Experimental Sample Set Research Articles

MCNP simulation and experimental study in situ low-grade copper analysis based on PGNAA

A prompt gamma neutron activation analysis (PGNAA) facility utilizing 252Cf source has been developed for in situ analysis of copper samples. Monte Carlo simulation is employed to determine optimal sizes for neutron moderator, gamma-ray shielding material, and thermal neutron absorber. Subsequently, based on the parameters optimized by MCNP, the PGNAA facility was constructed. Five sets of experimental samples containing low-grade copper concentration of 0 %, 0.5 %, 1 %, 1.5 % and 2 % are measured with the PGNAA facility. The results show that the minimum detectable concentration of copper is 0.218 %. The maximum relative deviation of copper is 8.53 %.

Effect of Blending of Shellac, Carbonyl Iron Powder, and Carbonyl Iron Powder/Carbon Nanotube Microcapsules on the Properties of Coatings

Nine sets of orthogonal experimental samples were prepared by examining four factors: shellac microcapsules, carbonyl iron powder (CIP) microcapsules, CIP/ carbon nanotube (CNT) microcapsules, and primer coating thickness. By testing the morphology and performance of the coating and using the fracture elongation of the coating as an orthogonal experimental analysis, the maximum factor affecting the fracture elongation of shellac, CIP, and CIP/CNT microcapsule coatings was determined. The first two factors that had a significant impact on the fracture elongation of the coating were the content of CIP/CNT microcapsules and shellac microcapsules. In order to further optimize the coating performance, important factor experiments were conducted, using the content of CIP/CNT microcapsules and shellac microcapsules as variables. It was found that the coating had the best performance when the content of CIP/CNT microcapsules was 7.0% and the content of shellac microcapsules was 4.0%. The optical properties of coatings with added shellac, CIP, and CIP/CNT microcapsules were tested, and the color difference and glossiness of the coatings showed little change. The mechanical properties of coatings with added shellac, CIP, and CIP/CNT microcapsules were tested. The blending of the three types of microcapsules enhanced the toughness of the coating to a certain extent, and suppressed the generation of micro-cracks, demonstrating a good self-healing effect. The electromagnetic-absorption performance of coatings with added shellac, CIP, and CIP/CNT microcapsules was tested. The blending of shellac, CIP, and CIP/CNT microcapsules exhibited two effective bands of electromagnetic absorption and a good absorption performance at a relatively wide frequency range. The combination of shellac, CIP, and CIP/CNT microcapsules endows the fiberboard surface with self-healing and electromagnetic-absorption functions, while maintaining the original performance of the water-based coating. The results can be used for application of surface coatings on wooden materials with dual functions of self-healing and electromagnetic absorption.

Real-time hybrid simulation incorporating machine learning for deep-water bridges subjected to seismic ground motion with fluid-structure dynamic interaction

The investigation of fluid-structure dynamic interaction (FSI) of deep-water structures subjected to seismic events with underwater shaking table testing method has been restricted by similarity problems and limited experimental capabilities. To address this issue, the authors previously proposed a real-time hybrid simulation (RTHS) method for FSI under seismic loading. In this study, the proposed method is applied to a deep-water bridge to demonstrate the low-cost and high-efficiency features of the proposed method. A total of 100 sets of experimental samples were analyzed, providing details and statistical information of the structural responses with FSI effects during seismic events. In the proposed RTHS application, a machine learning surrogate model was established for real-time calculation of the complex numerical substructure, and data exchange for complex physical-numerical boundaries. Additionally, a solution for RTHS when complex physical substructure boundary conditions can only be partially satisfied has been proposed, further contributing to the versatility of the study. Through the utilization of such advanced computational methods, the authors were able to explore the intricate coupled effect between fluid and structure in a deep-water environment. Such efforts hold the promise of enhancing our understanding of this complex phenomenon and may ultimately inform the design and construction of more resilient structures in the future.

