3σ Rule Research Articles

Method on condition assessment of pitch system based on fuzzy matter-element analysis

In order to improve the real-time reliability of wind turbine and solve the effect of artificial factors, fuzzy matter-element analysis is proposed. The pitch system, which has high failure rate, is researched in this paper. The condition assessment model of pitch system is built in two steps: (1) To avoid the subjective judgment of the parameter distribution, this thesis uses 3σ rule and quartile analysis method to get the boundary data sets. The ANFIS algorithm is used to train the data to reduce the extreme value, and results of multi-feature fault detection are obtained. (2) Results from fault detection are applied in condition assessment model based on fuzzy matter-element analysis to realize the unification of fuzzy value of detection result and grade assessment. The method is applied to test the actual operation state of wind turbine. The results show that it can obviously reflect the pitch system and has better assessment effects.

Boron- and Phenyl-Doped Graphitic Carbon Nitride (g-C₃N₄) Nanosheets for Colorimetric Detection of Hydrogen Peroxide in Soaked Foods.

Boron- and phenyl-doped graphitic carbon nitride nanosheets (BPCN NSs) were prepared by thermal polymerization of cyanamide with 3-aminobenzeneboronic acid followed by ultrasonic exfoliation. BPCN NSs exhibited enhanced peroxidase-like activity and catalyzed the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB), 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) and o-phenylenediamine by H₂O₂. A simple sensitive colorimetric senor was developed for H₂O₂ by utilizing TMB as the substrate and BPCN NSs as enzyme mimetic. The linear relations between the absorbance and H₂O₂ concentration over the range from 0 to 280 μmol L-1 and from 280 to 1000 μmol L-1 were obtained with the limit of detection of 1.0 μmol L-1 according to the 3σ rule. The colorimetric sensor was applied for the detection of H₂O₂ residue in simulated soaked foods with satisfied results. Finally, the portable test kits for H₂O₂ were prepared and applied for the semi-quantitative assay of H₂O₂ residues in soaked chicken feet.

Colorimetric sensor based on 4-mercaptophenylboronic modified gold nanoparticles for rapid and selective detection of fluoride anion.

A highly selective and sensitive colorimetric sensor based on aggregation-induced color change of 4-mercaptophenylboronic modified gold nanoparticles was designed for the determination of fluoride anion. The 4-mercaptophenylboronic modified gold nanoparticles were synthesized by a simple one-pot reaction. The aggregation process occurred when interaction between fluoride anion and 4-mercaptophenylboronic on the surface of gold nanoparticles took place; as a result, fluoroborate anions were formed coupled with changes in the electronic properties of the AuNPs. The change can be measured by UV-Vis absorption spectra. The sensor shows good selectivity and sensitivity for fluoride anion. The linear range is 10.0-30.0 μM for fluoride and the detection limit of fluoride is 3.45 × 10-7 M according to IUPAC criteria (3σ rule). Furthermore, the sensor has been used for the detection of fluoride anion in tap water, ground water and human serum samples, the recovery can achieve 94.0%-103.3%, 94.7%-101.0% and 89.8-100.9%, respectively. The excellent performance of colorimetric sensor in the detection of the fluoride anion demonstrated the potential application in the detecting fluoride anion present in the complex environmental and biological samples.

Target-triggered in situ autocatalysis in nanopore membrane for point-of-care testing of sub-nanomolar Ag+

This work initially describes a sample-in-answer-out paper-based assay for simple, rapid, sensitive, specific, and low-cost detection of silver (I) (Ag+) ions. It combines Ag+-triggered in situ autocatalysis for signal amplification with an instrument-free, timing readout in 3D origami paper-based analytical devices integrated with nanopore membranes (NMs). The autocatalytic amplification is based on the oxidability of Ag+ towards 3,3',5,5'-tetramethylbenzidine (TMB) loaded in the NMs. The Ag+ ions are rapidly reduced by the TMB to form silver nanoparticles that further act as nanocatalysts to catalyse the oxidation of more TMB molecules to their derivatives by Ag+ ions for producing bigger (and more) metal particles. The NM’s pores are thus partially blocked by these metal particles to adjust (prolong) the flowing time of a coloured reagent in the paper device. Under optimized conditions, this developed point-of-need method could quantitatively detect the Ag+ ions in a linear concentration range of 1.9–62.5 nM within 4 min, by simply using a ubiquitous phone (or a timer). Its detection limit was estimated to be ˜0.91 nM according to the 3σ rule. The recoveries of analyzing real water examples (i.e., pond water, tap water, drinking water, and soil water) were from ˜95.2 to ˜103.9%, and the corresponding relative standard deviations ranged from 3.3 to 8.1% (n = 6).

