Detection Zone Research Articles

Accuracy improvement via novel ratiometry design in distance-based microfluidic paper based analytical device: instrument-free point of care testing.

Developing accurate, precise, instrument-free, and point-of-need microfluidic paper-based devices is highly significant in clinical diagnosis and biomedical analysis. In the present work, a ratiometric distance-based microfluidic paper-based analytical device (R-DB-μPAD), along with a three-dimensional (3D) multifunctional connector (spacer), was designed to improve the accuracy and detection resolution analyses. Specifically, the novel R-DB-μPAD was used for the accurate and precise detection of ascorbic acid (AA) as a model analyte. In this design, two channels were fabricated as detection zones, with a 3D spacer located between the sampling and detection zones to improve the detection resolution by preventing the reagents mixing from overspreading between these zones. Two probes for AA were used: Fe3+ and 1,10-phenanthroline were deposited in the first channel, and oxidized 3,3',5,5'-tetramethylbenzidine (oxTMB) was added to the second channel. Accuracy improvement of this ratiometry-based design was achieved by enhancing the linearity range and reducing the volume dependency of the output signal. Moreover, the 3D connector improved the detection resolution by eliminating the systematic errors. Under the optimal conditions, the ratio of the distances of the color bands in the two channels was used to construct an analytical calibration curve in the range from 0.05 to 1.2 mM, with a limit of detection of 16 μM. The proposed R-DB-μPAD combined with the connector was successfully used for the detection of AA in orange juice and vitamin C tablets with satisfactory accuracy and precision. This work opens the door for multiplex analysis of various analytes in different matrices.

A trimodal detection paper chip for undisclosed drug "sibutramine" in nutraceuticals.

Nutraceuticals are promoted and marketed with the stated label of being natural as well as safe herbal products. In order to enhance their effectiveness, nutraceuticals are usually adulterated with undeclared constituents. Slimming herbs may contain sibutramine (SBT) which is an FDA-banned ingredient due to its fatal outcomes. This current work's aim is to design a trimodal sensor for SBT detection in different herbal slimming formulations. Screen-printed silver and multi-walled carbon nanotube inks were employed for the potentiometric sensor. The sensor was designed to fill a reaction well in which a carbon dot-silver nanoparticle pair was applied for fluorimetric and colorimetric purposes. The trimodal sensor was designed to fit an 8 mm 2-pin LED strip connector. Potentiometric measurement took place upon application of one sample aliquot then the optical reaction proceeded next in a specified zone for optical detection. These multiple detection mechanisms achieved the required selectivity for SBT determination in the presence of other slimming products' additives. This trimodal sensor satisfied World Health Organization standards for point-of-care devices demonstrating the suggested device as a dynamic part for rapid on-site detection of undisclosed SBT.

Paper biosensors utilize silver nanoparticles for onsite pesticide residue detection

The improper use of pesticides and excessive doses in the long term contribute to climate change and even threaten human health, organisms, and the balance of the ecosystem. A pesticide detection device is needed to monitor its levels to minimize risks to human health and the environment. A paper biosensor was developed in this study to detect organophosphates by utilizing the enzyme acetylcholine esterase (AChE) and silver nanoparticles (AgNP). The Whatman filter paper was used as a visual OP detection zone. AgNP, as an indicator, is adsorbed and gives a brownish-yellow color to the paper, while AChE is immobilized into the film and layered on the paper. The addition of acetylthiocholine chloride as a substrate to the film released thiocholine products which could replace the capping AgNPs causing the AgNPs to aggregate and the paper color to pale. The presence of OP in the sample will inhibit AChE activity so that paper fading is reduced. The biosensor response is quantized as an RGB value, which is determined using an application on a smartphone. The resulting biosensor has excellent performance with a linear range of 0.05-2.00 mg/L, a detection limit of 0.04 mg/L, and a CV of 0.48%. Biosensor measurements on vegetable samples showed conformity with the GCMS results as the standard method. Therefore, this biosensor is suitable for the on-site detection of pesticides offering easy, fast, and inexpensive analysis.

