Predation of livestock ticks by chickens as a tick-control method in a resource-poor urban environment

The increasing prevalence of streptococci as causes of potentially fatal nosocomial bacteremia requires that antimicrobial agents used for empiric therapy in hospitalized patients include both pneumococci and viridans group streptococci as well as beta-hemolytic streptococci in their activity profile. In this study, the in vitro activity of cefepime, a new fourth-generation cephalosporin, was compared with other cephalosporins versus 197 nosocomial blood stream isolates of streptococci (20 Streptococcus pneumoniae, 104 viridans group, and 73 beta-hemolytic) isolated from patients at more than 30 medial centers from 1995 to 1997. Additional agents tested included penicillin, erythromycin, and vancomycin. Overall, cefepime inhibited 83% of the isolates at concentrations < or = 0.5 microgram/mL and 100% at < or = 8 micrograms/mL. By comparison, ceftazidime inhibited 35 and 88% of isolates at the same concentrations. Cefepime was approximately eightfold more potent than ceftazidime against S. pneumoniae, viridans group streptococci, and beta-hemolytic streptococci. Among the 42 isolates with penicillin MICs > 0.12 microgram/mL, 100% were inhibited by cefepime and only 48% by ceftazidime at < or = 8 micrograms/mL. The rank order of activity for all six agents against the 197 isolates was vancomycin > ceftriaxone > cefepime > penicillin > erythromycin > ceftazidime. Based on the results of the present study, cefepime and ceftriaxone were the superior cephalosporins in potency and spectrum for empiric coverage of patients at risk for streptococcal blood stream infections.     

Transformations for nonideal uniform circular arrays operating in correlated signal environments

The Davies transformation is a method to transform the steering vector of a uniform circular array (UCA) to one with Vandermonde form. As such, it allows techniques such as spatial smoothing for direction-of-arrival (DOA) estimation in a correlated signal environment, developed originally for uniform linear arrays, to be applied to UCAs. However, the Davies transformation can be highly sensitive to perturbations of the underlying array model. This paper presents a method for deriving a more robust transformation using optimization techniques. The effectiveness of the method is illustrated through a number of DOA estimation examples.     

Imaging of follicular dendritic cell tumours of the liver

Follicular dendritic cell tumour of the liver is a recently recognized entity. To date, only two cases have been described, both in the pathology literature. Histologically, it resembles an inflammatory pseudotumour and immunohistochemical and ultrastructural studies are required for its diagnosis. The ultrasound, computed tomography and angiographic features of two cases of follicular dendritic cell tumour of the liver are described in detail. One of the patients had multiple recurrences of this tumour. The imaging features are very similar to those of hepatocellular carcinoma. As follicular dendritic cell tumour is considered to be of low-grade malignant potential, in contrast to the dismal prognosis for hepatocellular carcinoma, it is important to be able to accurately distinguish between the two types of tumour prior to initiating definitive therapy.     

Fast algorithm for computing discrete cosine transform

An efficient method for computing the discrete cosine transform (DCT) is proposed. Based on direct decomposition of the DCT, the recursive properties of the DCT for an even length input sequence is derived, which is a generalization of the radix 2 DCT algorithm. Based on the recursive property, a new DCT algorithm for an even length sequence is obtained. The proposed algorithm is very structural and requires fewer computations when compared with others. The regular structure of the proposed algorithm is suitable for fast parallel algorithm and VLSI implementation     

Fuzzy rule interpolation for multidimensional input spaces in determining d50c of hydrocyclones

Fuzzy rule-based systems have been very popular in many engineering applications. In mineral engineering, fuzzy rules are normally constructed using some fuzzy rule extraction techniques to establish the determination model in predicting the d50c of hydrocyclones. However, when generating fuzzy rules from the available information, it may result in a sparse fuzzy rule base. The use of more than one input variable is also common in hydrocyclone data analysis. This paper examines the application of fuzzy interpolation to resolve the problems using sparse fuzzy rule bases, and to perform analysis of fuzzy interpolation in multidimensional input spaces.     

