The present study was aimed to establish a novel TaqMan real-time PCR (RTm-PCR) for detecting and typing bovine viral diarrhea virus (BVDV), and also to develop a diagnostic proto- col which simplifies sample collection and processing. Universal primers and TaqMan-MGB probes were designed from the known sequences of conserved 5′ - and 3′-untranslated regions (5’UTR, 3’UTR) of the NADL strain of BVDV. Prior to optimizing the assay, cDNAs were tran- scribed in vitro to make standard curves. The sensitivity, specificity and stability (reproducibility) were evaluated. The RTm-PCR was tested on the 312 feces specimens collected from persistently infected (PI) calves. The results showed the optimum conditions for RTm-PCR were 17.0 μmol/L primer, 7.5 μmol/L probe and 51.4°C annealing temperature. The established TaqMan RTm-PCR assay could specially detect BVDV without detecting any other viruses. Its detection limit was 1.55×100 copies/μL for viral RNA. It was 10000-fold higher than conventional PCR with excel- lent specificity and reproducibility. 312 samples were tested using this method and universal PCR from six dairy farms, respectively. Positive detections were found in 49 and 44 feces samples, respectively. The occurrence rate was 89.80%. In conclusion, the established TaqMan RTm-PCR could rapidly detect BVDV and effectively identify PI cattle. The detection limit of RTm-PCR was 1.55 copies/μL. It will be beneficial for enhancing diagnosis and therapy efficacy and reduce losses in cattle farms.
The present study investigated the expression of androgen receptor (AR) in neurons of the anterior pelvic ganglion (APG) and celiac-superior mesenteric ganglion (CSMG; ganglion not involved in the innervation of reproductive organs) in the male pig with quantitative real-time PCR (qPCR) and immunohistochemistry. qPCR investigations revealed that the level of AR gene expression in the APG tissue was approximately 2.5 times higher in the adult (180-day-old) than in the juvenile (7-day-old) boars. Furthermore, in both the adult and juvenile animals it was sig- nificantly higher in the APG than in CSMG tissue (42 and 85 times higher, respectively). Immu- nofluorescence results fully confirmed those obtained with qPCR. In the adult boars, nearly all adrenergic (DβH-positive) and the majority of non-adrenergic neurons in APG stained for AR. In the juvenile animals, about half of the adrenergic and non-adrenergic neurons were AR-posi- tive. In both the adult and juvenile animals, only solitary CSMG neurons stained for AR. The present results suggest that in the male pig, pelvic neurons should be considered as an element of highly testosterone-dependent autonomic circuits involved in the regulation of urogenital func- tion, and that their sensitization to androgens is a dynamic process, increasing during the prepu- bertal period.
In this paper, an algorithm that monitors the power system to detect and classify power quality events in real time is presented. The algorithm is able to detect events caused by waveform distortions and variations of the RMS values of the voltage. Detection of the RMS events is done by comparing the RMS values with certain thresholds, while detection of waveform distortions is made using an algorithm based on multiharmonic leasts-squares fitting.
Natural gas is a mixture of 21 components and it is widely used in industries and homes. Knowledge of its thermodynamic properties is essential for designing appropriate processes and equipment. This paper presents simple but precise correlations of how to compute important thermodynamic properties of natural gas. As measuring natural gas composition is costly and may not be effective for real time process, the correlations are developed based on measurable real time properties. The real time properties are temperature, pressure and specific gravity of the natural gas. Calculations with these correlations are compared with measured values. The validations show that the average absolute percent deviation (AAPD) for compressibility factor calculations is 0.674%, for density is 2.55%, for Joule-Thomson coefficient is 4.16%. Furthermore, in this work, new correlations are presented for computing thermal properties of natural gas such as enthalpy, internal energy and entropy. Due to the lack of experimental data for these properties, the validation is done for pure methane. The validation shows that AAPD is 1.31%, 1.56% and 0.4% for enthalpy, internal energy and entropy respectively. The comparisons show that the correlations could predict natural gas properties with an error that is acceptable for most engineering applications.
In this paper, some issues of building a reliable, distributed measurement system for monitoring of water quality in reservoir Lake Dobczyckie are presented. The system is based on a measurement station that has the shape of a floating buoy which is supposed to be at anchor on the reservoir. Wireless data transmission problems that were encountered during the development of the buoy, modeling a radio link, and measurements of actual signal strength on the reservoir are discussed. A mathematical approach to procedures of early situation assessment was conducted, and specialized procedures were designed for measurement stations of the system. It is also discussed how such computations can improve a qualitative assessment of system performance in terms of real-time messaging
This paper deals with real-time (RT) simulators applied in power electronic applications and implemented in a real inverter. The process of preparing and starting up an active rectifier prototype (with an active filter function), using the real-time OPAL RT simulator is given. The control system of the converter and the results of simulation using the Matlab/Simulink suite are discussed.
This article presents an efficient method of modelling acoustic phenomena for real-time applications such as computer games. Simplified models of reflections, transmission, and medium attenuation are described along with assessments conducted by a professional sound designer. The article introduces representation of sound phenomena using digital filters for further digital audio processing.
This paper develops a new model of market abuse detection in real time. Market abuse is detected, as Minenna (2003) proposed, on the basis of prediction intervals. The model structure is based on the discrete-time, extended market model introduced by Monteiro, Zaman, Leitterstorf (2007) to analyze the market cleanliness. Parameters of the expected return equation are assumed, however, to be time-varying and estimated under the state-space framework using the extended Kalman filter postulated by Chou, Engle, Kane (1992) to capture the GARCH effect in returns. QML estimation is performed on intraday data; its utilization is proposed as an alternative to the continuous time modeling by Minenna (2003). This framework is generalized to the bivariate case which enables the analysis of daily open/close data. The paper also extends procedures of the statistical verification of the estimated state-space model to include the uncertainty arising from time-invariant parameters.
Modern control and measurement systems are equipped with interfaces to operate in local area networks and are typically intended to perform complicated data processing and control algorithms. The authors propose a digital system for rapid prototyping of target application devices. The concept solution separates the processing and control section from the hardware interface and user interface section. Both sections constitute independent ARM-based controllers interconnected via a direct USB link. Popular libraries can be used and low-level procedures developed, which enhances the system’s economic viability. A test unit developed for the purpose of the study was built around a SoC ARM7 microsystem and an off-the-shelf palmtop device. It demonstrated a continuous data stream transfer capability up to 150 kB per second, which was sufficient to monitor the performance of an electricity line.
A variety of algorithms allows gesture recognition in video sequences. Alleviating the need for interpreters is of interest to hearing impaired people, since it allows a great degree of self-sufficiency in communicating their intent to the non-sign language speakers without the need for interpreters. State-of-theart in currently used algorithms in this domain is capable of either real-time recognition of sign language in low resolution videos or non-real-time recognition in high-resolution videos. This paper proposes a novel approach to real-time recognition of fingerspelling alphabet letters of American Sign Language (ASL) in ultra-high-resolution (UHD) video sequences. The proposed approach is based on adaptive Laplacian of Gaussian (LoG) filtering with local extrema detection using Features from Accelerated Segment Test (FAST) algorithm classified by a Convolutional Neural Network (CNN). The recognition rate of our algorithm was verified on real-life data.