Cost-effective Detection System Research Articles

Electroextraction of methylene blue from aqueous environmental samples using paper points coupled with hollow fiber membranes

This article introduces a novel approach by coupling paper points with hollow fiber membrane for electroextraction (PP–HF-EE). The method was innovatively applied to extract methylene blue (MB) from large water volumes (up to 580 mL). A comprehensive study of six key parameters – organic filter, acceptor and donor phase composition, extraction time, applied voltage, and sample volume – was conducted using conventional flatbed scanning and digital image analysis. Our results revealed that extraction performance was primarily influenced by time, with low voltages (50 V) and low-conductivity organic filters (1-decanol) yielding comparable results to higher settings (300 V or 1-pentanol). Under optimized conditions (50 V, 60 min, 1-decanol as the organic filter), analytical performance parameters were assessed, demonstrating acceptable precision (RSD <18% for intra- and inter-day measurements) within a linear range of 5–100 μg L−1 (r = 0.98). PP–HF–EE demonstrated reliability through stable and reproducible electric current measurements during all extraction studies. Utilizing an extremely cost-effective detection system, PP–HF–EE achieved detection limits in the low ppb range, highlighting its potential as a promising variation of electromembrane extraction for environmental sample analysis.

Cost-effective detection system of cross-site scripting attacks using hybrid learning approach

Cross-Site Scripting (XSS) attacks inject malicious code payloads into web application logs, triggering stored cross-site scripting execution when accessing the view-logs interface. The destruction produced by the XSS injection susceptibilities is especially significant since the attacker can steal sensitive data such as the stored user's cookies and tokens or control the host remotely by using remote code execution of XSS. For example, if an attacker manages to obtain the cookies of the website administrator, the whole website can be taken over. In this paper, we develop and evaluate the performance of a machine-learning-based XSS detection system for website applications. Particularly, we investigate using three supervised machine learning: optimizable k-nearest neighbours, optimizable naïve bays, and hybrid (ensemble) learning of decision trees. To validate the system's efficacy, we employed the XSS-Attacks-2019 dataset consisting of modern real-world traffic-subjected types of classes normal (benign) or anomaly (XSS attack). To verify the performance evaluation, we have used several conventional metrics, including the confusion matrix analysis, the detection accuracy, the detection precision, the detection sensitivity, the harmonic detection means, and the detection time. The experimental results demonstrated the predominance of the hybrid learning-based XSS detection system. The best performance indicators peaked at 99.8% (accuracy, precision, and sensitivity) with a very short detection time of 103.1 μSec. Conclusively, the proposed hybrid model outpaced several recent XSS-attacks detection systems in the same study area.

Detecting Wind Turbine Blade Icing with a Multiscale Long Short-Term Memory Network

Blade icing is one of the main problems of wind turbines installed in cold climate regions, resulting in increasing power generation loss and maintenance costs. Traditional blade icing detection methods greatly rely on dedicated sensors, such as vibration and acoustic emission sensors, which require additional installation costs and even reduce reliability due to the degradation and failures of these sensors. To deal with this challenge, this paper aims to develop a cost-effective detection system based on the existing operation data collected from the supervisory control and data acquisition (SCADA) systems which are already equipped in large-scale wind turbines. Considering that SCADA data is essentially a multivariate time series with inherent non-stationary and multiscale temporal characteristics, a new wavelet-based multiscale long short-term memory network (WaveletLSTM) approach is proposed for wind turbine blade icing detection. The proposed method incorporates wavelet-based multiscale learning into the traditional LSTM architecture and can simultaneously learn global and local temporal features of multivariate SCADA signals, which improves fault detection ability. A real case study has shown that our proposed WaveletLSTM method achieved better detection performance than the existing methods.

