Counting Technique Research Articles

Bismuth (Bi3+) based lead-free halide perovskitoid for light driven applications: A potential low-toxic alternative for lead (Pb2+)

Bismuth-based perovskite-like materials are recognised as feasible optoelectronic alternatives to lead-based perovskites. High toxicity and limited environmental stability of Pb-based perovskite are the principal hurdles for their practical use, whereas Bismuth (Bi3+) based materials exhibit relatively low toxicity. In this study, we fabricated (FPEA)BiI4 (FPEA = Fluorophenylethyl amine, as a hydrophobic aromatic spacer) and explored its compatibility in the field of photocatalysis and solar cells. UV–Vis, photoluminescence (PL) and time-correlated single photon counting (TCSPC) techniques were used to understand the optoelectronic properties of the material. These fabricated thin films were used towards toxic MBT remediation. Solar cells (in n-i-p configuration) were also fabricated using (FPEA)BiI4 and their photo conversion efficiency (PCE) was tested under AM1.5 illumination.

Monitoring fatigue cracks in riveted plates using a sideband intensity based nonlinear ultrasonic technique

Aluminum structures are routinely used in aircraft due to their lightweight and corrosion resistance properties. Multi-layered aluminum plates are generally joined by rivets forming regions which are prone to fatigue crack formation in an aircraft. Therefore, the detection and monitoring of fatigue cracks at rivet joints in aluminum structures are crucial for ensuring flight safety. In this study, piezoelectric sensors were utilized to generate and detect Lamb waves on aluminum plates with rivet joints to investigate the feasibility of a newly developed Sideband Peak Count (SPC) technique for detecting fatigue cracks around these joints. To overcome the limitations of existing SPC-I (Sideband Peak Count – Index) and SPI (Sideband Peak Intensity) techniques in capturing harmonic and modulating wave frequencies due to material nonlinearity, a comprehensive index, the Sideband Intensity Index (SII) is introduced. Comparative analysis with existing SPC-I and SPI techniques confirm the effectiveness of the SII technique. This investigation shows that the SII technique significantly improves the detection capability of initial fatigue cracks around rivet joints on aluminum plates. This study offers a more efficient method for detecting critical fatigue cracks in rivet joints.

Quantification of play behaviour in calves using automated ultra-wideband location data and its association with age, weaning and health status

Play behaviour can act as an indicator of positive animal welfare. Previous attempts to predict play behaviour in farmed calves are limited because of the classification methods used, which lead to overestimation, and the short time periods that calves are observed. The study aimed to automatically classify and quantify play behaviour in farmed calves using location data from ultra-wide band sensors and to investigate factors associated with play behaviour. Location data were collected from 46 calves in three cohorts for a period of 18 weeks. Behavioural observations from video footage were merged with location data to obtain a total of 101.36 h of labelled data. An AdaBoost ensemble learning algorithm was implemented to classify play behaviour. To account for overestimation, generally seen in low-prevalence behaviours, an adjusted count technique was applied to the outputs of the classifier. Two generalized linear mixed models were fitted to investigate factors (e.g. age, health) associated with duration of play and number of play instances per day. Our algorithm identified play behaviour with > 94% accuracy when evaluated on the test set with no animals used for training, and 16% overestimation, which was computed based on the predicted number of samples of play versus the number of samples labelled as play on the test set. The instances and duration of play behaviour per day significantly decreased with age and sickness, whilst play behaviour significantly increased during and after weaning. The instances of play also significantly decreased as mean temperature increased. We suggest that the quantification method that we used could be used to detect and monitor other low prevalence behaviours (e.g. social grooming) from location data, including indicators of positive welfare.

Examining the response of Botrytis cinerea to aqueous ozone: inactivation kinetics, structure, physiology, and growth in different strawberries cultivars

ABSTRACT This work aimed to study the kinetics and mechanisms of Botrytis cinerea conidia inactivation by aqueous ozone treatments (2.5 ± 0.8 mg O3 L−1 and 4.2 ± 0.2 mg O3 L−1, 0.5–16 min), using conventional plate count technique, flow cytometry analysis (FCM), and transmission electron microscopy (TEM). The effect of treatments on the mold incidence on two artificially contaminated strawberries cultivars over refrigerated storage (6 ± 1 °C) was also investigated. The inactivation pattern of B. cinerea conidial suspensions depended on initial level of the microorganism, dissolved ozone concentration and treatment time. Non-linear survival curves were obtained and fitted successfully with the Weibullian model. FCM and TEM analysis revealed alterations in the physiological state and ultrastructure of ozonated conidia that depended on the ozone dose. Ozonation (4.4 mg O3L−1, 5–10 min) reduced B. cinerea incidence throughout storage in strawberries of cv. Fortuna, but no effect was found in cv. Aroma.

