Characteristic tryptic peptides and gelling properties of porcine skin gelatin affected by thermal action

Thermal action in extraction process had effects on characteristic tryptic peptides identification and gelling properties of porcine gelatin. SDS-PAGE, HPLC-LTQ/Orbitrap high-resolution mass spectrometry, texture analyser and rheometer were used to evaluate collagen depolymerisation degree, characteristic tryptic peptides and gelling properties of gelatins prepared in various thermal actions. Results showed that with increasing temperature and time, depolymerisation degree enlarged, while gel strength, gelling and melting temperature decreased. Mass spectra showed that 47 and 49 common characteristic tryptic peptides were identified in gelatins extracted at 50 °C and 100 °C with various times, respectively. Moreover, 34 common characteristic tryptic peptides were identified in all gelatin samples. Further comparison between this work and our previous investigations yielded 20 common characteristic tryptic peptides, which stably exist in various thermal actions. These common characteristic tryptic peptides may be very helpful for the accurate authentication of porcine gelatin.     

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.     

Relationships of tensile strength with crosslink density for the high-carbon black-filled EPDM compounds with various softeners

Equilibrium swelling and rheological tests were adopted to systematically investigate the effects of softener type and dosage on the crosslink densities. The results turned out that the chemical crosslink density could be distinguished from the physical crosslink density by comparing the results of equilibrium swelling and rheological tests. The liquid butadiene (LB) as a softener leads to the greatest reduction in crosslink density, followed by polyethylene wax (PW) and paraffinic oil (PO). The tensile strength decreases with increasing PO content while shows peak values with increase of LB and PW contents. The dependencies of chemical crosslink density on the aging time under 150°C are quite different for the three softeners, which can be expected from the double crosslinking networks consisting of small softener and large main crosslinking networks. Further investigation has been performed to correlate the tensile strength with chemical crosslink density of ethylene propylene diene monomer elastomer vulcanizates. Three different linear relationships can be obtained for the softeners independent of the aging time. It can now be expected from this study that the role of some new softeners in rubber compounds is not only confined to plasticization but also forms crosslinking networks in the peroxide-cured rubbers.     

Hydrogeochemical Processes and Inverse Modeling for a Multilayer Aquifer System in the Yuaner Coal Mine,Huaibei Coalfield,China

Coal mining can dramatically change hydrogeological conditions and induce serious environmental problems. Fifty groundwater samples were collected from the main aquifers in the Yuaner coal mine (Anhui Province, China). The results show that the main hydrogeochemical processes in the mine include dissolution, precipitation, pyrite oxidation, desulfurization, and cation exchange. The Neogene porous aquifer is affected by groundwater flow conditions; its main hydrogeochemical processes are dissolution of carbonate minerals and gypsum, and cation exchange. The Permian coal measure’s fractured sandstone aquifer was confirmed to be controlled by the region’s geological structure; its main hydrogeochemical processes are desulfurization and cation exchange. The Carboniferous Taiyuan limestone aquifer was determined by both groundwater flow conditions and regional geological structure; its main hydrogeochemical processes are dissolution of carbonate minerals and gypsum, pyrite oxidation, and cation exchange. Additionally, hydrogeochemical inverse modeling of the groundwater flow path confirm the hydrochemistry results and principal component analysis.

     

A self-adaptive synthetic over-sampling technique for imbalanced classification

Traditionally, in supervised machine learning, (a significant) part of the available data (usually 50%-80%) is used for training and the rest—for validation. In many problems, however, the data are highly imbalanced in regard to different classes or does not have good coverage of the feasible data space which, in turn, creates problems in validation and usage phase. In this paper, we propose a technique for synthesizing feasible and likely data to help balance the classes as well as to boost the performance in terms of confusion matrix as well as overall. The idea, in a nutshell, is to synthesize data samples in close vicinity to the actual data samples specifically for the less represented (minority) classes. This has also implications to the so-called fairness of machine learning. In this paper, we propose a specific method for synthesizing data in a way to balance the classes and boost the performance, especially of the minority classes. It is generic and can be applied to different base algorithms, for example, support vector machines, k-nearest neighbour classifiers deep neural, rule-based classifiers, decision trees, and so forth. The results demonstrated that (a) a significantly more balanced (and fair) classification results can be achieved and (b) that the overall performance as well as the performance per class measured by confusion matrix can be boosted. In addition, this approach can be very valuable for the cases when the number of actual available labelled data is small which itself is one of the problems of the contemporary machine learning.     