The Monitoring of Black-Odor River by Electronic Nose with Chemometrics for pH, COD, TN, and TP

Black-odor rivers are polluted urban rivers that often are black in color and emit a foul odor. They are a severe problem in aquatic systems because they can negatively impact the living conditions of residents and the functioning of ecosystems and local economies. Therefore, it is crucial to identify ways to mitigate the water quality parameters that characterize black-odor rivers. In this study, we tested the efficacy of an electronic nose (E-nose), which was inexpensive, fast, and easy to operate, for qualitative recognition analysis and quantitative parameter prediction of samples collected from the Yueliang River in Huzhou City. The E-nose sensors were cross-sensitive to the volatile compounds in black-odor water. The device recognized the samples from different river sites with 100% accuracy based on linear discriminant analysis. For water quality parameter predictions, partial least squares regression models based on E-nose signals were established, and the coefficients between the actual water quality parameters (pH, chemical oxygen demand, total nitrogen content, and total phosphorous content) and the predicted values were very high (R2 &gt; 0.90) both in the training and testing sets. These results indicate that E-nose technology can be a fast, easy-to-build, and cost-effective detection system for black-odor river monitoring.

Label-Free Electrochemical Detection of DNA Hybridization Related to Anthrax Lethal Factor by using Carbon Nanotube Modified Sensors

Background: Anthrax Lethal Factor (ANT) is the dominant virulence factor produced by B. anthracis and is the major cause of death of infected animals. In this paper, pencil graphite electrodes GE were modified with single-walled and multi-walled carbon nanotubes (CNTs) for the detection of hybridization related to the ANT DNA for the first time in the literature. Methods: The electrochemical monitoring of label-free DNA hybridization related to ANT DNA was explored using both SCNT and MCNT modified PGEs with differential pulse voltammetry (DPV). The performance characteristics of ANT-DNA hybridization on disposable GEs were explored by measuring the guanine signal in terms of optimum analytical conditions; the concentration of SCNT and MCNT, the concentrations of probe and target, and also the hybridization time. Under the optimum conditions, the selectivity of probe modified electrodes was tested and the detection limit was calculated. Results: The selectivity of ANT probes immobilized onto MCNT-GEs was tested in the presence of hybridization of probe with NC no response was observed and with MM, smaller responses were observed in comparison to full-match DNA hybridization case. Even though there are unwanted substituents in the mixture samples containing both the target and NC in the ratio 1:1 and both the target and MM in the ratio 1:1, it has been found that ANT probe immobilized CNT modified graphite sensor can also select its target by resulting with 20.9% decreased response in comparison to the one measured in the case of full-match DNA hybridization case Therefore, it was concluded that the detection of direct DNA hybridization was performed by using MCNT-GEs with an acceptable selectivity. Conclusion: Disposable SCNT/MCNT modified GEs bring some important advantages to our assay including easy use, cost-effectiveness and giving a response in a shorter time compared to unmodified PGE, carbon paste electrode and glassy carbon electrode developed for electrochemical monitoring of DNA hybridization. Consequently, the detection of DNA hybridization related to the ANT DNA by MCNT modified sensors was performed by using lower CNT, probe and target concentrations, in a shorter hybridization time and resulting in a lower detection limit according to the SCNT modified sensors. In conclusion, MCNT modified sensors can yield the possibilities leading to the development of nucleic acid sensors platforms for the improvement of fast and cost-effective detection systems with respect to DNA chip technology.

Development of a graphene oxide-based assay for the sequence-specific detection of double-stranded DNA molecules.

Graphene oxide (GO) is a promising material for the development of cost-effective detection systems. In this work, we have devised a simple and rapid GO-based method for the sequence-specific identification of DNA molecules generated by PCR amplification. The csp genes of Escherichia coli, which share a high degree of sequence identity, were selected as paradigm DNA templates. All tested csp genes were amplified with unlabelled primers, which can be rapidly removed at the end of the PCR taking advantage of the preferential binding to GO of single-stranded versus duplex DNA molecules. The amplified DNAs (targets) were heat-denatured and hybridized to a fluorescently-labelled single strand oligonucleotide (probe), which recognizes a region of the target DNAs displaying sequence variability. This interaction is extremely specific, taking place with high efficiency only when target and probe show perfect or near perfect matching. Upon GO addition, the unbound fraction of the probe was captured and its fluorescence quenched by the GO’s molecular properties. On the other hand, the probe-target complexes remained in solution and emitted a fluorescent signal whose intensity was related to their degree of complementarity.