Using a cotton thread-based colorimetric sensor modified by carboxymethylcellulose and cuprizone with smartphone detection for quantification of copper.

In the present work, we report the development of a novel cotton thread-based colorimetric sensor modified by carboxymethylcellulose (CMC) and cuprizone (CPZ) with smartphone detection and its application for the quantitative determination of cupric ions in water and cachaça. The cotton thread/smartphone detection-based colorimetric method is an easily affordable, low-cost technique which allows one to perform real-time and on-field determination analyses, especially with limited financial resources. The method involves the complexation of Cu(II) with CPZ, which causes a change in the coloration of the cotton thread from a shade of white to blue in the detection zone of the colorimetric sensor. The immobilization of CPZ on CMC in the cotton thread leads to the pre-concentration of Cu(II) via a complexation mechanism with colorimetric reaction. The application of the colorimetric sensor allows the quantification of copper in the range from 1 to 12 mg L-1, with a low limit of detection of 0.21 mg L-1. In addition, the recovery assays conducted in samples of water and cachaça resulted in recovery percentages ranging from 84.9% to 107%, which is indicative of a precise method. To validate the precision of the proposed colorimetric method, the values obtained from the quantification analysis were compared with those of the flame atomic absorption spectrometry and a good agreement at the 95% confidence level was obtained.

Mammal population density estimation using camera traps based on a random encounter model: theoretical basis and practical recommendations

Estimating the population density of mammals has long been one of the problematic tasks of both fundamental population ecology and practical programmes for their conservation and management. The majority of methods for population density estimation using camera traps are focused on individually marked species. This review paper presents the theoretical and practical foundations of a method, Random Encounter Model (REM), used for estimating the population density of unmarked mammal species using camera traps. Based on an extensive analysis of the literature and our personal practical experience, we discussed the theory and practice for the application of this method, as well as its strengths and weaknesses. In this method, if we know parameters of the effective detection zone of a camera trap (radius and angle), and the length of the day range, it is possible to correct the trapping rate (i.e. the number of independent trap events per total number of camera traps-nights) in order to calculate the population density of species. The effective detection zone of a camera trap is determined through modelling using computer vision algorithms. The mammal day range is calculated based on its activity level and travel speed, taking into account behavioural patterns based on machine learning models. For REM, a random or systematic design for the camera trap placements should be used. If camera traps are installed against trails or roads, appropriate correction factors must be applied. The effectiveness and reliability of REM has been confirmed by many independent population density estimates, including capture-recapture analyses, visual transect counts, and scat counts. To date, the implementation of REM and its extensions is presented in the R programming environment. It has been established that the main difficulties in the use of the REM are technical imperfections of the camera traps themselves, the relatively large required number of their stations (at least 50 or more), as well as long calibration work. For all these difficulties, possible solutions are proposed. In conclusion, practical recommendations are provided for the use of REM in studies in Protected Areas.

Turbidimetric Determination of Mebeverine Hydrochloride in Pharmaceutical Formulations Using Two Consecutive Detection Zones under Continuous Flow Conditions

A simple, low cost and rapid flow injection turbidimetric method was developed and validated for mebeverine hydrochloride (MBH) determination in pharmaceutical preparations. The developed method is based on forming of a white, turbid ion-pair product as a result of a reaction between the MBH and sodium persulfate in a closed flow injection system where the sodium persulfate is used as precipitation reagent. The turbidity of the formed complex was measured at the detection angle of 180° (attenuated detection) using NAG dual&Solo (0-180°) detector which contained dual detections zones (i.e., measuring cells 1 & 2). The increase in the turbidity of the complex was directly proportional to the increase of the MBH concentration in the range of 2.0-10 µmol/L with a limit of detection 0.35 µmol/L, 0.9981 (R2), and 2.0-12 µmol/L with a limit of detection 0.4 µmol/L and 0.9973 (R2) for measuring cells 1 and 2, respectively. The intra-day precision for three serial estimations of 5.0 and 9.0 µmol/L of MBH exhibited an RSD % of 0.23 % and 0.77 % and 0.68 % and 0.13 %, for cell 1 & 2, respectively. While the inter-day precision for three serials of three days exhibited an RSD % of 0.03 % and 0.77 % and 0.11 % and 0.07 %, for measuring cells 1 & 2, respectively. The accuracy of the developed method has expressed as an error % (E%) and a Rec % (recovery percentage), which was between 100.35 to 101.15 and 99.70 to 101.56 for cell 1 and cell 2, respectively. The present flow injection method has shown no interference effect from the common excipients and permits quantitively determination of 60 samples per hour. The developed method was successfully applied for the quantitative determination of MBH in different tablets containing 135 mg with excellent recovery percentage.