Using indirect survey techniques to investigate the relationship between employee personal experience of abusive supervision and job performance

PurposeTo propose the use of indirect survey protocols, in general and the item count technique (ICT), in particular, that ensure participant anonymity in organizations to explore the effect of employee perceived abusive supervision on job performance.Design/methodology/approachWe apply ICT to a sample of 363 employees (52.6% female) from Greek organizations. Utilizing multivariate statistical techniques, we investigated how employees assess the impact of their personal encounters with abusive supervision on job performance. This approach allowed us to explore the percentage of employees perceiving negative effects on job performance, distinguishing our study from previous studies that primarily focus on quantifying the extent or magnitude of abusive supervision in organizational settings. Also, we investigated how employee socio-demographic characteristics, human capital characteristics and affective traits relate to the evaluation of experienced abusive supervision as a negative factor for their job performance.FindingsWe found that approximately 62% of the respondents evaluated personal experience of abusive supervision as negatively affecting their job performance. We also found that the likelihood of employees evaluating personal experience of abusive supervision as having a negative impact on their job performance is: (1) higher for female employees, (2) does not depend on employee age, job tenure and education; (3) is lower for employees with managerial roles and (4) increases with employee trait negative affectivity.Originality/valueThe study is a response to the call for researchers to use innovative methods for advancing abusive supervision research. The study highlights the significance of taking a proactive stance towards addressing abusive supervision in the workplace, by using indirect survey methods that ensures employee anonymity. The results have implications for organizational strategies aimed at increasing awareness of abusive supervision and its impact on employee performance.

Stimulated Emission of Signal Photons from Dark Matter Waves.

The manipulation of quantum states of light has resulted in significant advancements in both dark matter searches and gravitational wave detectors. Current dark matter searches operating in the microwave frequency range use nearly quantum-limited amplifiers. Future high frequency searches will use photon counting techniques to evade the standard quantum limit. We present a signal enhancement technique that utilizes a superconducting qubit to prepare a superconducting microwave cavity in a nonclassical Fock state and stimulate the emission of a photon from a dark matter wave. By initializing the cavity in an |n=4⟩ Fock state, we demonstrate a quantum enhancement technique that increases the signal photon rate and hence also the dark matter scan rate each by a factor of 2.78. Using this technique, we conduct a dark photon search in a band around 5.965GHz (24.67 μeV), where the kinetic mixing angle ε≥4.35×10^{-13} is excluded at the 90% confidence level.

Indirect Questioning Technique Related to Sensitive Quantitative Variables with Options for Direct, Randomized and Item Count Responses

Randomized Response (RR) Technique (RRT) pioneered by Warner (1965) is a useful tool to elicit responses on sensitive characteristics, such as induced abortions, drug abuse, drunken driving, total amount of counterfeit notes of a particular denomination held by individuals in the population, etc. There exists a huge literature on Randomized Response (RR) devices for estimation of finite population mean of quantitative variables, sensitive in nature mostly based on Eichhorn and Hayre (1983). Device-I and Device-II vide Chaudhuri and Christofides (2013) allow estimation of population mean of sensitive quantitative variables using sample chosen by a general sampling design. On the other hand, Item Count Technique (ICT), described elaborately in Chaudhuri and Christofides (2013), is an alternative to RRT for respondents who do not choose to provide RRs. While some respondents may find a variable as sensitive, others may find it innocuous enough to provide a direct response (DR) about his/her true value. In such a case, Optional Randomized Response (ORR) Technique (ORRT) with options for DR and RR was introduced by Chaudhuri and Mukherjee (1985). Pal (2007) proposed an ORR device which offers choices for RR and ICT to the respondents for giving their answers. A new ORRT with options for DR, RR and ICT was provided by Shaw and Pal (2021) for eliciting indirect responses on sensitive characteristics. As this device relates to estimation of population proportion of sensitive characteristics, an attempt has been made to extend it for sensitive quantitative variables. Further, to take care of individuals’ varying choices for DR, RR and ICT and to protect the privacy of the respondents’ choices, this paper develops an ORR device allowing the respondents chosen by a general sampling design, to choose any one of the three options according to their choices. International Journal of Statistical Sciences, Vol.24(1), March, 2024, pp 155-170

