Authenticity green coffee bean species and geographical origin using near-infrared spectroscopy combined with chemometrics

To prevent the adulteration of agricultural resources and provide a solution to enhance the green coffee bean supply chain, authentication using the near-infrared spectroscopy (NIRS) technique was investigated. Partial least square with discrimination analysis (PLS-DA) models combined with various preprocessing methods were built from NIR spectra of 153 Vietnamese green coffee samples. The model combined with the standard normal variate and the first order of derivative yielded excellent performance in predicting coffee species with the error cross-validation of 0.0261. PLS-DA model of mean centre and first-order derivative spectra also yielded good performance in verifying geographical indication of green coffee with the error of 0.0656. By contrast, the predicting abilities of post-harvest methods were poor. The overall results showed a high potential of the NIRS in online authentication practices.     

Development of ensemble machine learning approaches for designing fiber-reinforced polymer composite strain prediction model

Engineering with Computers - Over the past few decades, it has been observed a remarkable progression in the development of computer aid models in the field of civil engineering. Machine learning...     

胶体电泳速度测定实验改进探索

胶体电泳速度测定实验是大学物理化学实验中一个重要的综合性教学实验.本文针对该实验中存在半透膜制作不稳定、渗析时间过长、电泳现象不明显、胶体/辅助液界面不清晰等问题.从胶体浓度、电极电压、半透膜、稳定剂四个方面进行了改进.结果表明,胶体界面移动距离,胶体/辅助液界面的清晰程度都有很大的改善,大大提高了实验的体验感.     

Effect of malondialdehyde oxidation on structure and physicochemical properties of amandin

Oil, accounting for 45% of almonds, is easily oxidised and can further induce the protein oxidation to reduce their quality. Structure and physicochemical properties of amandin, the main water-soluble protein in almonds, inducing oxidation by malondialdehyde (MDA) were investigated. The results showed that the content of carbonyl group increased from 5.23 to 33.25 nmol mg⁻¹ of protein with the increase in MDA concentration (P < 0.05). However, the sulphydryl content, surface hydrophobicity, particle size and the absolute value of ζ-potential first increased and then decreased. Fourier-transformed infrared spectroscopy (FT-IR) confirmed that the structure of amandin changed from order to disorder. Fluorescence spectroscopic analysis revealed that mild oxidation (0–0.1 mmol L⁻¹ MDA) exposed hydrophobic groups of the protein. Sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) suggested that protein oxidation promoted crosslinking between protein molecules. Furthermore, protein oxidation markedly declined the total amino acid content of amandin (P < 0.05). In conclusion, MDA oxidation changed the structure and amino acid content of amandin, and caused the protein aggregate and crosslink through hydrophobic interaction and electrostatic interaction.     

Stochastic grid bundling method for backward stochastic differential equations

ABSTRACT

In this work, we apply the Stochastic Grid Bundling Method (SGBM) to numerically solve backward stochastic differential equations (BSDEs). The SGBM algorithm is based on conditional expectations approximation by means of bundling of Monte Carlo sample paths and a local regress-later regression within each bundle. The basic algorithm for solving the backward stochastic differential equations will be introduced and an upper error bound is established for the local regression. A full error analysis is also conducted for the explicit version of our algorithm and numerical experiments are performed to demonstrate various properties of our algorithm.     

Single transition metal atom catalysts on Ti2CN2 for efficient CO2 reduction reaction

Electrochemical CO₂ reduction reaction (CO₂RR) is an efficient way in the utilization of CO₂. In this work, single transition-metal (TM) atom (TM = Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn) anchored on two-dimensional (2D) Ti₂CN₂ are designed for CO₂RR using density-functional-theory (DFT) calculation. We show that Ti₂CN₂ serves as an excellent substrate to support single atom catalysts (SACs), compared to Ti₂CO₂ and Ti₂CF₂. We find that the Sc, Ti and V supported on Ti₂CN₂ show high catalytic activities to produce CO with a low overpotential of 0.37, 0.27, and 0.23 eV, respectively. Differently, the Mn and Fe on Ti₂CN₂ are catalytically active for the production of HCOOH with a low overpotential of 0.32 and 0.43 eV, respectively. We further show that the negatively charged TM-Ti₂CN₂ can capture and activate CO₂ more effectively, and the catalytic activity and selectivity can be significantly tuned by injecting extra electrons.     

Cyanogenic,carotenoids and protein composition in leaves and roots across seven diverse population found in the world cassava germplasm collection at CIAT,Colombia

The objective of this study was to characterise the nutritional potential of leaves and identify a diversity centre with low cyanide and high nutrient content among 178 Latin American cassava genotypes. This field-based collection represents the seven diversity centres, held at The International Center for Tropical Agriculture (CIAT Palmira, Colombia) by the Cassava Program. The cyanide, all-trans-β-carotene and lutein concentrations in cassava leaves ranged from 346 to 7484 ppm dry basis (db), from 174–547 μg g⁻¹ db and 15–181 μg g⁻¹ db, respectively. Cassava leaves also showed significant levels of essential amino acids leucine, lysine, phenylalanine, valine and threonine, and average total protein content of 26.24 g 100 g⁻¹ db. Among seven diversity centres, South American rainforest group showed low cyanide and high carotene content in leaves. In addition, VEN77 and PAN51 genotypes stood out for having low cyanide in leaves and roots and high carotene in leaves. This genetic diversity can be used to select high potential progenitors for breeding purposes.     

Ultra-Robust Flexible Electronics by Laser-Driven Polymer-Nanomaterials Integration

Polyethylene terephthalate (PET) is the most widely used polymer in the world. For the first time, the laser-driven integration of aluminum nanoparticles (Al NPs) into PET to realize a laser-induced graphene/Al NPs/polymer composite, which demonstrates excellent toughness and high electrical conductivity with the formation of aluminum carbide into the polymer is shown. The conductive structures show an impressive mechanical resistance against >10000 bending cycles, projectile impact, hammering, abrasion, and structural and chemical stability when in contact with different solvents (ethanol, water, and aqueous electrolytes). Devices including thermal heaters, carbon electrodes for energy storage, electrochemical and bending sensors show this technology's practical application for ultra-robust polymer electronics. This laser-based technology can be extended to integrating other nanomaterials and create hybrid graphene-based structures with excellent properties in a wide range of flexible electronics’ applications.     

Simulation is essential for embedded control systems with task jitter

Sampling or task jitter affects the performance of digital control systems but realistic simulation of this effect has not been possible to date. Our previous work has developed a novel method to simulate sampling jitter in MATLAB/Simulink simulation software where the jitter is generated randomly. What has been missing is a way to capture sampling jitter from a target platform and then feed this timing information into the simulation. This paper presents a low-cost and novel solution to these problems. The method uses an Arduino board to capture task jitter from two different hardware platforms with multiple stressing conditions. Then the recorded performance data is used to drive realistic simulations of a control system. Measurement shows that the task jitter data does not follow any specific random distribution such as Gaussian or Uniform. Furthermore, very occasional timing patterns, which may not be picked up while testing a real system, can result in extreme controller responses. This novel method allows comparisons of different platforms and reduces the effort required to choose the most appropriate platform for full implementation.