Real-Time Split-Dose PET/CT-Guided Ablation Improves Colorectal Liver Metastasis Detection and Ablation Zone Margin Assessments without the Need for Repeated Contrast Injection.

Real-time split-dose PET can identify the targeted colorectal liver metastasis (CLM) and eliminate the need for repeated contrast administration before and during thermal ablation (TA). This study aimed to assess the added value of pre-ablation real-time split-dose PET when combined with non-contract CT in the detection of CLM for ablation and the evaluation of the ablation zone and margins. A total of 190 CLMs/125 participants from two IRB-approved prospective clinical trials using PET/CT-guided TA were analyzed. Based on detection on pre-TA imaging, CLMs were categorized as detectable, non-detectable, and of poor conspicuity on CT alone, and detectable, non-detectable, and low FDG-avidity on PET/CT after the initial dose. Ablation margins around the targeted CLM were evaluated using a 3D volumetric approach. We found that 129/190 (67.9%) CLMs were detectable on CT alone, and 61/190 CLMs (32.1%) were undetectable or of poor conspicuity, not allowing accurate depiction and targeting by CT alone. Thus, the theoretical 5- and 10-mm margins could not be defined in these tumors (32.1%) using CT alone. When TA intraprocedural PET/CT images are obtained and inspected (fused PET/CT), only 4 CLM (2.1%) remained undetectable or had a low FDG avidity. The addition of PET to non-contrast CT improved CLM detection for ablation targeting, margin assessments, and continuous depiction of the FDG avid CLMs during the ablation without the need for multiple intravenous contrast injections pre- and intra-procedurally.

A prototype microfluidic paper-based chromatic device for simultaneous determination of copper(II) and zinc(II) in urine

The present work proposes the development of a simple and easy-to-make microfluidic paper-based analytical device (µPAD) as a prototype chromatic device for the simultaneous determination of copper and zinc in urine. The µPAD comprises a main circular sampling zone with two identical arms, each containing a circular pretreatment zone and a circular detection zone. Copper(II) and zinc(II) react with 1-(2-pyridylazo)-2-naphthol (PAN) reagent, at pH 6.0 and room temperature, to form chelates colored red and pink, respectively, that can be quantified by digital imaging analysis. The colorimetric reaction sensitivity significantly improved by coating the paper substrate surface with 5% 3-aminopropyltriethoxysilane (APTES) and applying three successive additions of standard or sample onto the sampling zone, without any prior sample preparation step. These combined analytical strategies increased the color intensity of the metal chelates formed on µPAD surface, allowing to detect the desired elements at trace level concentrations. The reaction interferences associated with the presence of foreign elements were eliminated or reduced through the addition of masking agents at different concentrations for each case. Under optimized conditions, excellent linear relationships were obtained in the range 0.1−10 µg mL−1, with determination coefficients (R2) greater than 0.9957. The limits of detection (LOD) and quantification (LOQ), respectively, were 27.1 µg L−1 and 90.3 µg L−1 for copper and 35.9 µg L−1 and 119.7 µg L−1 for zinc. The developed prototype device was validated by analyzing urine certified material samples, obtaining a good concordance without significant difference between the certified values and the measured values. Its application for clinical analysis offers simple, quick, cheap, noninvasive, and environmentally friendly measurements, which are desirable analytical features for point-of-care testing.

