Virtual metrology enabled early stage prediction for enhanced control of multi-stage fabrication processes

Semiconductor fabrication involves several sequential processing steps with the result that critical production variables are often affected by a superposition of affects over multiple steps. In this paper a Virtual Metrology (VM) system for early stage measurement of such variables is presented; the VM system seeks to express the contribution to the output variability that is due to a defined observable part of the production line. The outputs of the processed system may be used for process monitoring and control purposes. A second contribution of this work is the introduction of Elastic Nets, a regularization and variable selection technique for the modelling of highly-correlated datasets, as a technique for the development of VM models. Elastic Nets and the proposed VM system are illustrated using real data from a multi-stage etch process used in the fabrication of disk drive read/write heads. © 2013 IEEE.

A rapid PCR-based assay for identification of cryptic Myotis spp. (M. mystacinus, M. brandtii and M. alcathoe)

The development of a quick PCR-based method to distinguish European cryptic Myotis spp., Myotis mystacinus, Myotis brandtii and Myotis alcathoe is described. Primers were designed around species-specific single nucleotide polymorphisms (SNP's) in the ND1 mitochondrial gene, and a pair of control primers was designed in the 12S mitochondrial gene. A multiplex of seven primer combinations produces clear species-specific bands using gel electrophoresis. Robustness of the method was tested on 33 M. mystacinus, 16 M. brandtii and 15 M. alcathoe samples from across the European range of these species. The method worked well on faecal samples collected from maternity roosts of M. mystacinus. The test is intended to aid collection of data on these species through a rapid and easy identification method with the ability to use DNA obtained from a range of sources including faecal matter.

Rapid single-nucleotide polymorphism-based identification of clonal Pseudomonas aeruginosa isolates from patients with cystic fibrosis by the use of real-time PCR and high-resolution melting curve analysis

Pseudomonas aeruginosa genotyping relies mainly upon DNA fingerprinting methods, which can be subjective, expensive and time-consuming. The detection of at least three different clonal P. aeruginosa strains in patients attending two cystic fibrosis (CF) centres in a single Australian city prompted the design of a non-gel-based PCR method to enable clinical microbiology laboratories to readily identify these clonal strains. We designed a detection method utilizing heat-denatured P. aeruginosa isolates and a ten-single-nucleotide polymorphism (SNP) profile. Strain differences were detected by SYBR Green-based real-time PCR and high-resolution melting curve analysis (HRM10SNP assay). Overall, 106 P. aeruginosa sputum isolates collected from 74 patients with CF, as well as five reference strains, were analysed with the HRM10SNP assay, and the results were compared with those obtained by pulsed-field gel electrophoresis (PFGE). The HRM10SNP assay accurately identified all 45 isolates as members of one of the three major clonal strains characterized by PFGE in two Brisbane CF centres (Australian epidemic strain-1, Australian epidemic strain-2 and P42) from 61 other P. aeruginosa strains from Australian CF patients and two representative overseas epidemic strain isolates. The HRM10SNP method is simple, is relatively inexpensive and can be completed in <3 h. In our setting, it could be made easily available for clinical microbiology laboratories to screen for local P. aeruginosa strains and to guide infection control policies. Further studies are needed to determine whether the HRM10SNP assay can also be modified to detect additional clonal strains that are prevalent in other CF centres.

Identification of systemic immune response markers through metabolomic profiling of plasma from calves given an intra-nasally delivered respiratory vaccine

Vaccination procedures within the cattle industry are important disease control tools to minimize economic and welfare burdens associated with respiratory pathogens. However, new vaccine, antigen and carrier technologies are required to combat emerging viral strains and enhance the efficacy of respiratory vaccines, particularly at the point of pathogen entry. New technologies, specifically metabolomic profiling, could be applied to identify metabolite immune-correlates representative of immune protection following vaccination aiding in the design and screening of vaccine candidates. This study for the first time demonstrates the ability of untargeted UPLC-MS metabolomic profiling to identify metabolite immune correlates characteristic of immune responses following mucosal vaccination in calves. Male Holstein Friesian calves were vaccinated with Pfizer Rispoval® PI3 + RSV intranasal vaccine and metabolomic profiling of post-vaccination plasma revealed 12 metabolites whose peak intensities differed significantly from controls. Plasma levels of glycocholic acid, N-[(3α,5β,12α)-3,12-Dihydroxy-7,24-dioxocholan-24-yl]glycine, uric acid and biliverdin were found to be significantly elevated in vaccinated animals following secondary vaccine administration, whereas hippuric acid significantly decreased. In contrast, significant upregulation of taurodeoxycholic acid and propionylcarnitine levels were confined to primary vaccine administration. Assessment of such metabolite markers may provide greater information on the immune pathways stimulated from vaccine formulations and benchmarking early metabolomic responses to highly immunogenic vaccine formulations could provide a means for rapidly assessing new vaccine formulations. Furthermore, the identification of metabolic systemic immune response markers which relate to specific cell signaling pathways of the immune system could allow for targeted vaccine design to stimulate key pathways which can be assessed at the metabolic level.