Navigating the Aerosolized Frontier: A Comprehensive Review of Bioaerosol Research Post-COVID-19

In the wake of the COVID-19 pandemic, the scientific community has been galvanized to unravel the enigmatic role of bioaerosols in the transmission of infectious agents. This literature review, anchored in the extensive Web of Science Core Collection database covering the period from 1990 to 2023, utilizes a bibliometric approach to chart the dynamic landscape of bioaerosol research. It meticulously documents the paradigm shifts and burgeoning areas of inquiry that have emerged in the aftermath of the pandemic. This review meticulously maps out the sources and detection strategies of pathogens in a variety of ecosystems. It clearly shows that impaction and filtration sampling methods, followed by colony counting and PCR-based detection techniques, were predominantly used in the scientific works within the previous three decades. It synthesizes the progress and limitations inherent in a range of models for predicting aerosol-mediated pathogen spread and provides a comparative analysis of eDNA technology and traditional analytical techniques for bioaerosols. The accuracy of these detection methods and forecasting models is paramount for the early recognition of transmission risks, which, in turn, paves the way for prompt and effective disease mitigation strategies. By providing a thorough analysis of the historical progression and current state of bioaerosol research, this review illuminates the path ahead, identifying the critical research needs that will drive the field’s advancement in the years to come.

Engineering an Exact Pseudo-Boolean Model Counter

Model counting, a fundamental task in computer science, involves determining the number of satisfying assignments to a Boolean formula, typically represented in conjunctive normal form (CNF). While model counting for CNF formulas has received extensive attention with a broad range of applications, the study of model counting for Pseudo-Boolean (PB) formulas has been relatively overlooked. Pseudo-Boolean formulas, being more succinct than propositional Boolean formulas, offer greater flexibility in representing real-world problems. Consequently, there is a crucial need to investigate efficient techniques for model counting for PB formulas. In this work, we propose the first exact Pseudo-Boolean model counter, PBCount , that relies on knowledge compilation approach via algebraic decision diagrams. Our extensive empirical evaluation shows that PBCount can compute counts for 1513 instances while the current state-of-the-art approach could only handle 1013 instances. Our work opens up several avenues for future work in the context of model counting for PB formulas, such as the development of preprocessing techniques and exploration of approaches other than knowledge compilation.

DISCount: Counting in Large Image Collections with Detector-Based Importance Sampling

Many applications use computer vision to detect and count objects in massive image collections. However, automated methods may fail to deliver accurate counts, especially when the task is very difficult or requires a fast response time. For example, during disaster response, aid organizations aim to quickly count damaged buildings in satellite images to plan relief missions, but pre-trained building and damage detectors often perform poorly due to domain shifts. In such cases, there is a need for human-in-the-loop approaches to accurately count with minimal human effort. We propose DISCount -- a detector-based importance sampling framework for counting in large image collections. DISCount uses an imperfect detector and human screening to estimate low-variance unbiased counts. We propose techniques for counting over multiple spatial or temporal regions using a small amount of screening and estimate confidence intervals. This enables end-users to stop screening when estimates are sufficiently accurate, which is often the goal in real-world applications. We demonstrate our method with two applications: counting birds in radar imagery to understand responses to climate change, and counting damaged buildings in satellite imagery for damage assessment in regions struck by a natural disaster. On the technical side we develop variance reduction techniques based on control variates and prove the (conditional) unbiasedness of the estimators. DISCount leads to a 9-12x reduction in the labeling costs to obtain the same error rates compared to naive screening for tasks we consider, and surpasses alternative covariate-based screening approaches.