Origami 3D-microfluidic paper-based analytical device for detecting carbaryl using mesoporous silica-platinum nanoparticles with a molecularly imprinted polymer shell

Herein, we present a novel Origami 3D-μPAD for colorimetric carbaryl detection using a super-efficient catalyst, namely mesoporous silica-platinum nanoparticles coated with a molecularly imprinted polymer (MSN-PtNPs@MIP). Morphological and structural characterization reveals that coating MIP on the MSN-PtNPs surface significantly increases the selective area, leading to larger numbers of imprinting sites for improved sensitivity and selectivity in determining carbaryl. The as-prepared MSN-PtNPs@MIP was used for catalytic oxidation of 3,3′,5,5′-tetramethylbenzidine (TMB) by H2O2. Carbaryl selectively binds to the cavities embedded on the MSN-PtNPs surface and subsequently inhibits TMB oxidation leading the color to change to light blue. The change of reaction color from dark blue to light blue depends on the concentration of carbaryl within the 3D-μPAD detection zone. This design integrates the advantages of highly efficient sample delivery through micro channels (top layer) and efficient partition/separation paths (bottom layer) of the cellulose substrate to achieve both improved detection sensitivity and selectivity. Assay on the Origami 3D-μPAD can determine carbaryl by ImageJ detection, over a dynamic range of 0.002–20.00 mg kg−1, with a very low limit of detection at 1.5 ng g−1. The developed 3D-μPAD exhibit high accuracy when applied to detect carbaryl in fruits, with satisfactory recoveries from 90.1% to 104.0% and relative differences from the reference HPLC values less than 5.0%. Furthermore, the fabricated Origami 3D-μPAD provides reliable durability and good reproducibility (3.19% RSD for fifteen devices).

High-throughput screening of toxicants that modulate extravillous trophoblast migration

Migration and subsequent invasion of extravillous trophoblasts into the uterus is essential for proper formation of the placenta. Disruption of these processes may result in poor pregnancy outcomes including preeclampsia, placenta accreta, fetal growth restriction, or fetal death. Currently, there are several methods for quantifying cell migration and invasion in vitro, each with limitations. Therefore, we developed a novel, high-throughput method to screen chemicals for their ability to alter human trophoblast migration. Human HTR8/SVneo trophoblast cells were cultured in Oris™ cell migration plates containing stopper barriers. After EVT cells attached and chemicals were added to media, stoppers were removed thereby creating a cell-free detection zone for migration. Entry of trophoblasts into this zone was monitored through imaging every 6 h and used to calculate a relative cell density. Chemicals known to increase (epidermal growth factor) and decrease (pertussis toxin and cadmium) trophoblast migration were used to validate this in vitro method. Next, a panel of environmental chemicals including bisphenols, mycoestrogens, and flame retardants, were screened for their ability to alter trophoblast invasion. In conclusion, a real-time method to track extravillous trophoblast migration offers potential for screening contaminants as placental toxicants.

A Prefatory Approach Towards Monitoring and Detection of Fire Outbreak Using Artificial Neural Network

Fire incidents had always been a primary concern in domestic and industrial properties, buildings, sites and offices. The end results of fire outbreaks can be exceedingly devastating and usually amount to serious losses of lives and properties. They also consist of alarm circuits and some manual call points often referred to as detection zones. Recent researches on fire related systems which are adaptations of the conventional fire systems, have dwelt comprehensively on technologies that can provide possible fire detection services by the integration of sensors that are capable of reacting to certain fire based parameters such as rise in temperature/heat, accumulation of pressure, smoke and other combustible elements etc.. The perceived setback of these sensors is that they need considerable time for responding as they require product of fire (e.g., smoke, temperature etc.) to reach the sensors. However, as computing power increases, and its effect is felt across most spheres of human existence, artificial intelligence based systems have been in the fore front of the discourse due to its ability to adequately minimize or exclude human involvement in most emergency or delicate activities. Therefore, implementing a computer vision-based fire monitoring and detection system using low cost surveillance cameras and artificial neural network is proposed and will sufficiently enhance the ability to monitor, detect and generally manage fire outbreaks in deployed buildings. The proposed system seek to significantly provide a more precise and accurate tool for the detection of fire situations and sufficiently eliminate the tendency for false fire alarms since it will be dependent on convolutional neural network trained with captured frames of video images of fire in order to accurately tell a fire situation. The primary purpose of this study is to develop an intelligent system for monitoring and detection of fire outbreak using computer vision and artificial neural network. Other objectives include: to develop a suitable neural network upon which the model will be trained and to implement the model using python programming language..The technology adopted in this study is expected to perform better unlike the conventional fire detection and alarm systems which are heavily reliant on sensors that are only effective with proximity and location of use.