Aptamer lateral flow assays for rapid and sensitive detection of cholera toxin.

Aptamers are envisioned to serve as powerful synthetic substitutes to antibodies in a variety of bioanalytical assay formats. However, lateral flow assays (LFAs) remain dominated by antibody-based strategies. In this study, a LFA for the detection of cholera toxin as a model analyte is developed and optimized using a synthetic aptamer and a naturally occurring receptor as biorecognition elements and directly compared with solely aptamer and aptamer and antibody-based alternative approaches. The aptamer (CT916) recently selected by our group, GM1 receptors and an anti-cholera toxin antibody were evaluated. Relying solely on molecules that can easily be synthesized while aiming for high sensitivity, we applied a novel combination of capture aptamer and GM1 cell receptor-labeled liposomes for cholera toxin detection, achieving a limit of detection (LOD) of 2 ng ml-1 (3σ)/10 ng ml-1 (visual) in ∼15 min. To put our novel aptasensor into perspective, we developed a competitive lateral flow assay, exploiting the competition of cholera toxin in solution with immobilized cholera toxin for binding of aptamer-coated gold nanoparticles (AuNPs) (LOD = 51 ng ml-1 (3σ)/100 ng ml-1 (visual), assay time ∼10 min). As dual simultaneously binding aptamers were not available, we designed aptamer antibody pair-based lateral flow assays using aptamer-coated AuNPs which yielded a LOD of 5 ng ml-1 (by the 3σ rule)/10 ng ml-1 (visual) in a 10 min assay and an even better LOD of 0.6 ng ml-1 (3σ)/1 ng ml-1 (visual), with an ∼20 min total assay time. All set-ups are highly specific and provide an excellent alternative for cholera toxin detection in places where professional knowledge and sophisticated equipment are not readily available and cost efficient, simple, and rapid tests are needed, while the combination of GM1 cell receptor-labeled liposomes and aptamers is clearly the most promising.

Electrochemical determination of hydrogen peroxide on a gold nanoparticle–nitrogen-doped graphene glassy carbon electrode

ABSTRACTA novel nonenzymatic sensor based on gold nanoparticle–nitrogen-doped graphene was synthesized by electrochemical sequential deposition on the surface of a glassy carbon electrode. Nitrogen-doped graphene was synthesized by a hydrothermal method using graphene oxide and carbamide as the raw materials mixed in specific proportions. The gold nanoparticles were used in the electrochemical sensor to provide unique electronic and electrochemical properties. Under the optimized conditions, hydrogen peroxide was determined by differential pulse voltammetry with a linear relationship for concentrations from 1.0 × 10−7 to 1.0 × 10−5 mol L−1. The detection limit was 4.9 × 10−8 mol · L−1 (according to the 3σ rule) and the recoveries were 95.0–98.0%. This sensor is simple, reproducible, and demonstrates that nitrogen-doped graphene oxide has potential applications for electrochemical sensors.

The price momentum of stock in distribution

In this paper, a new momentum of stock in distribution is proposed and applied in real investment. Firstly, assuming that a stock behaves as a multi-particle system, its share-exchange distribution and cost distribution are introduced. Secondly, an estimation of the share-exchange distribution is given with daily transaction data by 3σ rule from the normal distribution. Meanwhile, an iterative method is given to estimate the cost distribution. Based on the cost distribution, a new momentum is proposed for stock system. Thirdly, an empirical test is given to compare the new momentum with others by contrarian strategy. The result shows that the new one outperforms others in many places. Furthermore, entropy of stock is introduced according to its cost distribution.

A graphene-based biosensor for detecting microRNA with augmented sensitivity through helicase-assisted signal amplification of hybridization chain reaction

Most nucleic acid biosensors are based on hybridization binding models. During reactions, target molecules are hybridized with probes, inducing intensive signal changes. The molecular mechanism of nucleic acid related enzymes for new hybridization reaction systems based on graphene oxide (GO) has far-reaching significance, especially of helicases. This paper proposes a helicase-assisted GO-based reaction platform for microRNA (miRNA) detection. In this work, the detection platform was found capable for shortening the detection duration, dramatically from 4h to 50min, and its limit of detection for miRNA was calculated to be 4.2 fM as per 3σ rule. The sensitivity of the helicase-assisted HCR/GO sensing platform was 2 orders of magnitude higher than common HCR/GO sensing platform without enzymes. Meanwhile, the extensive applicability of helicases to hairpin probes makes the enzyme-associated platform in vast use to improve the detection efficacy of other nucleic acid molecules.