Decentralized control design for large-scale systems with strong interconnections using neural networks

We propose a decentralized neural network (NN) controller for a class of large-scale nonlinear systems with the strong interconnections. The NNs are used to approximate the unknown subsystems and interconnections. Due to the functional approximation capabilities of NNs, the additional precautions are not required to be made for avoiding the possible control singularity problems. Semiglobal asymptotic stability results are obtained and the tracking error converges to zero. Furthermore, the issue of transient performance of the subsystems is also addressed under an analytical framework.     

Zero-quantised discrete cosine transform prediction technique for video encoding

A new analytical model to eliminate redundant discrete cosine transform (DCT) and quantisation (Q) computations in block-based video encoders is proposed. The dynamic ranges of the quantised DCT coefficients are analysed, then a threshold scheme is derived to determine whether the DCT and Q computations can be skipped without video quality degradation. In addition, fast DCT/inverse DCT (IDCT) algorithms are presented to implement the proposed analytical model. The proposed analytical model is compared with other comparable analytical models reported in the literature. Both the theoretical analysis and experimental results demonstrate that the proposed analytical model can greatly reduce the computational complexity of video encoding without any performance degradation and outperforms other analytical models     

HLA-B27-restricted antigen presentation in the absence of tapasin reveals polymorphism in mechanisms of HLA class I peptide loading

Tapasin is a resident ER protein believed to be critical for antigen presentation by HLA class I molecules. We demonstrate that allelic variation in MHC class I molecules influences their dependence on tapasin for peptide loading and antigen presentation. HLA-B*2705 molecules achieve high levels of surface expression and present specific viral peptides in the absence of tapasin. In contrast, HLA-B*4402 molecules are highly dependent upon human tapasin for these functions, while HLA-B8 molecules are intermediate in this regard. Significantly, HLA-B*2705 like HLA-B*4402, requires tapasin to associate efficiently with TAP (transporters associated with antigen processing). The unusual ability of HLA-B*2705 to form peptide complexes without associating with TAP or tapasin confers flexibility in the repertoire of peptides presented by this molecule. We speculate that these properties might contribute to the role of HLA-B27 in conferring susceptibility to inflammatory spondyloarthropathies.     

Genetic algorithm hybridized with multilayer perceptron to have an economical slope stability design

The present work aimed to evaluate and optimize the design of an artificial neural network (ANN) combined with an optimization algorithm of genetic algorithm (GA) for the calculation of slope stability safety factors (SF) in a pure cohesive slope. To make datasets of training and testing for the developed predictive models, 630 finite element limit equilibrium (FELE) analyses were performed. Similar to many artificial intelligence-based solutions, the database was involved in 189 testing datasets (e.g., 30% of the entire database) and 441 training datasets; for example, a range of 70% of the total database. Moreover, variables of multilayer perceptron (MLP) algorithm (for example, number of nodes in any hidden layer) and the algorithm of GA like population size was optimized by utilizing a series of trial and error process. The parameters in input, which were used in the analysis, consist of slope angle (β), setback distance ratio (b/B), applied stresses on the slope (F_y) and undrained shear strength of the cohesive soil (C_u) where the output was taken SF. The obtained network outputs for both datasets from MLP and GA-MLP models are evaluated according to many statistical indices. A total of 72 MLP trial and error (e.g., parameter study) the optimal architecture of 4 × 8 × 1 were determined for the MLP structure. Both proposed techniques result in a proper performance; however, according to the statistical indices, the GA–MLP model can somewhat accomplish the least mean square error (MSE) when compared to MLP. In an optimized GA–MLP network, coefficient of determination (R²) and root mean square error (RMSE) values of (0.975, and 0.097) and (0.969, and 0.107) were found, respectively, to both of the normalized training and testing datasets.

     

Nonlinear evolutionary swarm intelligence of grasshopper optimization algorithm and gray wolf optimization for weight adjustment of neural network

Engineering with Computers - The advent of new data-mining techniques and, more recently, swarm-based optimization algorithms have antiquated traditional models in the field of energy performance...