Breaking the Mold: Towards Rapid and Cost-Effective Microbial Contamination Detection in Paints and Cosmetics Using ATP-Bioluminescence

Traditional culture-based methods, though a “gold standard” for bacterial detection in various industrial sectors, do often not fulfill today’s high requirements regarding rapidity, on-site applicability, and cost-efficiency both during operation and evaluation. Here, the feasibility of using an adenosine triphosphate (ATP)-based assay for determining microbial contaminations in paints and cosmetics was investigated and compared with standard plate count techniques and dipslides. Therefore, we initially determined the level of sensitivity and assessed the accuracy and concordance among the different methods via spiking tests using a mix of frequently abundant bacterial species to simulate microbial contamination. Bioluminescence intensity was linearly proportional to log colony counts over five orders of magnitude (R2 = 0.99), indicating a high level of sensitivity. Overall, the accuracy varied depending on the test specimen, most probably due to matrix-related quenching effects. Although the degree of conformity was consistently higher at target concentrations ≥ 105 CFU·mL−1, microbial contaminations were detectable down to 103 CFU·mL−1, thus meeting the high requirements of various industries. ATP-based results tended to be within an order of magnitude lower than the reference. However, bearing that in mind, the developed assay serves as a rapid, real-time alternative for routine quality control and hygiene monitoring.

A Seamless Deep Learning Approach for Apple Detection, Depth Estimation, and Tracking Using YOLO Models Enhanced by Multi-Head Attention Mechanism

Considering precision agriculture, recent technological developments have sparked the emergence of several new tools that can help to automate the agricultural process. For instance, accurately detecting and counting apples in orchards is essential for maximizing harvests and ensuring effective resource management. However, there are several intrinsic difficulties with traditional techniques for identifying and counting apples in orchards. To identify, recognize, and detect apples, apple target detection algorithms, such as YOLOv7, have shown a great deal of reflection and accuracy. But occlusions, electrical wiring, branches, and overlapping pose severe issues for precisely detecting apples. Thus, to overcome these issues and accurately recognize apples and find the depth of apples from drone-based videos in complicated backdrops, our proposed model combines a multi-head attention system with the YOLOv7 object identification framework. Furthermore, we provide the ByteTrack method for apple counting in real time, which guarantees effective monitoring of apples. To verify the efficacy of our suggested model, a thorough comparison assessment is performed with several current apple detection and counting techniques. The outcomes adequately proved the effectiveness of our strategy, which continuously surpassed competing methods to achieve exceptional accuracies of 0.92, 0.96, and 0.95 with respect to precision, recall, and F1 score, and a low MAPE of 0.027, respectively.

IFN‑γ induces apoptosis in gemcitabine‑resistant pancreatic cancer cells.

Pancreatic ductal adenocarcinoma (PDAC) is the most prevalent and aggressive form of pancreatic cancer. Gemcitabine (GEM), the first‑line treatment for PDAC, which alleviates symptoms and enhances the quality of life of patients. However, it is prone to lead to the development of drug resistance during treatment. Interferon (IFN)‑γ exhibits antitumor and immunomodulatory properties. The present study aimed to explore the impact of IFN‑γ on the viability, migration and apoptosis of GEM‑resistant pancreatic cancer cells. Firstly, a GEM‑resistant pancreatic cancer cell line, named PANC‑1/GEM, was constructed. Hematoxylin and eosin staining analyzed the cell morphology, whereas reverse transcription‑quantitative PCR (RT‑qPCR) assessed the expression levels of the drug‑resistance genes multidrug resistance‑associated protein (MRP) and breast cancer resistance protein (BCRP). The MTT assay and cell counting techniques were used to determine the appropriate concentration of IFN‑y and its effects on cell viability. The IFN‑γ‑induced apoptosis of PANC‑1/GEM cells was assessed using an Apoptosis Detection Kit, whereas the impact of IFN‑γ on the migration of these cells was evaluated using a wound‑healing assay. The MTT assay revealed a resistance index of 22.4 in the PANC‑1/GEM cell line. RT‑qPCR indicated that, compared with in wild‑type cells, the PANC‑1/GEM resistant strain exhibited lower MRP and higher BCRP mRNA expression levels. The optimal concentration of IFN‑γ for affecting PANC‑1/GEM cells was determined to be 0.3 µg/ml. At this concentration, IFN‑γ induced PANC‑1/GEM cell apoptosis, along with a notable reduction in migration. Following treatment of PANC‑1/GEM cells with IFN‑γ, MRP expression increased whereas BCRP mRNA expression decreased, indicating a reversal in their drug‑resistance gene expression. In conclusion, IFN‑γ exhibited antitumor immune properties by upregulating MRP and downregulating BCRP expression, reversing drug‑resistance gene expression, and reducing cell viability and migration, while promoting apoptosis in PANC‑1/GEM cells. IFN‑γ could potentially serve as a treatment option for patients with GEM‑resistant pancreatic cancer.

Quantifying distortion in time-correlated single photon counting: a universal parameter.