A likelihood-based spatial statistical transformation model (LBSSTM) of regional economic development using DMSP/OLS time-series nighttime light imagery

In a regional economy, the central city of a metropolitan area has a radiative effect and an accumulative effect on its surrounding cities. Considering the limitations of traditional data sources (e.g., its subjectivity) and the advantages of nighttime light data, including its objectivity, availability and cyclicity, this paper proposes a likelihood spatial statistical transformation model (LBSSTM) to invert for the gross domestic product (GDP) of the surrounding cities, using time series of Sum of Lights (SOL) data covering the central city and taking advantage of the economic and spatial association between the central city and the surrounding cities within a metropolitan area and the correlation between SOL and GDP. The Wuhan Metropolitan Area is chosen to verify the model using time series analysis and exploratory spatial data analysis (ESDA). The experimental results show the feasibility of the proposed LBSSTM. The prediction accuracy of our model is verified by cross-validation using data from 1998, 2004 and 2011, based on the 3σ rule. This model can quantitatively express the agglomeration and diffusion effect of the central city and reveal the spatial pattern of this effect. The results of this work are potentially useful in making spatio-temporal economic projections and filling in missing data from some regions, as well as gaining a deeper quantitative and spatio-temporal understanding of the laws underlying regional economic development.

Identifying outliers of non-Gaussian groundwater state data based on ensemble estimation for long-term trends

A hydrogeological dataset often includes substantial deviations that need to be inspected. In the present study, three outlier identification methods – the three sigma rule (3σ), inter quantile range (IQR), and median absolute deviation (MAD) – that take advantage of the ensemble regression method are proposed by considering non-Gaussian characteristics of groundwater data. For validation purposes, the performance of the methods is compared using simulated and actual groundwater data with a few hypothetical conditions. In the validations using simulated data, all of the proposed methods reasonably identify outliers at a 5% outlier level; whereas, only the IQR method performs well for identifying outliers at a 30% outlier level. When applying the methods to real groundwater data, the outlier identification performance of the IQR method is found to be superior to the other two methods. However, the IQR method shows limitation by identifying excessive false outliers, which may be overcome by its joint application with other methods (for example, the 3σ rule and MAD methods). The proposed methods can be also applied as potential tools for the detection of future anomalies by model training based on currently available data.

Cost-sensitive feature selection based on adaptive neighborhood granularity with multi-level confidence

Neighborhood rough set model is considered as one of the effective granular computing models in dealing with numerical data. This model is now widely discussed in feature selection and rule learning. However, there is no theoretical analysis on the issue of neighborhood granularity selection, the influence of sampling resolution, test and misclassification costs on modeling. In this paper, we design an adaptive neighborhood rough set model according to data precision and develop a fast backtracking algorithm for neighborhood rough sets based cost-sensitive feature selection by considering the trade-off between test costs and misclassification costs. In the proposed model, the neighborhood granularity, based on the 3σ rule of statistics, is adaptive to data precision that is described by the multi-level confidence of the feature subsets. Our experiments, thoroughly performed on 12 datasets, demonstrate the effectiveness of the model and the efficiency of the backtracking algorithm.

An ultrasensitive scanning electrochemical microscopy (SECM)-based DNA biosensing platform amplified with the long self-assembled DNA concatemers

The long DNA concatemers have been well developed to fabricate various biosensing platforms for the signal amplification. Herein, this signal amplification strategy was firstly used for an ultrasensitive scanning electrochemical microscopy (SECM)-based DNA biosensing platform. This platform was constructed through the hybridization of target DNA (TD) with thiol-tethered DNA capture probes (CP), immobilized on the gold substrate surface, and biotinylated DNA signal probes (SP), which formed then the long DNA concatemers through the continuous self-assembly with alternating DNA auxiliary probes (AP). The streptavidin-horseradish peroxidase (HRP) was linked to the long DNA concatemers through biotin-streptavidin interaction. In the HRP-catalyzed reaction, hydroquinone (H2Q) was oxidized to benzoquinone (BQ) with H2O2 at the modified substrate surface where sequence-specific hybridization had occurred, and the BQ generated could be monitored by a SECM tip. This platform exhibited a low detection limit of 0.18 aM estimated by the 3σ rule. Combined with DNA microarrays, four kinds of TDs (100 fM) as the models were detected simultaneously by using this proposed strategy, which also demonstrated sufficient selectivity to distinguish specific DNA sequences and good reproducibility. This method opens a promising direction to improve the SECM sensitivity for high-throughput DNA detection.

