients without pneumothorax diagnosed on previous and subsequent digital storage phosphor radiography (SPR, gold standard) had follow-up chest radiographs with CsI/a-Si FDR. Four observers confirmed or excluded the diagnosis of pneumothorax according to a five-point scale first on the 1K soft-copy image and then with help of 3K zoom function (1K monitor). Receiver operating characteristic (ROC) analysis was performed for each modality (1K and 3K). The area under the curve (AUC) values for each observer were 0.7815, 0.7779, 0.7946 and 0.7066 with 1K-matrix soft copies and 0.8123, 0.7997, 0.8078 and 0.7522 with 3K zoom. Overall detection of pneumothorax was better with 3K zoom. Differences between the two display methods were not statistically significant in 3 of 4 observers (p-values between 0.13 and 0.44; observer 4: p = 0.02). The detection of pneumothorax with 3K zoom is better than with 1K soft copy but not at a statistically significant level. Differences between both display methods may be subtle. Still, our results indicate that 3K zoom should be employed in clinical practice.

MODULARITY BASED FUZZY COMMUNITY DETECTION IN SOCIAL NETWORKS

Fuzzy community detection is to identify fuzzy communities in a network, which are groups of vertices in the network such that the membership of a vertex in one community is in [0,1] and that the sum of memberships of vertices in all communities equals to 1. Fuzzy communities are pervasive in social networks, but only a few works have been done for fuzzy community detection. Recently, a one-step forward extension of Newman’s Modularity, the most popular quality function for disjoint community detection, results into the Generalized Modularity (GM) that demonstrates good performance in finding well-known fuzzy communities. Thus, GMis chosen as the quality function in our research. We first propose a generalized fuzzy t-norm modularity to investigate the effect of different fuzzy intersection operators on fuzzy community detection, since the introduction of a fuzzy intersection operation is made feasible by GM. The experimental results show that the Yager operator with a proper parameter value performs better than the product operator in revealing community structure. Then, we focus on how to find optimal fuzzy communities in a network by directly maximizing GM, which we call it Fuzzy Modularity Maximization (FMM) problem. The effort on FMM problem results into the major contribution of this thesis, an efficient and effective GM-based fuzzy community detection method that could automatically discover a fuzzy partition of a network when it is appropriate, which is much better than fuzzy partitions found by existing fuzzy community detection methods, and a crisp partition of a network when appropriate, which is competitive with partitions resulted from the best disjoint community detections up to now. We address FMM problem by iteratively solving a sub-problem called One-Step Modularity Maximization (OSMM). We present two approaches for solving this iterative procedure: a tree-based global optimizer called Find Best Leaf Node (FBLN) and a heuristic-based local optimizer. The OSMM problem is based on a simplified quadratic knapsack problem that can be solved in linear time; thus, a solution of OSMM can be found in linear time. Since the OSMM algorithm is called within FBLN recursively and the structure of the search tree is non-deterministic, we can see that the FMM/FBLN algorithm runs in a time complexity of at least O (n2). So, we also propose several highly efficient and very effective heuristic algorithms namely FMM/H algorithms. We compared our proposed FMM/H algorithms with two state-of-the-art community detection methods, modified MULTICUT Spectral Fuzzy c-Means (MSFCM) and Genetic Algorithm with a Local Search strategy (GALS), on 10 real-world data sets. The experimental results suggest that the H2 variant of FMM/H is the best performing version. The H2 algorithm is very competitive with GALS in producing maximum modularity partitions and performs much better than MSFCM. On all the 10 data sets, H2 is also 2-3 orders of magnitude faster than GALS. Furthermore, by adopting a simply modified version of the H2 algorithm as a mutation operator, we designed a genetic algorithm for fuzzy community detection, namely GAFCD, where elite selection and early termination are applied. The crossover operator is designed to make GAFCD converge fast and to enhance GAFCD’s ability of jumping out of local minimums. Experimental results on all the data sets show that GAFCD uncovers better community structure than GALS.

OUT-OF-STEP DETECTION BASED ON ZUBOV’S APPROXIMATION BOUNDARY METHOD

Disturbances in power systems may lead to electromagnetic transient oscillations due to mismatch of mechanical input power and electrical output power. Out-of-step conditions in power system are common after the disturbances where the continuous oscillations do not damp out and the system becomes unstable. Existing out-of-step detection methods are system specific as extensive off-line studies are required for setting of relays. Most of the existing algorithms also require network reduction techniques to apply in multi-machine power systems. To overcome these issues, this research applies Phasor Measurement Unit (PMU) data and Zubov’s approximation stability boundary method, which is a modification of Lyapunov’s direct method, to develop a novel out-of-step detection algorithm. The proposed out-of-step detection algorithm is tested in a Single Machine Infinite Bus system, IEEE 3-machine 9-bus, and IEEE 10-machine 39-bus systems. Simulation results show that the proposed algorithm is capable of detecting out-of-step conditions in multi-machine power systems without using network reduction techniques and a comparative study with an existing blinder method demonstrate that the decision times are faster. The simulation case studies also demonstrate that the proposed algorithm does not depend on power system parameters, hence it avoids the need of extensive off-line system studies as needed in other algorithms.