One major drawback of the classic time-correlated single photon counting (TCSPC) technique is pileup-related distortion. To keep it under a reasonable level, the maximum count rate has to be reduced, posing a serious limitation to the overall measurement speed. This means that there is an intrinsic trade-off between speed and distortion: either count rate is raised, but distortion is worsened, or distortion is minimized at the expense of speed. In both cases, it is impossible to precisely evaluate the degree of distortion introduced. Here comes our new, to the best of our knowledge, figure of merit, which is able to provide a numerical estimate of the distortion whatever the signal shape is, marking a real turning point in the way of doing TCSPC. In this article, this new parameter will be defined and its effectiveness will be demonstrated by means of mathematical computations.

Fabrication and characterization of mesoporous calcium silicate and silver-incorporated mesoporous calcium silicate nanoparticles with low cytotoxicity and antibacterial properties as a dental biomaterial

AimThis study aimed to fabricate and characterize Mesoporous calcium silicate nanoparticles (MCSNs) and silver-incorporated Mesoporous calcium silicate nanoparticles (Ag-MCSNs) as bioactive nanoparticles either for hybridization with contemporary endodontic materials to improve their bioactivity by using (MCSNs) as a drug delivery system, and to achieve both low cytotoxicity and enhanced antibacterial activity by incorporating Ag which is avery potent antibacterial agent to form (Ag-MCSNs) as new multifunctional materials. MethodsThe MCSNs and Ag-MCSNs nanoparticles were made using the template method. Both nanoparticles' mesoporous structure, specific surface area, pore volume, pore size, and shape were examined and characterized by FTIR, XRD, EDS, DLS, and FE-SEM. The ion release, pH change, cytotoxicity by MTT assay, and antibacterial properties against planktonic Enterococcus faecalis were further investigated by colony forming units (CFUs) counting technique. ResultMCSNs nanoparticles were prepared and successfully incorporated with silver as Ag-MCSNs. MCSNs and Ag-MCSN nanoparticles had the characteristic mesoporous material shape and over time showed sustained ion release (Ca2+,Si4+ and Ag+) ,with an alkaline pH value (8.2–9.0). Both materials showed no obvious cytotoxicity but more cell viability with MCSNs (vitality value is >70%). Both nanoparticles showed antibacterial activity against Enterococcus faecalis (p < 0.05). With MCSNs containing Ag (Ag-MCSNs) showing higher antibacterial effect. ConclusionBoth mesoporous calcium silicate nanoparticles (MCSNs) and mesoporous calcium silicate nanoparticles loaded with silver (Ag-MCSNs) displayed a characteristic mesoporous structure, ion release, alkaline pH, minimal cytotoxicity, and outstanding antibacterial performance with MCSNs containing Ag (Ag-MCSNs) showing higher antibacterial effect. This substance may be improved to provide a better root canal filler material, sealer, or novel intracanal medicament in dentistry.

Heavy‐Mineral Grain Counting: Counting Techniques, Error Estimation, and the Number of Grains to be Counted

AbstractHeavy‐mineral assemblages of sediments and sedimentary rocks record information regarding provenance, including the source rocks involved, tectonic setting, climatic conditions, and modifications from source to sink. Drawing conclusions on provenance and provenance changes requires robust quantification of individual heavy‐mineral species contents, including error estimates. Nevertheless, it is common practice to count sub‐quantities of grains from aliquots and not considering the bias introduced by (a) counting similar numbers of grains from aliquots containing different total numbers of grains, and (b) using variable counting methods. Consequently, reported heavy‐mineral contents estimated from counting sub‐quantities are affected by errors of unknown extent, making it infeasible to determine whether intra‐ or intersample variations are statistically significant. Based on 65 heavy‐mineral aliquots of variable grain size, mineral species contents, total number of grains, and known composition determined by counting all grains (n = 80,393), here &gt;31 million countings of heavy‐mineral sub‐quantities are simulated using (a) ribbon counting with varying ribbon size, ribbon position, ribbon orientation, total number of counts, and ways of aggregating counts from multiple ribbons, and (b) a newly proposed counting technique called cluster counting. I show that (a) error estimation for a specific aliquot requires a finite population correction; (b) compared to adjacent ribbons, aggregating counts of spatially distant ribbons reduces the error; (c) cluster counting further reduces the error, showing the best fit with theory; and (d) the Wilson score interval enables error calculation as well as the number of grains to be counted to achieve an operator‐specific aim.