Development of a Sensitive Multiplexed Open Circuit Potential System for the Detection of Prostate Cancer Biomarkers

We report the development of a sensitive label-free, cost-effective detection system with simultaneous multi-channel measurement of open circuit potential (OCP) variations for the detection of prostate specific antigen (PSA). We demonstrate a significant increase of 600 times in the sensitivity as compared to the reported literature. To accurately measure OCP variations, a complete monolithic field-effect transistor (FET)-input ultra-low input bias current instrumentation amplifier is used to form the electronic circuit to measure the variation between a working electrode and a reference electrode. This amplifier electronic system setup provides a differential voltage measurement with high input impedance and low input bias current. Since no current is applied to the electrochemical system, a true and accurate measurement of the variation can be performed. This is the first report on the use of DNA aptamers with an OCP system where we employed a DNA aptamer against PSA. An optimised ratio of anti-PSA DNA aptamer with 6-mercapto-1-hexanol (MCH) was used to fabricate the aptasensor using gold electrodes. The electrodes are hosted in a cell with an automated flow system. A wide range of concentrations of PSA (0.1 to 100 ng/mL) were injected through the system. The sensor could potentially differentiate 0.1 ng/mL PSA from blank measurement, which is well below the required clinical range (>1 ng/mL). The sensor was also challenged with 4% human serum albumin and human kallikrein2 as control proteins where the sensor demonstrated excellent selectivity. The developed system can be further generalised to various other targets using specific probes.

Mimetic peptide and special antibody: promising agents for optimizing hapten-analyzing systems

Immunoassays are simple, rapid, and cost-effective detection systems that are widely used for the detection of haptens in varied matrices.

Three‐phase transient state estimation algorithm for distribution systems

The detection of the source and severity of disturbances is important as this allows network companies to respond faster and remediate the problem more quickly. After an event, knowledge of the severity of a disturbance at various busbars gives understanding of what equipment was subjected to and an indication of possible improvements needed to mitigate further events. Owing to the cost, it is impractical to fully monitor the network, however, with judicious selection of measurement points, and using state estimation techniques, allows information at unmonitored locations to be determined. Hence, a cost effective detection system can be developed. This study documents a new three-phase transient state estimation algorithm and demonstrates its performance with realistic background harmonic voltage distortion and with measurement error. The transient state estimation is based on the numerical integrator substitution method (Dommel's method for discretising the differential equations).

Review: advances in electrochemical genosensors-based methods for monitoring blooms of toxic algae

Harmful algal blooms (HABs), which have expanded worldwide in their occurrence and frequency, are a serious menace to aquatic ecosystems and humans. The development of rapid, accurate and cost-effective detection systems for toxic algal monitoring in aquatic environments is urgently required. Although many efforts have been devoted to develop reliable tools to monitor the entire spectrum of existing toxic algae, a portable semi-automated system that enables HAB monitoring at a low cost is still not available for general purchase. This work reviews the challenges and opportunities in translating the remarkable progress of electrochemical genosensors-based methods towards practical in situ HAB monitoring applications. It is specifically focused on reviewing the optimised methods for a detection system based on a sandwich hybridisation assay (SHA) performed over transducer platforms of different materials, geometries and dimensions and presenting the diverse advantages and disadvantages among them. Probe design and specificity and optimisation of the genosensor in terms of hybridisation conditions and electrochemical signal are discussed as well as their long-term stability and storage and semi-automation attempts. With continuous innovation and attention to key challenges, we expect semi-automatic devices containing DNA-based electrochemical biosensors to have an important impact upon monitoring of serious HAB events.

