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275 protocols using originpro 2018

1

Detailed Photovoltaic Characterization Protocol

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All experiments were conducted for more than three times to confirm the reproducibility of the results. A fill‐area‐under‐curve processing was performed for the EDS data in Figure 2b using a software OriginPro 2018. The transient photovoltage results (Figure 4f and Figure S13, Supporting Information) were normalized to the maximum photovoltage. A 30 point adjacent average smooth was processed as red curve in Figure 5g, where the directly measured raw data (black curve) were also showed. The adjacent average smooth was conducted by a software OriginPro 2018. All the rest of results were shown as directly measured without preprocessing. The statistical data shown in Figure 1k were performed by a software NanoScope Analysis. Five separate devices were measured to show the statistical data in Figure S5b in the Supporting Information, and the statistical analysis was conducted by a software OriginPro 2018.
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2

Optimization of CQ-Y1 Growth and Fe(III) Reduction

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All bacterial culture and biochemical assays were performed with at least three independent repeats for each experiment. Data were presented as means ± standard deviations. The SPSS19.0 software (SPSS Inc., Chicago, IL, United States) was used for all data analysis and OriginPro 2018 software (OriginLab, Northampton, MA, United States) were used to draw all figures. The preference of the cell growth and Fe(III) reduction of CQ-Y1 adapted to high NaCl or high temperature was assessed by the regression using OriginPro 2018 software.
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3

Correlating Anti-Melanin and Anti-Oxidation Properties

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All results were expressed as mean ± standard deviation. SPSS version 20 (SPSS Inc., Chicago, IL, USA) was used for analysis of variance (p < 0.05). The Duncan multi-range test was used for the comparison of means. Three replicates were used for each analysis. Principal component analysis (PCA) was used to analyze the correlation between the different properties of anti-melanin and anti-oxidation. The above indicators were used as active variables, and the concentration of FTGML was used as the observed value. Two-dimensional or three-dimensional graphs were drawn using Origin Pro 2018 software. Hierarchical cluster analysis (HCA) was used to visualize and emphasize the similarities between individuals. The difference is usually expressed by the distance between individuals [19 (link)]. Origin Pro 2018 software was used to determine the correlation between indicators by the Pearson correlation coefficient in binary linear correlation.
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4

Quantitative Fluorescence Analysis of Nanomaterials

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Example 3

To each of 36 wells of a Bio Tek 96 well plate was added a circular 6 mm piece of Whatman #1. A solution of 8.0 mg N-(1-naphthyl)ethylenediamine-HCl in 1.0 mL ultrapure water was created, then diluted by serial dilution to concentrations of 4.0, 2.0, 1.0, 0.50, 0.25, 0.125, 0.0625, 0.0313, 0.0156, 0.0078, 0.0039 mg/mL. To the first three wells was added 5 μL of the 8.0 mg/mL solution, to the second three wells was added 5 μL of the 4.0 mg/mL solution, etc., until all wells were filled. The solutions were allowed to dry for 2 hours in the dark, then the fluorescence of each well was analyzed using the Bio Tek. The fluorescence integration of each spectrum (fluorescence intensity by wavenumber) was obtained using OriginPro2018, and average and standard deviation values were obtained. OriginPro2018 non-linear curve fitting was applied to the data and a logistic curve fitting was obtained. Values for degree of functionalization were obtained using Excel Solver and the obtained equation.

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5

Statistical Analysis of Diffusion Dynamics

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Statistical analysis was performed by 2-sided t test on Microsoft Excel. P < 0.01 was considered to be statistically significant. Linear regression analysis and dose–response curve fitting were performed using OriginPro 2018. The theoretical curve for fast component of diffusion was drawn by parameters for actual measurement except for fractional percentage of the second component (fraction 2 set to 0) on OriginPro 2018.
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6

Spectroscopic Analysis of Experimental Data

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All experiments were repeated at least three times. Quantitative data were expressed as mean ± standard error (SD). NMR spectra were analyzed using Mestre Nova LITE v14.0.0.0–23239 software (Mestre lab Research S.L.). Statistical calculations were performed using OriginPro 2018 (64 bit) SR1 b9.5.1.195. Data analysis of absorption spectra and fluorescence spectra was performed using OriginPro 2018 (64 bit) SR1 b9.5.1.195.
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7

Fluorescence Decay Curve Analysis

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Graphs were plotted and analyzed using OriginPro 2018 software. To test statistical differences between the Ci replete, depleted and recovery, paired-sample t-test was applied using the OriginPro 2018 software. The flash-induced fluorescence decay curves and the OJIP transients were double normalized; minimal fluorescence F0 was set to 0 and maximal fluorescence was set to 1.
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8

Lettuce Leaves Pigment Analysis

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The mean and standard deviation (SD) of weight and water activity for 5 lettuce heads were calculated and graphically presented as a function of storage time using Origin Pro 2018 software (OriginLab Corp. Northampton, MA, USA).
The spectra of lettuce leaves acquired on the first and last day of storage were trimmed to only the visible region of 400–700 nm, and raw and standard normal variate (SNV) [34 (link)] transformed spectra were inspected for the absorbance bands attributable to pigments. The values of absorbance at the identified absorbance bands were compared using the paired samples t-test to evaluate the differences in pigments between the first and the last day of storage of lettuce leaves. The pre-processing of spectra was performed using commercially available software Pirouette v4.5 (Infometrix Inc, MA, USA), while visualization and statistical analysis were performed using Origin Pro 2018 software (OriginLab Corp. Northampton, MA, USA).
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9

Wastewater Treatment Efficiency Evaluation

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Removals of DOC, turbidity, UV254, total coliforms, E. coli and antibiotics were calculated based on influent and effluent concentrations. Mean and standard deviation were calculated in Microsoft Excel 2016. One-way analysis of variation (ANOVA) and Pearson correlation analysis were performed using OriginPro 2018. All figures were generated by OriginPro 2018.
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10

Quantifying Antibiotic Resistance Genes and Microbial Communities

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The absolute abundance or concentration of ARGs indicated the ARG copy numbers per gram in medium samples (copies/g) or per litre in influent/effluent samples (copies/L). The relative abundance of ARG was calculated based on the ARG copies normalised to the number of copies of the 16S rRNA gene. The number of different ARGs detected was expressed as the richness of ARGs. Mean and standard deviation calculations were performed with Microsoft Excel 2016. One-way analysis of variation (ANOVA), Pearson correlation analysis and ARGs' profile heatmap were performed using OriginPro 2018.
Principal coordinate analysis (PCoA) based on Bray-Curtis distance was utilised to evaluate the bacterial community profiles between different biofilm samples. Redundancy analysis (RDA) was performed to analyse the correlation between ARGs and bacterial communities (considered as the environmental factor). Variation partitioning analysis (VPA) was performed to explore the contributions of integrons and bacterial communities to the variations of ARGs.
PCoA, RDA and VPA were performed using Canoco 5.0 software (USA). Venn diagram analysis was performed to assess the numbers of shared and unique OTUs in each biofilm 193 sample. OriginPro 2018 was used to draw histogram, line graphs and Venn diagram. 194
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