Sample size determination for interval estimation of the prevalence of a sensitive attribute under non-randomized response models.

A sufficient number of participants should be included to adequately address the research interest in the surveys with sensitive questions. In this paper, sample size formulas/iterative algorithms are developed from the perspective of controlling the confidence interval width of the prevalence of a sensitive attribute under four non-randomized response models: the crosswise model, parallel model, Poisson item count technique model and negative binomial item count technique model. In contrast to the conventional approach for sample size determination, our sample size formulas/algorithms explicitly incorporate an assurance probability of controlling the width of a confidence interval within the pre-specified range. The performance of the proposed methods is evaluated with respect to the empirical coverage probability, empirical assurance probability and confidence width. Simulation results show that all formulas/algorithms are effective and hence are recommended for practical applications. A real example is used to illustrate the proposed methods.

Remote Work Integrated Learning (RWIL) Field Placement in Retail Management

Integrative projects have gained recognition in higher education institutions and the business community by providing valuable experience to students through immersive practice, bridging the gap between education and the business profession. This study provides a detailed analysis of students’ experiences in Remote Work Integrated Learning (RWIL) - field placement within the business area of retail management. Given that the study occurs during the COVID-19 pandemic, how remote working supports or hinders the WIL experience is investigated. The findings are extended to propose a framework for the practical implementation of RWIL design. This study offers new perspectives for higher-education professionals, specificity in retail management, and novelty of the Linguistic Inquiry and Word Count technique for sentiment analysis.

Performance of three techniques for diagnosing equine tapeworm infection

Tapeworm infection in horses can cause serious health concerns, and recent data have documented treatment failures in the most common species, Anoplocephala perfoliata. The threat of anthelmintic resistance in A. perfoliata is of particular concern because of poor diagnostic performance of standard egg counting techniques for detecting this parasite. This study compared the performance of three diagnostic techniques 1) Mini-FLOTAC, 2) Cornell-Wisconsin, and 3) Proudman and Edwards used to detect and quantify A. perfoliata eggs in naturally infected horses. Eighteen adult female horses from the University of Kentucky’s historic parasitology herd were included in this study. Fecal samples were collected from all horses at five collection time points two weeks apart and analyzed with the three techniques. A total of 90 samples were collected and 270 counts determined in the study. The proportions of positive samples determined by the three techniques were significantly different from each other (p<0.05): Mini-FLOTAC (16%), Cornell-Wisconsin (47%), and Proudman and Edwards (70%). The Proudman and Edwards technique counted consistently higher numbers of tapeworm eggs compared to the other two techniques throughout the study [p < 0.05]. Total raw counts of tapeworm eggs across the study for each technique were 16, 88, and 410 for the Mini-FLOTAC, Cornell-Wisconsin, and Proudman and Edwards, respectively. This study demonstrated that the Proudman and Edwards technique was superior in diagnosing A. perfoliata infection. Future work needs to assess this technique’s potential for Fecal Egg Count Reduction Testing (FECRT).

Exonuclease-III Assisted the Target Recycling Coupling with Hybridization Chain Reaction for Sensitive mecAGene Analysis by Using PGM.

In the field of neonatal infections nursing, methicillin-resistant Staphylococcus aureus (MRSA) is a major bacterial pathogen. Here, we present a portable biosensor for MRSA detection that is both highly sensitive and portable, owing to its implementation on the personal glucose meter (PGM) platform. The H probe was fixed on the magnetic bead for mecA gene analysis. A blunt 3' terminus appeared in the MBs-H probe when the mecA gene was present. Exonuclease-III (Exo-III) recognized the blunt terminus and cleaved it, freeing the mecA gene and so facilitating target recycling. In the meantime, the remaining H probe-initiated hybridization chain reaction (HCR) led to the desired signal amplification. Portable quantitative detection of mecA gene is possible because PGM can read the quantity of invertase tagged on HCR product. After optimizing several experimental parameters, such as the concentration of Exo-III and incubation time, the constructed sensor is extremely sensitive, with a detection limit of 2 CFU/mL. The results from this sensitive PGM-based sensor are in agreement with those obtained from plate counting methods, suggesting that it can be used to accurately assess the MRSA content in artificial clinical samples. In addition, the PGM sensor can significantly cut down on time spent compared to plate counting techniques. The manufactured sensor provides a promising option for accurate identification of pathogenic bacteria.