Human responses to high levels of carbon dioxide and air temperature

In this study, 30 subjects were exposed to different combinations of air temperature (T_a: 24, 27, and 30°C) and CO₂ level (8000, 10 000, and 12 000 ppm) in a high-humidity (RH: 85%) underground climate chamber. Subjective assessments, physiological responses, and cognitive performance were investigated. The results showed that as compared with exposure to T_a = 24°C, exposure to 30°C at all CO₂ levels caused subjects to feel uncomfortably warm and experience stronger odor intensity, while increased mental effort and greater intensity of acute health symptoms were reported. However, no significant effects of T_a on task performance or physiological responses were found. This indicated that subjects had to exert more effort to maintain their performance in an uncomfortably warm environment. Increasing CO₂ from 8000 to 12 000 ppm at all T_a caused subjects to report higher rates of headache, fatigue, agitation, and feeling depressed, although the results were statistically significant only at 24 and 27°C. The text typing performance and systolic blood pressure (SBP) decreased significantly at this exposure, whereas diastolic blood pressure (DBP) and thermal discomfort increased significantly. These effects suggest higher arousal/stress. No significant interaction effect of T_a and CO₂ concentration on human responses was identified.     

Microwave drying performance of lignite with the assistance of biomass-derived char

Microwave lignite drying with assistance of biomass-derived char was addressed and effect of bio-char on drying rate and energy consumption was investigated in this work. Effective diffusion coefficient and activation energy for the drying process were also analyzed. The results indicated the drying process was largely dependent on the variation of sample temperature. Bio-char originated from pine wood was most favorable for lignite drying, considering its better promoting effect and advanced security. There existed an optimal bio-char addition ratio for drying process at different power. The corresponding optimal ratio was 10% at 231?W and 15% at 385?W, at which the biggest drying rate and the least energy consumption were reached. It was compared lignite drying initiated at 385?W was better for energy conservation. Effective diffusivity was improved and activation energy was simultaneously reduced, with the addition of bio-char. The minimum activation energy was 15.54?W?·?g^?1, which was gained at bio-char addition ratio of 10%. The results revealed the effect of bio-char on depressing activation energy could rival that of metal-based additives. The drying process with assistance of microwave and bio-char could present technical and economical benefits on lignite upgrading.     

Headspace fingerprinting approach to identify the major pathway influencing volatile patterns of vinasse-cured duck processed by high pressure,as well as its impact on physicochemical and sensory attributes

As a decisive attribute, flavour could be influenced by HP treatments through multiple physical and chemical pathways within the high pressure (HP)-assisted meat curing process. This investigation aimed to identify the major pathway influencing volatile flavour patterns of two representative vinasse-cured duck (VCD) products with HP treatments (150–300 MPa/15 min), including wet and dry types, by employing headspace fingerprinting as an untargeted approach. Results suggested that HP treatments greatly lowered moisture contents and increased Warner-Bratzler shear force and thiobarbituric acid reactive substances of the cured samples. According to multivariate models, the volatile flavour patterns of the HP-processed VCD could be clearly separated from the unprocessed samples, but the VCD pressurised at different intensities represented similar volatile fingerprinting, which was validated by e-nose analysis. The discriminant analysis (OPLS-DA) model outlined vinasse-derived ethanol, acetic acid, 3-methyl-1-butanol, 2-methyl-1-butanol, phenethyl alcohol and 2-methyl-3-octanone as the major discriminant aromas across the unpressurised and pressurised samples.     

环保法规对船舶涂料企业的冲击及应对措施的探讨

随着我国环境保护法规《大气污染防治法》的修订和《涂料征收消费税通知》的公布,探讨了其对船舶涂料企业的冲击及其应对措施。