Enhancing of detection resolution via designing of a multi-functional 3D connector between sampling and detection zones in distance-based microfluidic paper-based analytical device: multi-channel design for multiplex analysis.

One of the problems in the distance-based microfluidic paper-based analytical device (DB-µPAD) that limits the detection resolution is the mixing of reagents from the detection to the sampling zone or vice versa due to spreading by capillary action. In the present paper, to overcome mixing of the reagents in the zones, a multi-functional connector using a three-dimensional (3D) design has been developed externally to connect the two zones. Using such a novel design, it is acertained that there is no any mixing due to the dispersion of the reagents in the two zones. Interestingly, the simple 3D connector has other functions, such as its potential to be used as a masking zone and/or reaction zone whenever is needed. Based on this proposed 3D connector-based DB-µPAD, three parallel microchannels were built as detection zones with one sampling zone for multiplex analysis for the detection of Fe2+, Ni2+, and hardness of water. In the Ni2+ channel, the connector piece worked as both masking part and connection part. In the Fe2+ line, the connector served as the connector and reducing pad (Fe3+ to Fe2+ ions). While in the third channel, the connector has connection function only. Satisfactory limit of detection (LoD), accuracy, and precision were obtained using this design. The LODs obtained with the proposed design were 1.13, 0.62, and 1.87mg.L-1 for total hardness, Fe2+, and Ni2+, respectively.

Fluorescence signal amplification by optical reflection in metal-coated nanowells.

Asignificant amplification in the fluorescence signal is demonstratedwhen measured in metal (aluminum)-coated fluidic wells with volumes on the order of a nanoliter or smaller (nanowells). Photolithographic and wet etching procedures were used to fabricate these nanowells on glass substrates followed by vapor deposition of an aluminum layer on them. The fluorescence signal recorded in these structures was enhanced due to the reflection of the incident and emitted radiation by the metal layer as well as focusing of this light by the curvature of the well surface. While the first effect amplified the background signal in the entire assay chamber, the latter one produced signal hotspots around the edges and center of the nanowell. In this work, we were able to realize over a 20-fold enhancement in the fluorescence signal upon quantitating it at the central hotspot of an aluminum-coated circular nanowell with a depth and photo-patterned diameter of 30µm and 38µm, respectively. More interestingly, our experiments indicate that this enhancement factor may be further improved by optimizing the curvature of the nanowell surface to merge all the signal hotspots within a smaller detection zone. Finally, quantitative assays using horseradish peroxidase samples were performed on the reported signal enhancement platform to further demonstrate its utility for making sensitive analytical measurements.

Microfluidic Magnetic Spatial Confinement Strategy for the Enrichment and Ultrasensitive Detection of MCF-7 and Escherichia coli O157:H7.

