Abstract: In this paper, a panel of single-stranded DNA aptamers with high affinity and specificity against Salmonella Paratyphi A was selected from an enriched oligonucleotide pool by a whole-cell-Systematic Evolution of Ligands by Exponential Enrichment (SELEX) procedure, during which four other Salmonella serovars were used as counter-selection targets. It was determined through a fluorescence assay that the selected aptamers had high binding ability and specificity to this pathogen. The dissociation constant of these aptamers were up to nanomolar range, and aptamer Apt22 with the lowest Kd (47 ± 3 nM) was used in cell imaging experiments. To detect this bacteria with high specificity and cost-efficiently, a novel useful detection method was also constructed based on the noncovalent self-assembly of single-walled carbon nanotubes (SWNTs) and DNAzyme-labeled aptamer detection probes. The amounts of target bacteria could be quantified by exploiting chemoluminescence intensity changes at 420 nm and the detection limit of the method was 103 cfu/mL. This study demonstrated the applicability of Salmonella specific aptamers and their potential for use in the detection of Salmonella in food, clinical and environmental samples.
Abstract: In this paper, a human electrocardiogram (ECG) identification system based on ensemble empirical mode decomposition (EEMD) is designed. A robust preprocessing method comprising noise elimination, heartbeat normalization and quality measurement is proposed to eliminate the effects of noise and heart rate variability. The system is independent of the heart rate. The ECG signal is decomposed into a number of intrinsic mode functions (IMFs) and Welch spectral analysis is used to extract the significant heartbeat signal features. Principal component analysis is used reduce the dimensionality of the feature space, and the K-nearest neighbors (K-NN) method is applied as the classifier tool. The proposed human ECG identification system was tested on standard MIT-BIH ECG databases: the ST change database, the long-term ST database, and the PTB database. The system achieved an identification accuracy of 95% for 90 subjects, demonstrating the effectiveness of the proposed method in terms of accuracy and robustness.
Abstract: It is easy to measure energy consumption with a power meter. However, energy savings cannot be directly computed by the powers measured using existing power meter technologies, since the power consumption only reflects parts of the real energy flows. The International Performance Measurement and Verification Protocol (IPMVP) was proposed by the Efficiency Valuation Organization (EVO) to quantify energy savings using four different methodologies of A, B, C and D. Although energy savings can be estimated following the IPMVP, there are limitations on its practical implementation. Moreover, the data processing methods of the four IPMVP alternatives use multiple sensors (thermometer, hygrometer, Occupant information) and power meter readings to simulate all facilities, in order to determine an energy usage benchmark and the energy savings. This study proposes a simple sensor platform to measure energy savings. Using usually the Electronic Product Code (EPC) global standard, an architecture framework for an information system is constructed that integrates sensors data, power meter readings and occupancy conditions. The proposed sensor platform is used to monitor a building with a newly built vertical garden system (VGS). A VGS shields solar radiation and saves on energy that would be expended on air-conditioning. With this platform, the amount of energy saved in the whole facility is measured and reported in real-time. The data are compared with those obtained from detailed measurement and verification (M&V) processes. The discrepancy is less than 1.565%. Using measurements from the proposed sensor platform, the energy savings for the entire facility are quantified, with a resolution of ±1.2%. The VGS gives an 8.483% daily electricity saving for the building. Thus, the results show that the simple sensor platform proposed by this study is more widely applicable than the four complicated IPMVP alternatives and the VGS is an effective tool in reducing the carbon footprint of a building.
Abstract: The objective of the current research was not only to provide a fast and automatic positioning platform for single cells, but also improved biomolecular manipulation techniques. In this study, an automatic platform for cell positioning using electroosmotic flow and image processing technology was designed. The platform was developed using a PCI image acquisition interface card for capturing images from a microscope and then transferring them to a computer using human-machine interface software. This software was designed by the Laboratory Virtual Instrument Engineering Workbench, a graphical language for finding cell positions and viewing the driving trace, and the fuzzy logic method for controlling the voltage or time of an electric field. After experiments on real human leukemic cells (U-937), the success of the cell positioning rate achieved by controlling the voltage factor reaches 100% within 5 s. A greater precision is obtained when controlling the time factor, whereby the success rate reaches 100% within 28 s. Advantages in both high speed and high precision are attained if these two voltage and time control methods are combined. The control speed with the combined method is about 5.18 times greater than that achieved by the time method, and the control precision with the combined method is more than five times greater than that achieved by the voltage method.
Abstract: A single-chip sensor system-on-a-chip (SoC) that implements radio for 2.4 GHz, complete digital baseband physical layer (PHY), 10-bit sigma-delta analog-to-digital converter and dedicated sensor calibration hardware for industrial sensing systems has been proposed and integrated in a 0.18-μm CMOS technology. The transceiver’s building block includes a low-noise amplifier, mixer, channel filter, receiver signal-strength indicator, frequency synthesizer, voltage-controlled oscillator, and power amplifier. In addition, the digital building block consists of offset quadrature phase-shift keying (OQPSK) modulation, demodulation, carrier frequency offset compensation, auto-gain control, digital MAC function, sensor calibration hardware and embedded 8-bit microcontroller. The digital MAC function supports cyclic redundancy check (CRC), inter-symbol timing check, MAC frame control, and automatic retransmission. The embedded sensor signal processing block consists of calibration coefficient calculator, sensing data calibration mapper and sigma-delta analog-to-digital converter with digital decimation filter. The sensitivity of the overall receiver and the error vector magnitude (EVM) of the overall transmitter are −99 dBm and 18.14%, respectively. The proposed calibration scheme has a reduction of errors by about 45.4% compared with the improved progressive polynomial calibration (PPC) method and the maximum current consumption of the SoC is 16 mA.
Abstract: Bio-composite coatings consisting of poly(3,4-ethylenedioxythiophene) (PEDOT) and tyrosinase (Ty) were successfully electrodeposited on conventional size gold (Au) disk electrodes and microelectrode arrays using sinusoidal voltages. Electrochemical polymerization of the corresponding monomer was carried out in the presence of various Ty amounts in aqueous buffered solutions. The bio-composite coatings prepared using sinusoidal voltages and potentiostatic electrodeposition methods were compared in terms of morphology, electrochemical properties, and biocatalytic activity towards various analytes. The amperometric biosensors were tested in dopamine (DA) and catechol (CT) electroanalysis in aqueous buffered solutions. The analytical performance of the developed biosensors was investigated in terms of linear response range, detection limit, sensitivity, and repeatability. A semi-quantitative multi-analyte procedure for simultaneous determination of DA and CT was developed. The amperometric biosensor prepared using sinusoidal voltages showed much better analytical performance. The Au disk biosensor obtained by 50 mV alternating voltage amplitude displayed a linear response for DA concentrations ranging from 10 to 300 μM, with a detection limit of 4.18 μM.