Methodology for Evaluating Controlled Moisture Distribution in Woven Cotton Fabric Surfaces

ABSTRACT The proposed study aims to discuss the methodology for measuring and evaluating controlled moisture distribution in woven fabric surfaces in the first part and the construction of woven fabric using hydrophobic and hydrophilic cotton yarns in the second part. Moisture distribution can be controlled in terms of the anisotropic (horizontal and vertical) and isotropic characteristics of the wetting of the cotton woven fabrics based on the combination of hydrophobic and hydrophilic threads. A set of experimental samples using hydrophobic and hydrophilic threads in warp and weft was produced to monitor the moisture (water) distribution in woven fabric surfaces. For evaluating the controlled distribution of moisture (water) in these atypical woven fabric constructions, an algorithm (methodology) was proposed, where the object (liquid) was separated from the background (fabrics) and various objects and geometric characteristics depending on time were evaluated on the object. The algorithm itself consisted of several steps and was executed in a loop for the current frame at a given time.

Liquid chromatography coupled with tandem mass spectrometry for simultaneous quantification of valproate, valproate-glucuronide and lamotrigine in various biological matrices of rat.

Valproate and lamotrigine are commonly used as antiepileptic drugs even in pregnant and breastfeeding women. The extent and effects of drug exposure on the developing brain of the offspring are not well understood. Animal models can be utilised to investigate the transfer of substances into fetal brain with the ultimate aim of providing insights to aid clinical decisions. In the present study, an LC-MS/MS method was developed and validated for quantification of valproate (VPA), valproate-glucuronide (VPA-Gluc, a major metabolite of valproate) and lamotrigine (LTG) in rat blood plasma, cerebrospinal fluid and brain tissue. A 10 μl sample was spiked with stable isotope-labelled internal standards and extracted by methanol. An Agilent RRHD Eclipse Plus C18 column (2.1 × 100 mm, 1.8 μm) was used. The MS/MS transitions were 143.1016-143.1016 (VPA), 319.1392-143.0978 (VPA-Gluc) and 256.0157-210.9826 (LTG). The linear ranges of VPA, VPA-Gluc and LTG were 30-250, 10-140 and 0.3-1 μg/ml, respectively. The intra- and inter-day accuracy and precision, carryover, sensitivity and recovery were evaluated according to the US Food and Drug Administration guidance for bioanalytical method validation. Finally, the validated method was applied to a set of experimental animal samples and produced results highly comparable with those from an orthogonal analytical method.

The effect of loading mode on fatigue crack initiation of IN718 superalloy

The article deals with the effect of applied fatigue load with different cycle asymmetry parameters R, test temperature and loading frequency on fatigue crack initiation in IN718 superalloy. For this purpose, four sets of experimental samples were produced. The first and second sets of samples with cycle asymmetry parameter R = -1 were subjected to fatigue tests at loading frequency f ≈ 20,000 kHz and ambient temperature, respectively f ≈ 64 Hz and a temperature of 700°C. The third and fourth sets of samples with cycle asymmetry parameter R < 1 with loading frequency f ≈ 150 Hz and ambient temperature, respectively after applying annealing 800°C/72 hours. SEM fractography analysis was performed on all samples to define the fatigue crack initiation mechanism.

Effect of chemical desulfurization on coal properties and sulfur structure based on microwave technology

AbstractUnder the two frequency microwave conditions of 915 and 2450 MHz, orthogonal tests were designed to investigate the effects of organic acid reagent, microwave irradiation time, and mixing time of additives and coal samples on the desulfurization effect of coal. Results show that the effect of irradiation time on the experimental desulfurization efficiency under frequency microwave conditions is large and is the main factor. The desulfurization effect under 915 MHz microwave condition is better than 2450 MHz microwave condition. Two sets of experimental optimal coal samples were used for characterization and analysis. Thermogravimetric analysis revealed that the combustion temperature range of the coal samples is shortened and the integrated combustion index is considerably higher after the microwave irradiation experiment. Fourier‐transform infrared spectroscopy analysis showed that the overall chemical structure of the coal samples does not change significantly after the experimental treatment. X‐ray photoelectron spectroscopy analysis showed that the intensity of organic sulfur in coal samples is weakened after microwave irradiation, the characteristic peaks of thiols and thioethers are reduced to a great extent, and an increase in the intensity of sulfoxide organic sulfur is observed. On the basis of the results of experimental analysis and quantum chemical simulation calculations, the mechanism of organosulfur structure removal under the action of microwave is revealed.

