A Gradient-Type Method For Real-Time State Estimation Of Water Distribution Networks

Drinking water distribution networks risk exposure to malicious or accidental contamination. Several levels of responses are conceivable. One of them consists to install a sensor network to monitor the system on real time. Once a contamination has been detected, this is also important to take appropriate counter-measures. In the SMaRT-OnlineWDN project, this relies on modeling to predict both hydraulics and water quality. An online model use makes identification of the contaminant source and simulation of the contaminated area possible. The objective of this paper is to present SMaRT-OnlineWDN experience and research results for hydraulic state estimation with sampling frequency of few minutes. A least squares problem with bound constraints is formulated to adjust demand class coefficient to best fit the observed values at a given time. The criterion is a Huber function to limit the influence of outliers. A Tikhonov regularization is introduced for consideration of prior information on the parameter vector. Then the Levenberg-Marquardt algorithm is applied that use derivative information for limiting the number of iterations. Confidence intervals for the state prediction are also given. The results are presented and discussed on real networks in France and Germany.

Neural network based estimation of torque in induction motors for real-time applications

Induction motors are largely used in several industry sectors. The selection of an induction motor has still been inaccurate because in most of the cases the load behavior in its shaft is completely unknown. The proposal of this article is to use artificial neural networks for torque estimation with the purpose of best selecting the induction motors rather than conventional methods, which use classical identification techniques and mechanical load modeling. Since proposed approach estimates the torque behavior from the transient to the steady state, one of its main contributions is the potential to also be implemented in control schemes for real-time applications. Simulation results are also presented to validate the proposed approach.

Quantification of bovine cytokine gene expression using real-time RT-PCR methodology

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Quantitative real-time PCR identifies a critical region of deletion on 22q13 related to prognosis in oral cancer

Quantitative real time PCR was performed on genomic DNA from 40 primary oral carcinomas and the normal adjacent tissues. The target genes ECGFB, DIA1, BIK, and PDGFB and the microsatellite markers D22S274 and D22S277, mapped on 22q13, were selected according to our previous loss of heterozygosity findings in head and neck tumors. Quantitative PCR relies on the comparison of the amount of product generated from a target gene and that generated from a disomic reference gene (GAPDH-housekeeping gene). Reactions have been performed with normal control in triplicates, using the 7700 Sequence Detection System (PE Applied Biosystems). Losses in the sequences D22S274 (22q13.31) and in the DIA1 (22q13.2-13.31) gene were detected in 10 out of 40 cases (25%) each. Statistically significant correlations were observed for patients with relative copy number loss of the marker D22S274 and stages T3-T4 of disease (P=0.025), family history of cancer (P = 0.001), and death (P = 0.021). Relative copy number loss involving the DIA1 gene was correlated to family history of cancer (P<0.001), death (P=0.002), and consumption of alcohol (P=0.026). Log-rank test revealed a significant decrease in survival (P=0.0018) for patients with DIA1 gene loss. Relative copy number losses detected in these sequences may be related to disease progression and a worse prognosis in patients with oral cancer.

Real-time optical monitoring of the dip coating process

A significant part of film production by the coating industry is based on wet bench processes, where better understanding of their temporal dynamics could facilitate control and optimization. In this work, in situ laser interferometry is applied to study properties of flowing liquids and quantitatively monitor the dip coating batch process. Two oil standards Newtonian, non-volatile, with constant refractive indices and distinct flow properties - were measured under several withdrawing speeds. The dynamics of film physical thickness then depends on time as t(-1/2), and flow characterization becomes possible with high precision (linear slope uncertainty of +/-0.04%). Resulting kinematic viscosities for OP60 and OP400 are 1,17 +/- 0,03. St and 9,9 +/- 0,2 St, respectively. These results agree with nominal values, as provided by the manufacturer. For more complex films (a multi-component sol-gel Zirconyl Chloride aqueous solution) with a varying refractive index, through a direct polarimetric measurement, allowing also determination of the temporal evolution of physical thickness (uncertainty of +/- 0,007 microns) is also determined during dip coating.

CONTROL OF UNCERTAIN DYNAMIC-SYSTEMS USING STRICTLY POSITIVE REAL SYSTEMS

This paper presents necessary and sufficient conditions to turn a linear time-invariant system with p outputs, m inputs, p greater-than-or-equal-to m and using only inputs and outputs measurements into a Strictly Positive Real (SPR).Two results are presented. In the first, the system compensation is made by two static compensators, one of which forward feeds the outputs and the second back feeds the outputs of the nominal system.The second result presents conditions for the Walcott and Zak variable structure observer-controller synthesis. In this problem, if the nominal system is given by {A,B,C}, then the compensated system is given by {A+GC,B,FC} where F and G are the constant compensation matrices. These results are useful in the control system with uncertainties.