Intelligent potentiostat for identification of heavy metals in situ

This article presents a low-cost portable electrochemical instrument capable of on-site identification of heavy metals. The instrument acquires metal-specific voltage and current signals by the application of differential pulse anodic stripping voltammetry. This technique enhances the analytical current and rejects the background current, resulting in a higher signal-to-noise ratio for a better detection limit. The identification of heavy metals is based on an intelligent machine-based method using a multilayer perceptron neural network consisting of three layers of neurons. The neural network is implemented using a 16 bit microcontroller. The system is developed for use in the field in order to avoid expensive and time-consuming procedures and can be used in a variety of situations to help environmental assessment and control. 

LC- HRMS based metabolomics in food safety and doping control – DeTECH21

Issues surrounding the misuse of prohibited and licensed substances in animals destined for food production and performance sport competition continue to be an enormous challenge to regulatory authorities charged with enforcing their control. Efficient analytical strategies are implemented to screen and confirm the presence of a wide range of exogenous substances in various biological matrices. However, such methods rely on the direct measurement of drugs and/or their metabolites in a targeted mode, allowing the detection of restricted number of compounds. As a consequence, emerging practices, in particular the use of natural hormones, designer drugs and low-dose cocktails, remain difficult to handle from a control point of view. A new SME-led FP7 funded project, DeTECH21, aims to overcome current limitations by applying an untargeted metabolomics approach based on liquid chromatography coupled to high resolution mass spectrometry and bioinformatic data analysis to identify bovine and equine animals which have been exposed to exogenous substances and assist in the identification of administered compounds. Markerbased strategies, dealing with the comprehensive analysis of metabolites present in a biological sample (urine/plasma/tissue), offer a reliable solution in the areas of food safety and animal sport doping control by effective, high-throughput and sensitive detection of exogenously administered agents. Therefore, the development of the first commercially available forensic test service based on metabolomics profiling will meet 21st century demands in animal forensics.

Proteomic identification of plasma proteins as markers of growth promoter abuse in cattle

Growth-promoting agents are continually misused for increasing animal growth and fraudulent gain in the meat industry, yet detection rates from conventional targeted testing for drug residues do not reflect this. This is because testing currently relies on direct detection of drugs or related metabolites and administrators of such compounds can take adaptive measures to avoid detection through the use of endogenous or unknown drugs, and low dose or combined mixtures. New detection methods are needed which focus on the screening of biological responses of an animal to such growth-promoting agents as it has been demonstrated that genomic, proteomic and metabolomics profiles are altered by xenobiotic intake. Therefore, an untargeted proteomics approach using comparative two-dimensional gel electrophoresis (2DE) was carried out to identify putative proteins altered in plasma after treatment with oestradiol, dexamethasone or prednisolone. Twenty-four male cattle were randomly assigned to four groups (n = 6) for experimental treatment over 40 days, namely a control group of non-treated cattle, and three groups administered 17β-oestradiol-3-benzoate (0.01 mg/kg, intramuscular), dexamethasone sodium phosphate (0.7 mg/day, per os) or prednisolone acetate (15 mg/day, per os), respectively. Plasma collected from each animal at day 25 post study initiation was subjected to proteomic analysis by 2DE for comparison of protein expression between treated and untreated animals. Analysis of acquired gel images revealed 22 plasma proteins which differed in expression by more than 50 % (p < 0.05) in treated animals compared to untreated animals. Proteins of interest underwent identification by LC–MS/MS analysis and were found to have associated roles in transport, blood coagulation, immune response and metabolism pathways. In this way, seven proteins are highlighted as novel biomarker candidates including transthyretin which is shown to be significantly increased in all treatment groups compared to control animals and potentially may find use as global markers of suspect anabolic practice.

