Helical resonator filters with improved power handling capabilities for space applications

The power-handling capabilities of helical resonator filters for space applications are discussed. Emerging difficulties due to the multipaction effects are highlighted. A method is proposed to increase specified power handling without significantly sacrificing the size/quality factor. Experimental verification is attained by means of a fabricated prototype for which measured filter response and multipaction test results are obtained and presented.

Improved Nonlinear PCA for Process Monitoring Using Support Vector Data Description

Nonlinear principal component analysis (PCA) based on neural networks has drawn significant attention as a monitoring tool for complex nonlinear processes, but there remains a difficulty with determining the optimal network topology. This paper exploits the advantages of the Fast Recursive Algorithm, where the number of nodes, the location of centres, and the weights between the hidden layer and the output layer can be identified simultaneously for the radial basis function (RBF) networks. The topology problem for the nonlinear PCA based on neural networks can thus be solved. Another problem with nonlinear PCA is that the derived nonlinear scores may not be statistically independent or follow a simple parametric distribution. This hinders its applications in process monitoring since the simplicity of applying predetermined probability distribution functions is lost. This paper proposes the use of a support vector data description and shows that transforming the nonlinear principal components into a feature space allows a simple statistical inference. Results from both simulated and industrial data confirm the efficacy of the proposed method for solving nonlinear principal component problems, compared with linear PCA and kernel PCA.

An improved immunoassay for detection of saxitoxin by surface plasmon resonance biosensors

Saxitoxin and its analogs, the causative agents of paralytic shellfish poisoning (PSP), are a worldwide threat to seafood safety. Effective monitoring of potentially contaminated fishing areas as well as screening of seafood samples is necessary to adequately protect the public. While many analytical methods exist for detecting paralytic shellfish toxins (PSTs), each technique has challenges associated with routine use. One recently developed method [1] that overcomes ethical or performance-related issues of other techniques is the surface plasmon resonance (SPR) bioassay. Notwithstanding the advantages of this method, much research remains in optimizing the sensor substrate and assay conditions to create a robust technique for rapid and sensitive measurement of PSTs. This manuscript describes a more rigorous and stable SPR inhibition immunoassay through optimization of the surface chemistry as well as determination of optimum mixture ratios and mixing times. The final system provides rapid substrate formation (18 h saxitoxin conjugation with low reagent consumption), contains a reference channel for each assay, and is capable of triplicate measurements in a single run with detection limits well below the regulatory action level. Published by Elsevier B.V.

Improved conjugate gradient implementation for least squares support vector machines

As a promising method for pattern recognition and function estimation, least squares support vector machines (LS-SVM) express the training in terms of solving a linear system instead of a quadratic programming problem as for conventional support vector machines (SVM). In this paper, by using the information provided by the equality constraint, we transform the minimization problem with a single equality constraint in LS-SVM into an unconstrained minimization problem, then propose reduced formulations for LS-SVM. By introducing this transformation, the times of using conjugate gradient (CG) method, which is a greatly time-consuming step in obtaining the numerical solution, are reduced to one instead of two as proposed by Suykens et al. (1999). The comparison on computational speed of our method with the CG method proposed by Suykens et al. and the first order and second order SMO methods on several benchmark data sets shows a reduction of training time by up to 44%. (C) 2011 Elsevier B.V. All rights reserved.

Improved structure optimization for fuzzy-neural networks

Fuzzy-neural-network-based inference systems are well-known universal approximators which can produce linguistically interpretable results. Unfortunately, their dimensionality can be extremely high due to an excessive number of inputs and rules, which raises the need for overall structure optimization. In the literature, various input selection methods are available, but they are applied separately from rule selection, often without considering the fuzzy structure. This paper proposes an integrated framework to optimize the number of inputs and the number of rules simultaneously. First, a method is developed to select the most significant rules, along with a refinement stage to remove unnecessary correlations. An improved information criterion is then proposed to find an appropriate number of inputs and rules to include in the model, leading to a balanced tradeoff between interpretability and accuracy. Simulation results confirm the efficacy of the proposed method.