Bovine primary chondrocyte culture in synthetic matrix metalloproteinase-sensitive poly(ethylene glycol)-based hydrogels as a scaffold for cartilage repair

A poly(ethylene glycol) (PEG)-based hydrogel was used as a scaffold for chondrocyte culture. Branched PEG-vinylsulfone macromers were end-linked with thiol-bearing matrix metalloproteinase (MMP)-sensitive peptides (GCRDGPQGIWGQDRCG) to form a three-dimensional network in situ under physiologic conditions. Both four- and eight-armed PEG macromer building blocks were examined. Increasing the number of PEG arms increased the elastic modulus of the hydrogels from 4.5 to 13.5 kPa. PEG-dithiol was used to prepare hydrogels that were not sensitive to degradation by cell-derived MMPs. Primary bovine calf chondrocytes were cultured in both MMP-sensitive and MMP-insensitive hydrogels, formed from either four- or eight-armed PEG. Most (>90%) of the cells inside the gels were viable after 1 month of culture and formed cell clusters. Gel matrices with lower elastic modulus and sensitivity to MMP-based matrix remodeling demonstrated larger clusters and more diffuse, less cell surface-constrained cell-derived matrix in the chondron, as determined by light and electron microscopy. Gene expression experiments by real-time RT-PCR showed that the expression of type II collagen and aggrecan was increased in the MMP-sensitive hydrogels, whereas the expression level of MMP-13 was increased in the MMP-insensitive hydrogels. These results indicate that cellular activity can be modulated by the composition of the hydrogel. This study represents one of the first examples of chondrocyte culture in a bioactive synthetic material that can be remodeled by cellular protease activity.

IS711-based real-time PCR assay as a tool for detection of Brucella spp. in wild boars and comparison with bacterial isolation and serology

BACKGROUND: Control of brucellosis in livestock, wildlife and humans depends on the reliability of the methods used for detection and identification of bacteria. In the present study, we describe the evaluation of the recently established real-time PCR assay based on the Brucella-specific insertion sequence IS711 with blood samples from 199 wild boars (first group of animals) and tissue samples from 53 wild boars (second group of animals) collected in Switzerland. Results from IS711 real-time PCR were compared to those obtained by bacterial isolation, Rose Bengal Test (RBT), competitive ELISA (c-ELISA) and indirect ELISA (i-ELISA). RESULTS: In the first group of animals, IS711 real-time PCR detected infection in 11.1% (16/144) of wild boars that were serologically negative. Serological tests showed different sensitivities [RBT 15.6%, c-ELISA 7.5% and i-ELISA 5.5%] and only 2% of blood samples were positive with all three tests, which makes interpretation of the serological results very difficult. Regarding the second group of animals, the IS711 real-time PCR detected infection in 26% of animals, while Brucella spp. could be isolated from tissues of only 9.4% of the animals. CONCLUSION: The results presented here indicate that IS711 real-time PCR assay is a specific and sensitive tool for detection of Brucella spp. infections in wild boars. For this reason, we propose the employment of IS711 real-time PCR as a complementary tool in brucellosis screening programs and for confirmation of diagnosis in doubtful cases.

Method of collaborative detection of autonomous transport vehicles based on laser rangefinder data

To master changing performance demands, autonomous transport vehicles are deployed to make inhouse material flow applications more flexible. The socalled cellular transport system consists of a multitude of small scale transport vehicles which shall be able to form a swarm. Therefore the vehicles need to detect each other, exchange information amongst each other and sense their environment. By provision of peripherally acquired information of other transport entities, more convenient decisions can be made in terms of navigation and collision avoidance. This paper is a contribution to collective utilization of sensor data in the swarm of cellular transport vehicles.

Identification and detection of Actinobacillus pleuropneumoniae by PCR based on the gene apxIVA

The apxIVA gene, a recently discovered RTX determinant of Actinobacillus pleuropneumoniae, was shown to be species-specific. DNA hybridization experiments using probes for various regions of apxIVA revealed that the 3'-terminus of this gene was present in all 14 serotypes of A. pleuropneumoniae but absent from phylogenetically related species. A primer pair spanning this region specifically amplified a 422bp fragment in PCR experiments with DNA from the reference strains of the 14 serotypes and 194 field strains isolated from various geographic locations worldwide. DNA sequence analysis of PCR products derived from all serotypes were identical except in serotypes 3, 8, and 10, which showed minor differences. The PCR did not amplify any product when DNA from 17 different bacterial species closely related to A. pleuropneumoniae was used as template. In addition, the PCR was negative with DNA of several Actinobacillus sp. which were initially characterized as A. pleuropneumoniae using routine phenotypic and serological analyses but which were subsequently shown by 16S rRNA sequence analysis to belong to yet undefined Actinobacillus species. The sensitivity of the PCR was determined to be 10pg of A. pleuropneumoniae DNA. A set of nested primers amplified a 377bp fragment specifically with A. pleuropneumoniae DNA. DNA titration experiments using the flanking and nested primer pairs showed an improved level of sensitivity to approximately 10fg of genomic DNA. The nested PCR was used to monitor the spread of A. pleuropneumoniae in pigs experimentally infected with a virulent serotype 1 strain and housed in a controlled environment facility. A. pleuropneumoniae DNA could be detected by nested PCR in nasal swab samples of infected pigs receiving either a high dose (5x10(5)) or a low dose (1x10(4)) challenge and in unchallenged cohorts that were contact-infected by the inoculated animals. Furthermore, PCR confirmed the presence of A. pleuropneumoniae in 16/17 homogenates from necrotic lung lesions, while the bacterium was successfully recovered from 13 of these lesions by culture.