Experimental and Meta-Analytic Validation of RNA Sequencing Signatures for Predicting Status of Microsatellite Instability.

Microsatellite instability (MSI) is an important diagnostic and prognostic cancer biomarker. In colorectal, cervical, ovarian, and gastric cancers, it can guide the prescription of chemotherapy and immunotherapy. In laboratory diagnostics of susceptible tumors, MSI is routinely detected by the size of marker polymerase chain reaction products encompassing frequent microsatellite expansion regions. Alternatively, MSI status is screened indirectly by immunohistochemical interrogation of microsatellite binding proteins. RNA sequencing (RNAseq) profiling is an emerging source of data for a wide spectrum of cancer biomarkers. Recently, three RNAseq-based gene signatures were deduced for establishing MSI status in tumor samples. They had 25, 15, and 14 gene products with only one common gene. However, they were developed and tested on the incomplete literature of The Cancer Genome Atlas (TCGA) sampling and never validated experimentally on independent RNAseq samples. In this study, we, for the first time, systematically validated these three RNAseq MSI signatures on the literature colorectal cancer (CRC) (n = 619), endometrial carcinoma (n = 533), gastric cancer (n = 380), uterine carcinosarcoma (n = 55), and esophageal cancer (n = 83) samples and on the set of experimental CRC RNAseq samples (n = 23) for tumors with known MSI status. We found that all three signatures performed well with area under the curve (AUC) ranges of 0.94–1 for the experimental CRCs and 0.94–1 for the TCGA CRC, esophageal cancer, and uterine carcinosarcoma samples. However, for the TCGA endometrial carcinoma and gastric cancer samples, only two signatures were effective with AUC 0.91–0.97, whereas the third signature showed a significantly lower AUC of 0.69–0.88. Software for calculating these MSI signatures using RNAseq data is included.

Complete stress–strain curves for pine needle fibre reinforced concrete under compression

To reduce the high consumption of natural resources by civil construction, in recent years, there are more and more re-searches on using natural biomass to replace coarse and fine natural aggregates. Masson pine needle fibre (MPNF) is an im-portant raw material for environment-friendly and cost-effective. In this paper, the surface of pine needles was directly modified by boiling water, 2% dilute alkali and soaking in water. Each set of experimental samples containing volume contents of MNPF with 30 mm length ranging from 0% to 2% by concrete volume were prepared. The stress–strain behaviour and the mechanical properties of pine needle fibre reinforced concrete (PNFRC) under uniaxial compression are studied. The result of this paper shows that the addition of pine needle fibre changed fracture process and improved the mechanical properties compare to that of plain concrete. Compared the fitting curve of the proposed equations and experimental date, it can be concluded that using 0.5% and 1% of dilute alkali-treated and boiling water-treated MPNF adding in the concrete, consents to obtain a composite with optimum mechanical properties, and the proposed model in this paper could express the stress–strain curves of PNFRC.

Chemical Oxygen Demand Can Be Converted to Gross Energy for Food Items Using a Linear Regression Model

Human and microbial metabolism are distinct disciplines. Terminology, metrics, and methodologies have been developed separately. Therefore, combining the 2 fields to study energetic processes simultaneously is difficult. When developing a mechanistic framework describing gut microbiome and human metabolism interactions, energy values of food and digestive materials that use consistent and compatible metrics are required. As an initial step toward this goal, we developed and validated a model to convert between chemical oxygen demand (COD) and gross energy (${E_g}$) for >100 food items and ingredients. We developed linear regression models to relate (and be able to convert between) theoretical gross energy (${E_g}^{\prime}$) and chemical oxygen demand (COD'); the latter is a measure of electron equivalents in the food's carbon. We developed an overall regression model for the food items as a whole and separate regression models for the carbohydrate, protein, and fat components. The models were validated using a sample set of computed ${E_g}^{\prime}$ and COD' values, an experimental sample set using measured ${E_g}$ and COD values, and robust statistical methods. The overall linear regression model and the carbohydrate, protein, and fat regression models accurately converted between COD and ${E_g}$, and the component models had smaller error. Because the ratios of COD per gram dry weight were greatest for fats and smallest for carbohydrates, foods with a high fat content also had higher ${E_g}$ values in terms of kcal · g dry weight-1. Our models make it possible to analyze human and microbial energetic processes in concert using a single unit of measure, which fills an important need in the food-nutrition-metabolism-microbiome field. In addition, measuring COD and using the regressions to calculate ${E_g}$ can be used instead of measuring ${E_g}$ directly using bomb calorimetry, which saves time and money.