Linear quadratic Gaussian control of discrete-time Markov jump linear systems with horizon defined by stopping times

The linear quadratic Gaussian control of discrete-time Markov jump linear systems is addressed in this paper, first for state feedback, and also for dynamic output feedback using state estimation. in the model studied, the problem horizon is defined by a stopping time τ which represents either, the occurrence of a fix number N of failures or repairs (T N), or the occurrence of a crucial failure event (τ δ), after which the system paralyzed. From the constructive method used here a separation principle holds, and the solutions are given in terms of a Kalman filter and a state feedback sequence of controls. The control gains are obtained by recursions from a set of algebraic Riccati equations for the former case or by a coupled set of algebraic Riccati equation for the latter case. Copyright © 2005 IFAC.

Presence of infectious agents and co-infections in diarrheic dogs determined with a real-time polymerase chain reaction-based panel

Background: Infectious diarrhea can be caused by bacteria, viruses, or protozoan organisms, or a combination of these. The identification of co-infections in dogs is important to determine the prognosis and to plan strategies for their treatment and prophylaxis. Although many pathogens have been individually detected with real-time polymerase chain reaction (PCR), a comprehensive panel of agents that cause diarrhea in privately owned dogs has not yet been established. The objective of this study was to use a real-time PCR diarrhea panel to survey the frequencies of pathogens and co-infections in owned dogs attended in a veterinary hospital with and without diarrhea, as well the frequency in different countries. Feces samples were tested for canine distemper virus, canine coronavirus, canine parvovirus type 2 (CPV-2), Clostridium perfringens alpha toxin (CPA), Cryptosporidium spp., Giardia spp., and Salmonella spp. using molecular techniques.Results: In total, 104 diarrheic and 43 control dogs that were presented consecutively at a major private veterinary hospital were included in the study. Overall, 71/104 (68.3%) dogs with diarrhea were positive for at least one pathogen: a single infection in 39/71 dogs (54.9%) and co-infections in 32/71 dogs (45.1%), including 21/32 dogs (65.6%) with dual, 5/32 (15.6%) with triple, and 6/32 (18.8%) with quadruple infections. In the control group, 13/43 (30.2%) dogs were positive, all with single infections only. The most prevalent pathogens in the diarrheic dogs were CPA (40/104 dogs, 38.5%), CPV-2 (36/104 dogs, 34.6%), and Giardia spp. (14/104 dogs, 13.5%). CPV-2 was the most prevalent pathogen in the dual co-infections, associated with CPA, Cryptosporidium spp., or Giardia spp. No statistical difference (P = 0.8374) was observed in the duration of diarrhea or the number of deaths (P = 0.5722) in the presence or absence of single or co-infections.Conclusions: Diarrheic dogs showed a higher prevalence of pathogen infections than the controls. Whereas the healthy dogs had only single infections, about half the diarrheic dogs had co-infections. Therefore, multiple pathogens should be investigated in dogs presenting with diarrhea. The effects of multiple pathogens on the disease outcomes remain unclear because the rate of death and the duration of diarrhea did not seem to be affected by these factors.

Increasing Utilization of US Electric Grids via Smart Technologies: Integration of Load Management, Real Time Pricing, Renewables, EVs and Smart Grid Sensors

Electric power grids throughout the world suffer from serious inefficiencies associated with under-utilization due to demand patterns, engineering design and load following approaches in use today. These grids consume much of the world’s energy and represent a large carbon footprint. From material utilization perspectives significant hardware is manufactured and installed for this infrastructure often to be used at less than 20-40% of its operational capacity for most of its lifetime. These inefficiencies lead engineers to require additional grid support and conventional generation capacity additions when renewable technologies (such as solar and wind) and electric vehicles are to be added to the utility demand/supply mix. Using actual data from the PJM [PJM 2009] the work shows that consumer load management, real time price signals, sensors and intelligent demand/supply control offer a compelling path forward to increase the efficient utilization and carbon footprint reduction of the world’s grids. Underutilization factors from many distribution companies indicate that distribution feeders are often operated at only 70-80% of their peak capacity for a few hours per year, and on average are loaded to less than 30-40% of their capability. By creating strong societal connections between consumers and energy providers technology can radically change this situation. Intelligent deployment of smart sensors, smart electric vehicles, consumer-based load management technology very high saturations of intermittent renewable energy supplies can be effectively controlled and dispatched to increase the levels of utilization of existing utility distribution, substation, transmission, and generation equipment. The strengthening of these technology, society and consumer relationships requires rapid dissemination of knowledge (real time prices, costs & benefit sharing, demand response requirements) in order to incentivize behaviors that can increase the effective use of technological equipment that represents one of the largest capital assets modern society has created.

Real-time adaptive models for the personalized prediction of glycemic profile in type 1 diabetes patients

Prediction of glycemic profile is an important task for both early recognition of hypoglycemia and enhancement of the control algorithms for optimization of insulin infusion rate. Adaptive models for glucose prediction and recognition of hypoglycemia based on statistical and artificial intelligence techniques are presented.