Identification of Dynamics of Surface Suction Over an Airfoil at Low Reynolds Numbers

This paper deals with identification of dynamics in suction control of airfoils for low Reynolds number regimes (8 x 10^4 - 5 x 10^5). In particular, the dynamics of interest is the map that relates suction pressure and surface pressure. Identification of such dynamics is of use to a variety of active control applications including suction control in small/medium wind turbines which operate in these Reynolds number regimes. Prior research has largely focused on higher Reynolds number regimes, creating a need for such a study. Towards identifying the said dynamic relations, experiments were conducted on NACA0012 airfoil in a wind tunnel. The dynamic relation between suction and surface pressure was identified as an overdamped second order system.

Identification of human neutrophil defensins (HNPs1-3) in biopsies of squamous cell carcinomas of the human tongue

It has previously been reported that the a-defensins, found in the granules of polymorphonuclear leukocytes (neutrophils/ PMNs), are cytolytic for human tumour cells in vitro. Objective: To identify and quantify the a- defensins, HNP-1, HNP-2 and HNP-3 in healthy and tumour tissue from patients with oral squamous cell carcinoma using HPLC, mass spectrometry and amino acid sequencing. Methods: All patients (n=5) were diagnosed with oral squamous cell carcinoma of the tongue.Biopsy tissue from the site of the tumour (n=5) and a non-affected region of the tongue (n=5) was snap frozen and subsequently stored at -70 ºC until analysed. Peptides were extracted from the 10 tissue biopsies using acidified ethanol. Peptide extracts were separated by reverse-phase HPLC . All tumour and control tissue samples were individually analysed under identical conditions with a flow rate of l ml/min, ambient column temperature and absorbance detection at 214 and 280 nm. Fractions (1ml) were collected automatically. HPLC fractions were analysed by MALDI-MS using a linear time-of-flight Voyager DE-mass spectrometer (PerSeptive Biosystems, UK). Using this system the detection limit was 10 fmol. Peptides with molecular masses corresponding to those reported for the a-defensins were deemed of interest and were further subject to complete structural analysis by automated Edman degradation using an Applied Biosystems 491 Procise microsequencer. Results: MALDI-MS revealed a triad of peptides of molecular masses 3442 Da, 3371 Da and 3486 Da in both healthy and tumour tissue. Full length sequence data were obtained for the three a-defensins, unequivocally identifying their presence in both tumour and healthy tissue. Analysis of the MALDI-MS and sequence data indicated that the a-defensins were overexpressed (up to 12 fold) in tumour tissue. Conclusion: This study demonstrates the feasibility of screening tumour tissue for novel peptides/proteins using HPLC and MALDI-MS.The role of a-defensins in oral squamous cell carcinoma of the tongue requires further investigation.

Special section on intelligent control systems and signal processing

The IFAC International Conference on Intelligent Control Systems and Signal Processing (ICONS 2003) was organized under the auspices of the recently founded IFAC Technical Committee on Cognition and Control, and it was the first IFAC event specifically devoted to this theme. Recognizing the importance of soft-computing techniques for fields covered by other IFAC Technical Committees, ICONS 2003 was a multi-track Conference, co-sponsored by four additional Technical Committees: Computers for Control, Optimal Control, Control in Agriculture, and Modelling, Identification and Signal Processing. The Portuguese Society for Automatic Control (APCA) hosted ICONS 2003, which was held at the University of Algarve, Faro, Portugal.

Intelligent control and signal processing

SYSID is organized every three years. This will be the first SYSID symposium in the 3rd millenium and the second SYSID symposium to take place in The Netherlands. The symposium covers all major aspects of system identification, experimental modelling, signal processing and adaptive control from theoretical and methodological developments to practical applications in a wide range of application areas. The aim of the meeting is to promote the research activities and the cooperation between researchers in these areas. To enhance the applications and industrial perspective of the symposium, participation from industrial authors is particularly encouraged. This will be the first Council meeting after the World Congress in Barcelona last year. The year that has passed has been very active indeed. Following the restructuring of the Technical Board which was endorsed in Barcelona, the 39 Technical Committees within the Technical Board have taken up their work and, after a year, we may say that work is proceeding very smoothly and a lot of activities are going on which will be reported on in greater detail after the meeting of the Technical Board in Rotterdam. The scopes of all these 39 Technical Committees have been revised and were published in Issue 1, 2003 of the IFAC Newsletter, which was published on the web. Shortly a document for download with all the scopes will be available on the web.

Design and implementation of a real-time data acquisition system for the identification of dynamic temperature models in a hydroponic greenhouse

This text describes a real data acquisition and identification system implemented in a soilless greenhouse located at the University of Algarve (south of Portugal). Using the Real Time Workshop, Simulink, Matlab and the C programming language a system was developed to perform real-time data acquisition from a set of sensors.