A Preliminary Study on the Differentiation of Linseed and Poppy Oil Using Principal Component Analysis Methods Applied to Fiber Optics Reflectance Spectroscopy and Diffuse Reflectance Imaging Spectroscopy.

This paper presents results from the examination of a set of experimental samples using fibre optic reflectance spectroscopy (FORS) and diffuse reflectance imaging spectroscopy in the short-wave infrared (SWIR) range, combined with statistical analysis of the data for the discrimination and mapping of poppy and linseed oil. The aim was to evaluate the efficacy of this non-invasive approach for the study of paint samples with a view to the application of the method for characterisation of the two drying oils in painted art. The approach allowed discrimination between the two drying oils based on FORS spectra and the hyperspectral cube, indicating the influence of the spectral region around 1700 nm on the statistical discrimination based on the anti-symmetric and symmetric first overtone stretching of methylenic CH2 groups. This method is being studied as a potential non-invasive method of organic analysis of oil types that have formerly been studied using gas chromatography-mass spectrometry (GC-MS), which requires micro-samples.

Microbial-derived bio-surfactant using neem oil as substrate and its suitability for enhanced oil recovery

The limitation in the formulation and application of synthetic surfactants in petroleum industry is owing to their high cost of production or importation and their associated toxic effect which have been proven to be harmful to the environment. Hence it is vitally imperative to develop an optimum surfactant that is cost-effective, environmentally safe (biodegradable) and equally serves as surface acting agent. This study discusses the production of microbial produced bio-surfactant and its application in enhanced oil recovery. The bacteria Pseudomonas sp. were isolated from urine and allow to feed on neem seed oil as the major carbon source and energy. The crude bio-surfactant produced from the fermentation process was used to prepare three (3) solutions of bio-surfactants at different concentrations of 5 g/500 mL, 10 g/500 mL and 15 g/500 mL, and their suitability for enhanced oil recovery (EOR) was evaluated. Reservoir core samples and crude oil collected from the Niger Delta field were used to evaluate the EOR application of the microbial-derived surfactants. The sets of experimental samples were carried out using core flooding and permeability tester equipment, and the results obtained were compared with conventional waterflooding experiments. The three bio-surfactant concentrations were observed to recover more oil than the conventional waterflooding method for the two core samples used. Optimum performance of the produced microbial-derived surfactant on oil recovery based on the concentrations was observed to be 10 g/500 mL for the two samples used in this study. Therefore, eco-friendly bio-surfactant produced from neem seed oil using Pseudomonas sp. has shown to be a promising potential substance for enhanced oil recovery applications by incremental recoveries of 51.9%, 53.2%, and 29.5% at the concentration of 5, 10, and 15 g/500 mL and 24.7%, 28.7%, and 20.1% at concentration of 5, 10, and 15 g/500 mL for the two core samples, respectively.

Investigation for correction formulas on the basis of packed cell volume for blood glucose concentration measurements obtained with portable glucometers when used in rabbits.

