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.     

Photocatalytic degradation and heat reflectance recovery of waterborne acrylic polymer/ZnO nanocomposite coating

This work aims to clarify the photocatalytic degradation mechanism and heat reflectance recovery performance of waterborne acrylic polymer/ZnO nanocomposite coating. To fabricate the nanocomposite coating, ZnO nanoparticles (nano-ZnO) were dispersed into acrylic polymer matrix at the various concentrations from 1 to 6% (by total weight of resin solids). The photocatalytic degradation of nanocomposite coating under ultraviolet (UV) light irradiation has been investigated by monitoring its weight loss and chemical/microstructural/morphological changes. As the topcoat layer, its heat reflectance recovery has been evaluated under UV/condensation exposure by using an artificial dirty mixture of 85 wt% nanoclay, 10 wt% silica particles (1–5 μm), 1 wt% carbon black, and 2 wt% engine oil. After 108-cycle UV/condensation exposure, infrared spectra and weight loss analysis indicated that the maximal degradation for nanocomposite coating is observed at 1 wt% nano-ZnO. On the other hand, after 96 hr of UV light exposure, the nanocomposite coating with1 wt% nano-ZnO could restore effectively the reflective index of solar-heat reflectance coating (from 58.45 to 80.78%). Finally, the photodegradation mechanism of this waterborne acrylic polymer coating has been proposed as the UV-induced formation of CC CO conjugated double bonds. As a result, its self-cleaning phenomenon can be achieved as the recovery of heat reflectance.     

Coexistence of three ferroelectric phases and enhanced piezoelectric properties in BaTiO3–CaHfO3 lead-free ceramics

Perovskite ferroelectrics possess the fascinating piezoelectric properties near a morphotropic phase boundary, attributing to a low energy barrier that the results in structural instability and easy polarization rotation. In this work, a new lead-free system of (1-x)BaTiO₃-xCaHfO₃ was designed, and characterized by a coexistence of ferroelectric rhombohedral-orthorhombic-tetragonal (R-O-T) phases. With the increase amount of CaHfO₃ (x), a stable coexistence region of three ferroelectric phases (R-O-T) exists at 0.06 ≤ x ≤ 0.08. Both large piezoelectric coefficient (d₃₃～400 pC/N), inverse piezoelectric coefficient (d₃₃^*～547 pm/V) and planar electromechanical coupling factor (k_p～58.2%) can be achieved for the composition with x = 0.08 near the coexistence of three ferroelectric phases. Our results show that the materials with the composition located at a region where the three ferroelectric R-O-T phases coexist would have the lowest energy barrier and thus greatly promote the polarization rotation, resulting in a strong piezoelectric response.     

Research on the overall architecture of Internet of Things middleware for intelligent industrial parks

With the continuous development of the Internet of Things technology and the proposal of “Made in China 2025”, the construction of IoT applicat     

The extended quadratic residue code is the only (48,24,12) self-dual doubly-even code

An extremal self-dual doubly-even binary (n,k,d) code has a minimum weight d=4/spl lfloor/n/24/spl rfloor/+4. Of such codes with length divisible by 24, the Golay code is the only (24,12,8) code, the extended quadratic residue code is the only known (48,24,12) code, and there is no known (72,36,16) code. One may partition the search for a (48,24,12) self-dual doubly-even code into three cases. A previous search assuming one of the cases found only the extended quadratic residue code. We examine the remaining two cases. Separate searches assuming each of the remaining cases found no codes and thus the extended quadratic residue code is the only doubly-even self-dual (48,24,12) code.     

Mining constrained gradients in large databases

Many data analysis tasks can be viewed as search or mining in a multidimensional space (MDS). In such MDSs, dimensions capture potentially important factors for given applications, and cells represent combinations of values for the factors. To systematically analyze data in MDS, an interesting notion, called "cubegrade" was recently introduced by Imielinski et al. [2002], which focuses on the notable changes in measures in MDS by comparing a cell (which we refer to as probe cell) with its gradient cells, namely, its ancestors, descendants, and siblings. We call such queries gradient analysis queries (GQs). Since an MDS can contain billions of cells, it is important to answer GQs efficiently. We focus on developing efficient methods for mining GQs constrained by certain (weakly) antimonotone constraints. Instead of conducting an independent gradient-cell search once per probe cell, which is inefficient due to much repeated work, we propose an efficient algorithm, LiveSet-Driven. This algorithm finds all good gradient-probe cell pairs in one search pass. It utilizes measure-value analysis and dimension-match analysis in a set-oriented manner, to achieve bidirectional pruning between the sets of hopeful probe cells and of hopeful gradient cells. Moreover, it adopts a hypertree structure and an H-cubing method to compress data and to maximize sharing of computation. Our performance study shows that this algorithm is efficient and scalable. In addition to data cubes, we extend our study to another important scenario: mining constrained gradients in transactional databases where each item is associated with some measures such as price. Such transactional databases can be viewed as sparse MDSs where items represent dimensions, although they have significantly different characteristics than data cubes. We outline efficient mining methods for this problem.     

Nonlinear protein binding and enzyme heterogeneity: effects on hepatic drug removal

The kinetics of substrate removal by the liver and the resulting nonlinear changes in unbound fraction along the flow path at varying input drug concentrations were examined by a model simulation study. Specifically, we varied the binding association constant, KA, and the Michaelis-Menten constants (Km and Vmax) to examine the steady state drug removal (expressed as hepatic extraction ratio E) and changes in drug binding for (i) unienzyme systems and (ii) simple, parallel metabolic pathways; zonal metabolic heterogeneity was also added as a variable. At low KA, E declined with increasing input drug concentration, due primarily to saturation of enzymes; only small differences in binding were present across the liver. At high KA, a parabolic profile for E with concentration was observed; changes in unbound fraction between the inlet and the outlet of the liver followed in parallel fashion. Protein binding was the rate-determining step at low input drug concentrations, whereas enzyme saturation was the rate-controlling factor at high input drug concentration. Heterogeneous enzymic distribution modulated changes in unbound fraction within the liver and at the outlet. Despite marked changes in unbound fraction occurring within the liver for different enzymic distributions, the overall transhepatic differences were relatively small. We then investigated the logarithmic average unbound concentration and the length averaged concentration as estimates of substrate concentration in liver in the presence of nonlinear drug binding. Fitting of simulated data, with and without assigned random error (10%), to the Michaelis-Menten equation was performed; fitting was repeated for simulated data obtained with presence of a specific inhibitor of the high-affinity, anteriorly distributed pathway. Results were similar for both concentration terms: accurate estimates were obtained for anterior, high affinity pathways; an overestimation of parameters was observed for the lower affinity posteriorly distributed pathways. Improved estimations were found for posteriorly distributed pathways upon inhibition with specific inhibitors; with added random error, however, the improvement was much decreased. We applied the method for fitting of several sets of metabolic data obtained from rat liver perfusion studies performed with salicylamide (SAM) (i) without and (ii) with the presence of 2,6-dichloro-4-nitrophenol (DCNP), a SAM sulfation inhibitor. The fitted results showed that SAM sulfation was a high-affinity high-capacity pathway; SAM glucuronidation was of lower affinity but comparable capacity as the sulfation pathway, whereas SAM hydroxylation was of lower affinity and lower capacity.