Quantitative measurement of human anti-HCV Core immunoglobulins on an electrical biochip platform

The importance of early diagnosis devices increased continuously in the last two decades and plays an important role in medical care. Early stage diagnosis of e.g. ovarian cancer, HCV-infection or HIV-infection increased the survival rate of patients significantly. In parallel there is a trend leaving centralized diagnostic laboratories in order to get closer to the patient to perform analysis of even complex parameters in the field. This often saves time, increases the prognosis of the patient significantly and is cheaper in many cases. In this study we employ a rapid and cost-effective detection system based on electrical biochip technology for decentralized detection of anti-HCV Core immunoglobulins (HCV antibodies). In this system the qualitative and quantitative detection of virus-specific antibodies is done by an ELISA directly on a gold electrode array utilizing HCV Core as capture antigen. The biochip allows antibody detection within 20 min. Signal amplification was done by enzyme labelling and by “Single Electrode Redox Cycling”. This method enhances current signals up to 40-fold in comparison to simple oxidation. The sensitivity of this approach is therefore comparable to a standard microtiter plate based ELISA with a 9-fold saving of assay time. This biochip system allows serum or whole blood analysis with no signal loss or increasing background caused by the red blood cells. Fields of application can be hospital emergency units where only single detections have to be conducted in a quick manner or by the general practitioner.

Quantitative Physiology of the Precancerous Cervix In Vivo through Optical Spectroscopy

Cervical cancer is the second most common female cancer worldwide. The ability to quantify physiological and morphological changes in the cervix is not only useful in the diagnosis of cervical precancers but also important in aiding the design of cost-effective detection systems for use in developing countries that lack well-established screening and diagnostic programs. We assessed the capability of a diffuse reflectance spectroscopy technique to identify contrasts in optical biomarkers that vary with different grades of cervical intraepithelial neoplasia (CIN) from normal cervical tissues. The technology consists of an optical probe and an instrument (with broadband light source, dispersive element, and detector), and a Monte Carlo algorithm to extract optical biomarker contributions including total hemoglobin (Hb) concentration, Hb saturation, and reduced scattering coefficient from the measured spectra. Among 38 patients and 89 sites examined, 46 squamous normal sites, 18 CIN 1, and 15 CIN 2(+) sites were included in the analysis. Total Hb was statistically higher in CIN 2(+) (18.3 +/- 3.6 microM, mean +/- SE) compared with normal (9.58 +/- 1.91 microM) and CIN 1 (12.8 +/- 2.6 microM), whereas scattering was significantly reduced in CIN 1 (8.3 +/- 0.8 cm(-1)) and CIN 2(+) (8.6 +/- 1.0 cm(-1)) compared with normal (10.2 +/- 1.1 cm(-1)). Hemoglobin saturation was not significantly altered in CIN 2(+) compared with normal and CIN 1. The difference in total Hb is likely because of stromal angiogenesis, whereas decreased scattering can be attributed to breakdown of collagen network in the cervical stroma.

Electrical recognition of label-free oligonucleotides upon streptavidin-modified electrode surfaces

For the purpose of developing a direct label-free electrochemical detection system, we have systematically investigated the electrochemical signatures of each step in the preparation procedure, from a bare gold electrode to the hybridization of label-free complementary DNA, for the streptavidin-modified electrode. For the purpose of this investigation, we obtained the following pertinent data; cyclic voltammogram measurements, electrochemical impedance spectra and square wave voltammogram measurements, in Fe(CN)6 3−/Fe(CN)6 4− solution (which was utilized as the electron transfer redox mediator). The oligonucleotide molecules on the streptavidin-modified electrodes exhibited intrinsic redox activity in the ferrocyanide-mediated electrochemical measurements. Furthermore, the investigation of electrochemical electron transfer, according to the sequence of oligonucleotide molecules, was also undertaken. This work demonstrates that direct label-free oligonucleotide electrical recognition, based on biofunctional streptavidin-modified gold electrodes, could lead to the development of a new biosensor protocol for the expansion of rapid, cost-effective detection systems.