To determine effects of PCV on blood glucose (BG) concentration measurements obtained with a human portable blood glucometer (HPBG) and a veterinary portable blood glucometer (VPBG) on canine (cVPBG) and feline (fVPBG) settings (test methods) when used in rabbits and to develop correction formulas to mitigate effects of PCV on such measurements. 48 resuspended blood samples with known PVCs (range, 0% [plasma] to 92% [plasma and packed RBCs]) from 6 healthy research rabbits (experimental sample set) and 252 historic measurements of BG concentration and PCV in 84 client-owned rabbits evaluated at a veterinary hospital (validation data set). Duplicate measurements of BG concentration with each test method and of PCV were obtained for each sample in the experimental sample set, and the mean results for each variable for each test method and sample were compared with results from a clinical laboratory analyzer (reference method) used to determine the true BG concentration for each sample. Mean ± SD differences in measurements between the reference and test methods were calculated. Linear regression and modified Clarke error grid analysis were used to develop correction formulas for the test methods given known PCVs, and these formulas were evaluated on the validation data set with linear regression and a modified Clarke error grid. Blood glucose concentrations were falsely low for cVPBG and fVPBG used on samples with PCV < 31% and were falsely high for all test methods used on samples with PCV > 43%. Compared with original measurements, formula-corrected measurements overall had better agreement with reference method measurements for the experimental sample set; however, only the formula-corrected HPBG measurements had improved agreement for the validation data set. Findings indicated that, in rabbits, HPBG measurements had improved accuracy with the use of the correction formula HPBG measurement of BG concentration + ([0.75 × PCV] - 15); however, the correction formulas did not improve the accuracy of VPBG measurements, and we believe that neither the cVPBG nor fVPBG should be used in rabbits.

A semi-physical static model for optimizing power consumption of HVAC systems

Mathematical models of heating, ventilation and air conditioning (HVAC) systems is of great significance for optimizing power consumptions in large buildings. This paper proposes a semi-physical model to describe static characters of a typical HVAC system. Major components of the HVAC system are modeled individually according to their thermodynamic principles or input–output relations, and are integrated into an overall model by choosing input and output variables from a perspective of optimizing power consumptions. One set of experimental data samples is used to estimate unknown model coefficients, and more data sets are taken to validate the estimated model. Based on the estimated model, genetic algorithms are exploited to find the optimal operating point of the HAVC system for minimizing power consumptions under constraints on indoor temperatures.

Study on Corrosion Resistance and Bio-Tribological Behavior of Porous Structure Based on the SLM Manufactured Medical Ti6Al4V

Titanium and its alloy, especially Ti6Al4V is one of the most widely used metal due to its excellent properties. Selective laser melting, which is known as additive manufacturing is considered as a suitable method to manufacture Ti6Al4V parts. To print a more analogous Ti6Al4V artificial bone, laser power was changed by taking volume porosity, corrosion resistance and wear resistance into consideration. The testing results showed that sample printed using 200 W showed a relative optimal corrosion resistance and volume porosity in all these five samples (the value of corrosion voltage is − 0.352 V), while it showed the best bio-tribological behavior, and its wear volume is as low as 5.90 μm3. Summarize the 5 sets of experimental samples, the Ti6Al4V part printed using 180–200 W were the most prominent in the test, its overall performance was, indeed, best fit to print artificial Ti6Al4V bone, because it is similar to bone, there are a large number of microporous structures. Corrosion mechanism At the oxide film/metal interface, the metal undergoes an ionization reaction to form M2+, the O2 molecule forms an atomic state of oxygen by physical adsorption on the metal surface, and then chemically adsorbs to form O−, and is bonded to the oxide crystal lattice in an O2− state to form a new oxide which hinders further oxidation. The presence of voids also reduces the corrosion resistance of the substrate material due to the increased corrosion area, and corrosive ions are more likely to penetrate into corrosive materials. Wear mechanism Ploughing wear and oxidation erode can be seen on the surface while ploughing wear was the most significant mechanism. From the EDS results, it can be found that the abrasive dust was mainly composed of TiO2. This phenomenon was due to the fact that Ti is a kind of active metal and it is easily oxidized. That is the reason why oxidation erode can also be found on the surface and it further explained the equivalent circuit given in corrosion behavior section.

TASBE Flow Analytics: A Package for Calibrated Flow Cytometry Analysis.