Constructing general cube to be aware of network security situation

Concerning the problems of limited current network security situation assessment scope,single information source,higher time and space complexity and larger deviation of the accuracy,a method was put forward to construct general cube,which can be aware of the network security situation. The continuous situation factor data monitored can be pretreated by discretizing by "3σ rule"and aggregated in the general built cube,that fused into component security situation vertically and merged into the network security situation from component security situation using statistical methods horizontally. It can provide reliable reference to enhance network security. Finally,making full use of network data,the network security situation awareness model and algorithm proposed are verified and the experimental results show correctness of this method.

Spatial Outlier Detection of CO2 Monitoring Data Based on Spatial Local Outlier Factor

Spatial local outlier factor (SLOF) algorithm was adopted in this study for spatial outlier detection because of the limitations of the traditional static threshold detection. Based on the spatial characteristics of CO 2 monitoring data obtained in the carbon capture and storage (CCS) project, the K-Nearest Neighbour (KNN) graph was constructed using the latitude and longitude information of the monitoring points to identify the spatial neighbourhood of the monitoring points. Then SLOF was adopted to calculate the outlier degrees of the monitoring points and the 3σ rule was employed to identify the spatial outlier. Finally, the selection of K value was analysed and the optimal one was selected. The results show that, compared with the static threshold method, the proposed algorithm has a higher detection precision. It can overcome the shortcomings of the static threshold method and improve the accuracy and diversity of local outlier detection, which provides a reliable reference for the safety assessment and warning of CCS monitoring.

Preparation and properties of bisphenol A sensor based on multiwalled carbon nanotubes/Li4Ti5O12-modified electrode

A new electrochemical sensor based on the multiwalled carbon nanotube (MWCNT)/Li4Ti5O12-modified glassy carbon electrode for determination of bisphenol A (BPA) was developed by modifying the surface of a glassy carbon electrode with the prepared composite Li4Ti5O12/MWCNTs. The morphology and structure of the composite were characterized by infrared spectroscopy and scanning electron microscope. The obtained electrochemical sensor Li4Ti5O12/MWCNTs/GCE takes advantages of large specific surface area of the Li4Ti5O12 nanostructure, excellent adsorption properties, and electrochemical properties of MWCNTs. Under optimal conditions, the response of the proposed sensor to BPA was linear in the BPA concentration range from 1.0 × 10−7 to 1.0 × 10−5 mol L−1 and the detection limit was of 7.8 × 10−8 mol L−1 according to the 3σ rule. The results revealed that the newly developed sensor exhibited high sensitivity and selectivity, excellent electrochemical performance, and fast response to BPA, allowing it to be used for the detection of BPA in actual samples.

A sensitive electrochemical molecularly imprinted sensor based on catalytic amplification by silver nanoparticles for 3-indoleacetic acid determination

A novel strategy for improving the sensitivity of a molecularly imprinted sensor was proposed based on the amplification effect derived from the electrochemical stripping of copper produced by catalytic deposition by silver nanoparticles (AgNPs). Polypyrrole was electrochemically polymerized to prepare a molecularly imprinted polymer film using 3-indoleacetic acid (IAA) as a template. After the competitive reaction between IAA and thiolation-3-indoleacetic acid (IAA-S), IAA-S was labeled with AgNPs, and then copper was catalytically reduced and deposited onto the AgNP surface. The deposited copper was electrochemically dissolved, and the anodic stripping current was recorded using linear sweep voltammetry. The change in signal decreased when IAA-S was replaced by IAA in the samples. The peak current was proportional to the logarithm of the concentration of IAA in the range of 9×10−10–6×10−7mol/L, with a detection limit of 2.31×10−10mol/L determined by the 3σ rule. Samples were assayed, and the recoveries of the approach ranged within 99.7–104.2%.