A microfluidic magnetic spatial confinement strategy was developed and employed to realize an ultrasensitive cell immunoassay. The straight confined channels in poly(dimethylsiloxane)-glass hybrid microchips were used as the enrichment and detection chambers for the proposed microfluidic magnetic cell immunoassays (μMCI). To accomplish the μMCI, prepared magnetic cell immunocomplexes were introduced into microchannels and preconcentrated in the detection zone under a permanent magnet. The magnetic cell immunocomplexes were constructed from aptamer-/antibody-coated magnetic beads and antibody-linked horseradish peroxidase-labeled target cells to guarantee the specificity and enhance the detection signal generated from the enzyme reaction. The sensitivity enhancement of μMCI was confirmed in a one-dimensional space confined microchamber, especially in the analysis of cells having more enzyme conjugating sites on their surface. This spatial confinement strategy based μMCI was then applied for model cell detection in the microchannel, the limits of detection (LODs) were 2 cells/mL for MCF-7 and 34 colony-forming unit/mL for Escherichia coli O157:H7 (E. coli O157:H7), which corresponded to up to 1202-fold LOD sensitivity improvement compared to the results of the similar immunoassays in microwell plates. The satisfactory selectivity and reproducibility of the strategy were also obtained. Moreover, it enabled rare MCF-7 detection in whole blood and E. coli O157:H7 detection in milk after time-shortened incubation. Constructing an appropriate confined space, this strategy can be extended to detect various cells with higher sensitivity, which provides a valuable approach for rare cell detection in practical applications.

A compact solution for ultra-light drone optical auto-detection and distance estimation using AI

This paper proposes a system for ultra-light drone (ULD) auto–detection using only one non-static optical PTZ camera. The system includes multi-stages of suspect objects detection, clarification, and distance estimation. An AI model for detection and clarification stages is designed based on the YOLOv3 architecture and trained with a practical dataset. In the detection stage, the camera continuously pans, tilts, and zooms to take panoramic images of the detection zone and pass them to the AI model. Once the AI model detects a suspect object, it will switch to the verification stage. In this stage, the camera controlled by the AI model’s output focuses on the target to clarify and estimate the distance to ULD. The proposed solution was implemented and tested with popular fly cams. The results show that the system can auto-detect ultra-light drones effectively with high accuracy.

Dual-mode visual detection strategies of viable pathogens for point-of-care testing

Here, we introduce a power-free foldable poly(methyl methacrylate) (PMMA) microdevice fully integrating DNA extraction, amplification, and visual detection, realized in novel dual modes – colorimetric and aggregate formation – using 4-Aminoantipyrine (4-AP) for monitoring pathogens. The microdevice contains two parts: reaction and detection zones. A sealing film was utilized to connect the two zones and make the device foldable. The FTA card was deposited in the reaction zone for DNA extraction, followed by loop-mediated isothermal amplification (LAMP) at 65 °C for 45 min. When the detection zone is folded toward the reaction zone, paper discs modified with 4-AP placed in the detection zone are delivered to the reaction zone. Specifically, in the presence of LAMP amplicons, 4-AP is oxidized into antipyrine red or generates aggregates by interacting with copper sulfate, forming copper hybrid nanostructure (Cu-hNs). In the absence of LAMP amplicons, 4-AP is not oxidized and maintains yellow color or fails to form aggregates. Furthermore, we introduced the ethidium homodimer-1 (EthD-1) to identify viable bacteria. EthD-1 penetrated the compromised membranes of nonviable cells and prevented further DNA amplification by intercalating with the DNA. In this way, only samples containing viable cells displayed color change or formed aggregates upon reaction with 4-AP. Using this method, SARS-CoV-2 RNA and Enterococcus faecium were identified by naked eye, with the limit of detection of 103 copies/μL and 102 CFU/mL, respectively, within 60 min. The introduced microdevice can be used for rapidly monitoring viable pathogens and controlling outbreaks of infectious disease in resource-limited settings.

Modeling and Quantitative Analysis of Motion Detection in CSI-Based Sensing

Channel state information (CSI) based sensing approaches have unique advantages for fine-grained motion sensing. However, due to the mismatch between the sensing position and detection probability, mapping motion-sensing precision to optimal detection zones is an involved problem. In this letter, we propose a general CSI-based motion detection model, in which the Fresnel Zones and radar detection theory are used to analyze the key factors affecting detection probability. Besides, analytic expressions for the detection probability at arbitrary positions with available and unavailable phases are derived. Finally, numerical results corroborate the theoretical analysis and show that appropriate transceiver deployment and sensing frequency selection can effectively improve sensing performance.