Alternative method for producing organic fertiliser from anaerobic digestion liquor and limestone powder:High Shear wet granulation

Generally, the solid and liquid fractions (digestate) from Anaerobic Digestion (AD) energy production are considered as waste. This has a negative impact on the sustainability of AD processes because of the financial outlay required to treat digestate before being discharged into municipal water treatment plants or natural water bodies. The main aim of this research was to investigate feasibility of producing an organic fertiliser using anaerobic digestate and limestone powders as the raw materials employing a high shear granulation process. Two-level factorial experimental design was used to determine the influence of granulation process variables on, the strength, resistance to attrition and yield of the granules. It was concluded from the study that it is technically feasible to produce organic fertiliser granules of acceptable strength and product yield. Increasing the liquid-to-solid ratio during granulation leads to increased granule strength and better product yield. Although the strength of the granules produced was lower than typical strength of commercial synthetic fertiliser granules (about 5 to 7. MPa), this could be improved by mixing the digestate with a polymeric binder or coating the particles post granulation. © 2012 Elsevier B.V.

The development of a surface defect machining method for hard turning processes

Hard turning (HT) is a material removal process employing a combination of a single point cutting tool and high speeds to machine hard ferrous alloys which exhibit hardness values over 45 HRC. In this paper, a surface defect machining (SDM) method for HT is proposed which harnesses the combined advantages of porosity machining and pulsed laser pre-treatment processing. From previous experimental work, this was shown to provide better controllability of the process and improved quality of the machined surface. While the experiments showed promising results, a comprehensive understanding of this new technique could only be achieved through a rigorous, in depth theoretical analysis. Therefore, an assessment of the SDM technique was carried out using both finite element method (FEM) and molecular dynamics (MD) simulations.
FEM modelling was used to compare the conventional HT of AISI 4340 steel (52 HRC) using an Al2O3 insert with the proposed SDM method. The simulations showed very good agreement with the previously published experimental results. Compared to conventional HT, SDM provided favourable machining outcomes, such as reduced shear plane angle, reduced average cutting forces, improved surface roughness, lower residual stresses on the machined surface, reduced tool–chip interface contact length and increased chip flow velocity. Furthermore, a scientific explanation of the improved surface finish was revealed using a state-of-the-art MD simulation model which suggested that during SDM, a combination of both the cutting action and rough polishing action help improve the machined surface finish.

A multiconfigurational time-dependent Hartree-Fock method for excited electronic states. I. General formalism and application to open-shell states

The solution of the time-dependent Schrodinger equation for systems of interacting electrons is generally a prohibitive task, for which approximate methods are necessary. Popular approaches, such as the time-dependent Hartree-Fock (TDHF) approximation and time-dependent density functional theory (TDDFT), are essentially single-configurational schemes. TDHF is by construction incapable of fully accounting for the excited character of the electronic states involved in many physical processes of interest; TDDFT, although exact in principle, is limited by the currently available exchange-correlation functionals. On the other hand, multiconfigurational methods, such as the multiconfigurational time-dependent Hartree-Fock (MCTDHF) approach, provide an accurate description of the excited states and can be systematically improved. However, the computational cost becomes prohibitive as the number of degrees of freedom increases, and thus, at present, the MCTDHF method is only practical for few-electron systems. In this work, we propose an alternative approach which effectively establishes a compromise between efficiency and accuracy, by retaining the smallest possible number of configurations that catches the essential features of the electronic wavefunction. Based on a time-dependent variational principle, we derive the MCTDHF working equation for a multiconfigurational expansion with fixed coefficients and specialise to the case of general open-shell states, which are relevant for many physical processes of interest. (C) 2011 American Institute of Physics. [doi: 10.1063/1.3600397]

Algorithmic method for scraper load-time optimization

Scrapers have established an important position in the earthmoving field as they are independently capable of accomplishing an earthmoving operation. Given that loading a scraper to its capacity does not entail its maximum production, optimizing the scraper’s loading time is an essential prerequisite for successful operations management. The relevant literature addresses the loading time optimization through a graphical method that is founded on the invalid assumption that the hauling time is independent of the load time. To correct this, a new algorithmic optimization method that incorporates the golden section search and the bisection algorithm is proposed. Comparison of the results derived from the proposed and the existing method demonstrates that the latter entails the systematic needless prolongation of the loading stage thus resulting in reduced hourly production and increased cost. Therefore, the proposed method achieves an improved modeling of scraper earthmoving operations and contributes toward a more efficient cost management.

Covariance Averaging for Improved Estimation and Portfolio Allocation

We propose a new method for estimating the covariance matrix of a multivariate time series of nancial returns. The method is based on estimating sample covariances from overlapping windows of observations which are then appropriately weighted to obtain the nal covariance estimate. We extend the idea of (model) covariance averaging o ered in the covariance shrinkage approach by means of greater ease of use, exibility and robustness in averaging information over different data segments. The suggested approach does not su er from the curse of dimensionality and can be used without problems of either approximation or any demand for numerical optimization.