Flow cytometry is a powerful method for high-throughput precision measurement of cell fluorescence and size. Effective use of this tool for quantification of synthetic biology devices and circuits, however, generally requires careful application of complex multistage workflows for calibration, filtering, and analysis with appropriate statistics. The TASBE Flow Analytics package provides a free, open, and accessible implementation of such workflows in a form designed for high-throughput analysis of large synthetic biology data sets. Given a set of experimental samples and controls, this package can process them to output calibrated data, quantitative analyses and comparisons, automatically generated figures, and detailed debugging and diagnostic reports in both human-readable and machine-readable forms. TASBE Flow Analytics can be used through a simple user-friendly interactive Excel interface, as a library supporting Matlab, Octave, or Python interactive sessions, or as a component integrated into automated workflows.

Method for the prediction of time series using small sets of experimental samples

The paper is concerned with the method of prediction of time series based on the concepts of system identification. The distinctive property of the method is the use of small sets of experimental samples of data. The latter create some basis for building so-called learning subsets, which are used to construct particular prediction models. Values of variables predicted by different particular models allow calculating the desired variables by using a batch voting technique. The method can be used for short-term prediction of data values at future time instants based on the analysis of a brief history of the process under consideration. It can be useful in cases of processing very large arrays of data samples, when the researcher has to confirm his (her) attention to only a small part of the samples received at the last instants of time, in view of the limited memory of the computer or in cases when very slow processes are analyzed. A special place in the paper is given to the example in which the computational aspects of the proposed method are considered in detail.

Perovskite Solar Cells with Increased Resistance to Moisture

This article compares two methods of perovskite solar cells manufacturing process due to their resistance against moisture. Two sets of experimental perovskite samples were subjected to the study. Solar cells were exposed to increasing humidity in the climatic chamber. The results have shown that cells manufactured in a 15% relative humidity environment are more resistant to later external environmental influences. The reason is probably in a low moisture presence during the perovskite solar cell production process which contributes to increased resistance against later degradation effects of water molecules.

An Optimization Study on Listening Experiments to Improve the Comparability of Annoyance Ratings of Noise Samples from Different Experimental Sample Sets.

Annoyance ratings obtained from listening experiments are widely used in studies on health effect of environmental noise. In listening experiments, participants usually give the annoyance rating of each noise sample according to its relative annoyance degree among all samples in the experimental sample set if there are no reference sound samples, which leads to poor comparability between experimental results obtained from different experimental sample sets. To solve this problem, this study proposed to add several pink noise samples with certain loudness levels into experimental sample sets as reference sound samples. On this basis, the standard curve between logarithmic mean annoyance and loudness level of pink noise was used to calibrate the experimental results and the calibration procedures were described in detail. Furthermore, as a case study, six different types of noise sample sets were selected to conduct listening experiments using this method to examine the applicability of it. Results showed that the differences in the annoyance ratings of each identical noise sample from different experimental sample sets were markedly decreased after calibration. The determination coefficient (R2) of linear fitting functions between psychoacoustic annoyance (PA) and mean annoyance (MA) of noise samples from different experimental sample sets increased obviously after calibration. The case study indicated that the method above is applicable to calibrating annoyance ratings obtained from different types of noise sample sets. After calibration, the comparability of annoyance ratings of noise samples from different experimental sample sets can be distinctly improved.

The Role of Different Atmospheric Plasma Spray Parameters on Microstructure of Abradable AlSi-Polyester Coatings

One of the approaches to increase the thermic efficiency of aerospace engines is the application of abradable coatings enabling minimization and control of the clearance between the stator and the rotating blades tips. The main purpose of this contribution is to define the role of different technological parameters utilized for atmospheric plasma spraying of AlSi-polyester coating on its resulting microstructure. Deposition of abradable coatings on the real engine parts is mostly dependent on spraying stand-off distance and on spraying angle. These two parameters influence not only the coating microstructure but also the deposition efficiency itself, which is directly connected with economical aspects of the coating production. The set of experimental samples with atmospheric plasma sprayed Ni-based bond coat and two in chemical composition same initial powders delivered from different powder manufacturers were used to spray thick AlSi-polymer top coats with different spraying stand-off distances and angles. Subsequently some of the samples were also heat treated to burn-out the polymer phase from the coating microstructure. The Rockwell HR15Y hardness was measured on all samples and the microstructure and coating thickness were evaluated by means of light microscopy and image analysis methods.