A HYDROGEN PEROXIDE SENSOR BASED ON PRUSSIAN BLUE AND DNA-MODIFIED ELECTRODE

The polyvinylpyrrolidone (PVP) protected Prussian blue (PB) nanoparticles were prepared for use as a sensor for the catalytic reduction of hydrogen peroxide. The nanoparticles were used to modify a gold electrode, which was applied to detect hydrogen peroxide. Impedance spectra and differential pulse voltammetry were applied to detect the performance of the novel electrode and its response to H2O2 and Ramos cell smash fluid. Under the optimized experimental conditions, hydrogen peroxide was detected in a linear range of 6.25 × 10−7 to 1.0 × 10−5 mol · L−1, and the detection limit was 7.12 × 10−8 mol · L−1 according to 3σ rule. Under the same conditions, hydrogen peroxide was determined in Ramos cell smash fluid with a linear range from 400–80000 mol mL−1, with a detection limit of 114 mL−1 according to 3σ rule. The modified electrode with Prussian blue nanoparticles displayed high sensitivity, good reproducibility, and long-term stability to hydrogen peroxide.

Measurement of the spatial resolution and the relative density resolution in an industrial cone-beam micro computed tomography system

The spatial resolution and the relative density resolution are the two most critical indicators in CT system. The method recommended in the ASTM E1695-95 and GJB 5311-2004 is only suitable to the fan-beam CT system. In this paper, for industrial cone-beam micro CT system, we will adopt the edge response function (ERF) created by the step edges of a steel ball to measure the system 3D PSF and MTF. To describe the contrast discrimination function more accurately, we will first propose to extend the two-dimensional measurement region to the three-dimensional space. Our experimental spatial resolution is (55.56±0.56) lp/mm and the relative density resolution is 1% within 300 μm×300 μm×300 μm according to the 3σ rule.

Triphenylamine-based conjugated polymer/I− complex as turn-on optical probe for mercury(II) ion

A kind of triphenylamine-based conjugated polymer with simple structure, poly(9,9-dioctyl)-2,7-fluorene-co-N-4-phenylethenyl-4,4′-triphenylamine (PFT-PE), was successfully synthesized via Suzuki coupling reaction. Chemical structure of PFT-PE was verified by NMR and FT-IR analyses. PFT-PE possesses high fluorescence quantum efficiency in THF solution (~0.90), and its fluorescence was efficiently quenched by the introduction of I−, accompanied by the change of its apparent color from colorless to light yellow. Specificity for the detection of I− of PFT-PE was verified by anti-interference experiments toward other common anionic ions, and the detection limit reaches ~2.9×10−7M (according to 3σ rule). Interestingly, thanks to the high association constant and matching ratio between I− and Hg2+, fluorescence of PFT-PE/I− complex recovered quickly with the presence of Hg2+. Most of background cationic ions brought slight interference to the detection of Hg2+ except for Ag+ and Cu2+, and their interference can be excluded readily by additional UV–vis analysis. Detection limit of ~2.4×10−7M for Hg2+ can be obtained by PFT-PE/I−, suggests that PFT-PE can act as dual-channel, high selective, immediacy and sensitive optical probe for I− and Hg2+.

Highly sensitive grating coupler-based surface plasmon-coupled emission (SPCE) biosensor for immunoassay

We have evaluated the performance of a novel high-content gold grating coupler-based surface plasmon-coupled emission (SPCE) biosensor system. The polyelectrolyte (PEL) layer on the system's biosensor chip surface was formed on the gold surface using a layer-by-layer (LbL) deposition technique to spatially separate fluorophores from the gold surface and as a linker layer for protein immobilization. The characteristics of the PEL spacer layers were determined by surface plasmon resonance (SPR) analysis and by ellipsometry. The SPCE response decreased as the spacer layer thickness increased above a dominant quenching range (10 nm). Two PEL layers of poly(diallyldimethylammonium chloride) and poly(acrylic acid) were found to be an effective spacer that minimized the quenching effect while maximizing SPCE responses for both direct and sandwich immunoassay formats. A mouse IgG sandwich immunoassay using this optimized spacer layer configuration showed a dose-dependent response with a 1 pg ml(-1) limit of detection by the 3σ rule. A nine log dynamic range of human IgG concentrations in unfractionated human serum could be analyzed using this approach. These results show the potential of the grating coupler-based SPCE biosensor as a sensitive platform for high-content analysis.