Detection of Mycoplasma mycoides subsp. mycoides SC in bronchoalveolar lavage fluids of cows based on a TaqMan real-time PCR discriminating wild type strains from an lppQ(-) mutant vaccine strain used for DIVA-strategies

Contagious bovine pleuropneumonia (CBPP) is the most serious cattle disease in Africa, caused by Mycoplasma mycoides subsp. mycoides small-colony type (SC). CBPP control strategies currently rely on vaccination with a vaccine based on live attenuated strains of the organism. Recently, an lppQ(-) mutant of the existing vaccine strain T1/44 has been developed (Janis et al., 2008). This T1lppQ(-) mutant strain is devoid of lipoprotein LppQ, a potential virulence attribute of M. mycoides subsp. mycoides SC. It is designated as a potential live DIVA (Differentiating Infected from Vaccinated Animals) vaccine strain allowing both serological and etiological differentiation. The present paper reports on the validation of a control strategy for CBPP in cattle, whereby a TaqMan real-time PCR based on the lppQ gene has been developed for the direct detection of M. mycoides subsp. mycoides SC in ex vivo bronchoalveolar lavage fluids of cows and for the discrimination of wild type strains from the lppQ(-) mutant vaccine strain.

Application of conventional and real-time fluorescent ITS1 rDNA PCR for detection of Besnoitia besnoiti infections in bovine skin biopsies

Besnoitia besnoiti, an apicomplexan protozoan parasite, is the causative agent of bovine besnoitiosis. This infection may dramatically affect body condition, and, in males, lead to irreversible infertility. While identification of clinical cases and their histopathological confirmation is relatively simple to carry out, finding subclinical forms of infection is more difficult, thus a more sensitive test for the identification of the etiological agent may be an appropriate diagnostic tool. We have developed the ITS1 rDNA-sequence-based conventional and real-time PCR which are highly sensitive and specific for the detection of B. besnoiti infection in cattle. A recombinant internal positive control was introduced to assess possible sample-related inhibitory effects during the amplification reaction and, in order to prevent false-positive results, a pre-PCR treatment of potentially contaminating dU-containing PCR product with uracil-DNA-glycosylase (UDG) was followed.

Real-time multiplex PCR assays for reliable detection of Clostridium perfringens toxin genes in animal isolates

Typing of Clostridium perfringens strains by PCR-based determination of toxin genes proved to be a reliable method for diagnosis of enterotoxaemia in various animal species. We report the establishment and validation of three real-time fluorogenic (TaqMan) multiplex PCRs for the detection of C. perfringens alpha-, beta-, beta2-, epsilon-, entero- and iota-toxin genes. The composition of the PCRs was chosen with regard to robustness of the assays and in order to increase sensitivity compared to the conventional simplex PCRs. The combination of probe dyes selected for the real-time assays (FAM/TAMRA, Cy-5/BHQ-2 and VIC/TAMRA) as well as the designation of the chromosome-borne alpha-toxin as internal positive control allowed the creation of highly specific and sensitive, as well as time and cost effective PCRs. One hundred and three strains of C. perfringens isolated in Switzerland derived from clinical or suspected cases of enterotoxaemia in 10 different animal species were tested. The toxin genotypes were in agreement in both the conventional PCRs and the newly designed multiplex PCRs. Furthermore, the real-time PCR carried out as simplex allows to quantitate the copy numbers of plasmid-borne toxin genes in relation to the chromosomally located alpha-toxin gene.

Assessment of a real-time PCR test to diagnose syphilis from diverse biological samples

OBJECTIVES: To investigate the contribution of a real-time PCR assay for the detection of Treponema pallidum in various biological specimens with the secondary objective of comparing its value according to HIV status. METHODS: Prospective cohort of incident syphilis cases from three Swiss hospitals (Geneva and Bern University Hospitals, Outpatient Clinic for Dermatology of Triemli, Zurich) diagnosed between January 2006 and September 2008. A case-control study was nested into the cohort. Biological specimens (blood, lesion swab or urine) were taken at diagnosis (as clinical information) and analysed by real-time PCR using the T pallidum 47 kDa gene. RESULTS: 126 specimens were collected from 74 patients with primary (n = 26), secondary (n = 40) and latent (n = 8) syphilis. Among primary syphilis, sensitivity was 80% in lesion swabs, 28% in whole blood, 55% in serum and 29% in urine, whereas among secondary syphilis, it was 20%, 36%, 47% and 44%, respectively. Among secondary syphilis, plasma and cerebrospinal fluid were also tested and provided a sensitivity of 100% and 50%, respectively. The global sensitivity of T pallidum by PCR (irrespective of the compartment tested) was 65% during primary, 53% during secondary and null during latent syphilis. No difference regarding serology or PCR results was observed among HIV-infected patients. Specificity was 100%. CONCLUSIONS: Syphilis PCR provides better sensitivity in lesion swabs from primary syphilis and displays only moderate sensitivity in blood from primary and secondary syphilis. HIV status did not modify the internal validity of PCR for the diagnosis of primary or secondary syphilis.