Improved Detection of Mycobacterium bovis in Bovine Tissues Using Immunomagnetic Separation Approaches

Immunomagnetic separation (IMS) represents a simple but effective method of selectively capturing and concentrating Mycobacterium bovis, the causative agent of bovine tuberculosis (bTB), from tissue samples. It is a physical cell separation technique that does not impact cell viability, unlike traditional chemical decontamination prior to culture. IMS is performed with paramagnetic beads coated with M. bovis-specific antibody and peptide binders. Once captured by IMS, M. bovis cells can be detected by either PCR or cultural detection methods. Increased detection rates of M. bovis, particularly from non-visibly lesioned lymph node tissues from bTB reactor animals, have recently been reported when IMS-based methods were employed.

Improved Physical Layer Secure Wireless Communications using a Directional Modulation Enhanced Retrodirective Array

Unlike the mathematical encryption and decryption adopted in the classical cryptographic technology at the higher protocol layers, it is shown that characteristics intrinsic to the physical layer, such as wireless channel propagation, can be exploited to lock useful information. This information then can be automatically unlocked using real time analog RF means. In this paper retrodirective array, RDA, technology for spatial encryption in the multipath environment is for the first time combined with the directional modulation, DM, method normally associated with free space secure physical layer communications. We show that the RDA can be made to operate more securely by borrowing DM concepts and that the DM enhanced RDA arrangement is suitable for use in a multipath environment.

Towards an Improved Phasor Measurement Unit Data Communications Framework

This paper discusses a proposed new communications framework for phasor measurement units (PMU) optimized for use on wide area networks. Traditional PMU telecoms have been optimized for use in environments where bandwidth is restricted. The new method takes the reliability of the telecommunications medium into account and provides guaranteed delivery of data whilst optimizing for realtime delivery of the most current data. Other important aspects, such as security, are also considered.

A validated UPLC–MS/MS method for the surveillance of ten aquatic biotoxins in European brackish and freshwater systems

Over the past few decades, there has been an increased frequency and duration of cyanobacterial Harmful Algal Blooms (HABs) in freshwater systems globally. These can produce secondary metabolites called cyanotoxins, many of which are hepatotoxins, raising concerns about repeated exposure through ingestion of contaminated drinking water or food or through recreational activities such as bathing/ swimming. An ultra-performance liquid chromatography tandem mass spectrometry (UPLC–MS/MS) multi-toxin method has been developed and validated for freshwater cyanotoxins; microcystins-LR, -YR, -RR, -LA, -LY and -LF, nodularin, cylindrospermopsin, anatoxin-a and the marine diatom toxin domoic acid. Separation was achieved in around 9 min and dual SPE was incorporated providing detection limits of between 0.3 and 5.6 ng/L of original sample. Intra- and inter-day precision analysis showed relative
standard deviations (RSD) of 1.2–9.6% and 1.3–12.0% respectively. The method was applied to the analysis of aquatic samples (n = 206) from six European countries. The main class detected were the hepatotoxins; microcystin-YR (n = 22), cylindrospermopsin (n = 25), microcystin-RR (n = 17), microcystin-LR (n = 12), microcystin-LY (n = 1), microcystin-LF (n = 1) and nodularin (n = 5). For microcystins, the levels detected ranged from 0.001 to 1.51 mg/L, with two samples showing combined levels above the guideline set by the WHO of 1 mg/L for microcystin-LR. Several samples presented with multiple toxins indicating the potential for synergistic effects and possibly enhanced toxicity. This is the first published pan European survey of freshwater bodies for multiple biotoxins, including two identified for the first time; cylindrospermopsin in Ireland and nodularin in Germany, presenting further incentives for improved monitoring and development of strategies to mitigate human exposure.

Petal-rod - A Novel Method of Lightweighting

Lightweighting the preform to reduce material cost is possibly reaching its limit; key areas of the bottle however may deserve closer attention. The lack of material stretching at the bottle base insists on increased thickness to compensate for the impaired strength in this area. To improve this phenomenon, design of a novel stretch-rod that can mechanically stretch the preform tip during the ISBM process has been developed.

PETAL-ROD is a device that can be retrofitted to existing ISBM machines with minimum interruption to production rate, with the added benefit that material characteristics similar to the sidewall of the bottle can be achieved in the area of the base. Coupled with an optimized preform design, material weight saving can be improved.