Development of a bead-based multiplex assay for the simultaneous detection of porcine inflammation markers using xMAP technology

Commercially available assays for the simultaneous detection of multiple inflammatory and cardiac markers in porcine blood samples are currently lacking. Therefore, this study was aimed at developing a bead-based, multiplexed flow cytometric assay to simultaneously detect porcine cytokines [interleukin (IL)-1β, IL-6, IL-10, and tumor necrosis factor alpha], chemokines (IL-8 and monocyte chemotactic protein 1), growth factors [basic fibroblast growth factor (bFGF), vascular endothelial growth factor, and platelet-derived growth factor-bb], and injury markers (cardiac troponin-I) as well as complement activation markers (C5a and sC5b-9). The method was based on the Luminex xMAP technology, resulting in the assembly of a 6- and 11-plex from the respective individual singleplex situation. The assay was evaluated for dynamic range, sensitivity, cross-reactivity, intra-assay and interassay variance, spike recovery, and correlation between multiplex and commercially available enzyme-linked immunosorbent assay as well as the respective singleplex. The limit of detection ranged from 2.5 to 30,000 pg/ml for all analytes (6- and 11-plex assays), except for soluble C5b-9 with a detection range of 2-10,000 ng/ml (11-plex). Typically, very low cross-reactivity (<3% and <1.4% by 11- and 6-plex, respectively) between analytes was found. Intra-assay variances ranged from 4.9 to 7.4% (6-plex) and 5.3 to 12.9% (11-plex). Interassay variances for cytokines were between 8.1 and 28.8% (6-plex) and 10.1 and 26.4% (11-plex). Correlation coefficients with singleplex assays for 6-plex as well as for 11-plex were high, ranging from 0.988 to 0.997 and 0.913 to 0.999, respectively. In this study, a bead-based porcine 11-plex and 6-plex assay with a good assay sensitivity, broad dynamic range, and low intra-assay variance and cross-reactivity was established. These assays therefore represent a new, useful tool for the analysis of samples generated from experiments with pigs.

PCR-based assay using occult blood detection cards for detection of diarrheagenic Escherichia coli in specimens from U.S. travelers to Mexico with acute diarrhea.

Large field studies of travelers' diarrhea for multiple destinations are limited by the need to perform stool cultures on site in a timely manner. A method for the collection, transport, and storage of fecal specimens that does not require immediate processing and refrigeration and that is stable for months would be advantageous. This study was designed to determine if enterotoxigenic Escherichia coli (ETEC) and enteroaggregative E. coli (EAEC) DNA could be identified from cards that were processed for the evaluation of fecal occult blood. U.S. students traveling to Mexico during 2005 to 2007 were monitored for the occurrence of diarrheal illness. When ill, students provided a stool specimen for culture and occult blood by the standard methods. Cards then were stored at room temperature prior to DNA extraction. Fecal PCR was performed to identify ETEC and EAEC in DNA extracted from stools and from occult blood cards. Significantly more EAEC cases were identified by PCR that was performed on DNA that was extracted from cards (49%) or from frozen feces (40%) than from culture methods that used HEp-2 adherence assays (13%) (P < 0.001). Similarly, more ETEC cases were detected from card DNA (38%) than from fecal DNA (30%) or by culture that was followed by hybridization (10%) (P < 0.001). The sensitivity and specificity of the card test were 75 and 62%, respectively, compared to those for EAEC by culture and were 50 and 63%, respectively, compared to those for ETEC. DNA extracted from fecal cards that was used for the detection of occult blood is of use in identifying diarrheagenic E. coli.

Vision-based Proximity Detection in Retinal Surgery

In retinal surgery, surgeons face difficulties such as indirect visualization of surgical targets, physiological tremor, and lack of tactile feedback, which increase the risk of retinal damage caused by incorrect surgical gestures. In this context, intraocular proximity sensing has the potential to overcome current technical limitations and increase surgical safety. In this paper, we present a system for detecting unintentional collisions between surgical tools and the retina using the visual feedback provided by the opthalmic stereo microscope. Using stereo images, proximity between surgical tools and the retinal surface can be detected when their relative stereo disparity is small. For this purpose, we developed a system comprised of two modules. The first is a module for tracking the surgical tool position on both stereo images. The second is a disparity tracking module for estimating a stereo disparity map of the retinal surface. Both modules were specially tailored for coping with the challenging visualization conditions in retinal surgery. The potential clinical value of the proposed method is demonstrated by extensive testing using a silicon phantom eye and recorded rabbit in vivo data.