A portable paper-based aptasensor for simultaneous visual detection of two mycotoxins in corn flour using dual-color upconversion nanoparticles and Cu-TCPP nanosheets

A portable paper-based microfluidic aptasensor is established to simultaneously and visually detect zearalenone (ZEN) and ochratoxin A (OTA). The targets at the sample zone can migrate to two detection zones through dual-channels and result in green and blue fluorescence recovery. This is due to the specific recognition by a respective aptamer that destroys fluorescence resonance energy transfer (FRET) from dual-color upconversion nanoparticles (UCNPs) to Cu-TCPP nanosheets. By capturing fluorescent images and analyzing the corresponding RGB value via a smartphone, ZEN and OTA can be analyzed with limits of detection down to 0.44 ng/mL and 0.098 ng/mL in the linear ranges of 0.5–100 ng/mL and 0.1–50 ng/mL, respectively. Satisfactory recoveries are also obtained for ZEN (94.5–103.7 %) and OTA (92.2–106.8 %) in corn flour. With the advantages of simple operation, low sample consumption, and broad adaptability, this promising platform allows for the on-site detection of multiple hazards in food.

A coffee-ring effect-based paper sensor chip for the determination of beta-lactoglobulin in foods via a smartphone

To determine allergen beta-lactoglobulin (β-LG) in foods, a method by a coffee-ring effect (CRE)-based paper sensor chip combined with a smartphone has been developed. The strategy was based on the principle of fluorescence quenching by the quantum dot-aptamer-graphene oxide (QD-Apt-GO) and where the degree of quenching was inversely proportional to the concentration of β-LG. First, the prepared β-LG solution was added to the QD-Apt fluorescent probe solution followed by an appropriate amount of GO. After the reaction, a certain amount of the mixture was dispensed onto the detection zone of the sensor chip, resulting in the spread of the analyte solution by evaporation-driven flow. The QD-Apt and the QD-Apt-β-LG in the mixed solution formed a visible fluorescent coffee-ring. For signal quantitation, an image of the coffee-ring was taken by a smartphone and imported into self-programmed software for analysis. The quantitative results for β-LG were acquired rapidly based on the magnitude of the generated fluorescent coffee-ring. The limit of detection (LOD) for β-LG was 0.048 mg L-1 and the linear range for the optimized assay was 0.39–1000 mg L-1. The method was validated for analysis of real food samples and the results were consistent with those of a commercial ELISA assay kit. The smartphone-based assay provides a simple, economic, compact, and visual detection platform for the determination of β-LG in foods.

A model predictive Goertzel algorithm based active islanding detection for grid integrated photovoltaic systems

A microgrid is a cluster of several energy sources and interconnected loads which are synchronized to operate either in grid connected or islanded mode. To attain higher efficiency and improved power control the microgrid is integrated with power electronic devices. But various problems arise related to protection among which the major issue to be focused on is islanding detection. Whenever an islanding condition arises the balance between load and generation in the islanded circuit can be violated, thereby leading to abnormal frequencies and voltages. This hazardous state observed in the system can be prevented by early detection of occurrence. In this paper, an active islanding detection with integrated PV system for grid based on Predictive Goertzel algorithm is proposed. The proposed single-phase single stage photovoltaic system injects a small harmonic component of the output of the grid and checks point of common coupling (PCC). The Predictive Goertzel algorithm is a discrete Fourier transform that resolve Non detection Zone (NDZ) and detection time. The highlight of this work is to demonstrate the performance of proposed islanding detection method, a single-stage single-phase grid integrated PV system embraces of 1-Φ full bridge inverter, LCL filter and local load (RLC parallel load) is considered. This algorithm is implemented in MATLAB Simulink environment. From the results obtained, the detection time for real time environment has reduced by 200ms compared to existing algorithm.