Volatile and non-volatile compound profiles of commercial sweet pickled mango and its correlation with consumer preference

Sweet pickled mango named Ma-Muang Bao Chae-Im is a traditional preserved mango from Hat Yai, Thailand. This study investigated (I) volatile and non-volatile compound profiles of commercial Ma-Muang Bao Chae-Im and (II) their relationship to consumer preference. Untargeted metabolomics profiling was performed by gas chromatography-mass quadrupole-time of flight analysis. There were 117 volatile and 44 non-volatile compounds annotated in six commercial brands of Ma-Muang Bao Chae-Im. Furthermore, 46 volatile and 19 non-volatile compounds’ discriminant markers were found by Partial least square discriminant analysis. Among those markers, sorbic and benzoic acid were observed in several brands; moreover, the combination of both compounds altered the volatile profile, especially the ester group. Partial least square regression revealed that overall consumer liking is correlated to 1-heptanol; 1-octanol; acetoin; acetic acid, 2-phenylethyl ester; D-manitol; terpenes and terpenoids, while firmness to sucrose and L-(-)-sorbofuranose. On the other hand, most ester compounds were not related to consumer preference.     

Data fusion and transfer learning empowered granular trust evaluation for Internet of Things

In the Internet of Things (IoT), a huge amount of valuable data is generated by various IoT applications. As the IoT technologies become more complex, the attack methods are more diversified and can cause serious damages. Thus, establishing a secure IoT network based on user trust evaluation to defend against security threats and ensure the reliability of data source of collected data have become urgent issues, in this paper, a Data Fusion and transfer learning empowered granular Trust Evaluation mechanism (DFTE) is proposed to address the above challenges. Specifically, to meet the granularity demands of trust evaluation, time–space empowered fine/coarse grained trust evaluation models are built utilizing deep transfer learning algorithms based on data fusion. Moreover, to prevent privacy leakage and task sabotage, a dynamic reward and punishment mechanism is developed to encourage honest users by dynamically adjusting the scale of reward or punishment and accurately evaluating users’ trusts. The extensive experiments show that: (i) the proposed DFTE achieves high accuracy of trust evaluation under different granular demands through efficient data fusion; (ii) DFTE performs excellently in participation rate and data reliability.     

Effect of cooking temperature on texture and flavour binding of braised sauce porcine skin

To investigate the effect of cooking temperature (55, 65, 75, 85 and 95 °C) on texture and flavour binding of braised sauce porcine skin (BSPS), sensory acceptance, microstructure and flavour-binding capacity were investigated during the processing of BSPS. Samples cooked at 85 and 95 °C showed better texture and aroma scores. Hardness and chewiness of BSPS were obviously improved at 85 and 95 °C than control group. Collagen structure was significantly destroyed over 85 °C. The porcine skin collagen heated at 85 and 95 °C showed relatively higher flavour-binding capacity than other samples. The improvement of texture of BSPS was mainly attributed to the degradation of collagen. Higher aroma scores of BSPS were related to intense binding abilities with aroma compounds at 85 and 95 °C. Cooking at 85 or 95 °C could be an optimal cooking temperature for BSPS.     

Mass transfer in polycrystalline ytterbium monosilicate under oxygen potential gradients at high temperatures

Mass transfer in polycrystalline Yb₂SiO₅ wafers with precise composition control was evaluated and analyzed by oxygen permeation experiments at high temperatures using an oxygen tracer. Oxygen permeation proceeded due to mutual grain boundary diffusion of oxide ions and Yb ions without synergistic effects such as acceleration or suppression. The oxygen shielding properties of Yb₂SiO₅ were compared with those of the other line compounds such as Yb₂Si₂O₇ and Al₂O₃ based on the determined mass transfer parameters. It was found that the more preferentially an oxide ion diffuses in the grain boundary compared to the interior of the grain, the greater the effect of suppressing the movement of the oxide ion by applying an oxygen potential gradient becomes.     

我国水-能源-粮食耦合关系及影响因素

为缓解我国水、能源和粮食资源紧张问题，促进资源可持续利用，构建水-能源-粮食系统，利用耦合协调度模型对我国的30个省（自治区、直辖市）进行测算,并利用空间杜宾模型分析主要影响因素。结果表明：2003—2017年，我国能源、粮食评价[JP]指数高于水资源评价指数，系统综合评价指数逐年递增；大部分省份耦合协调度处于初级协调水平且呈现逐年上升的态势，个别省份耦合协调度濒临失调；耦合协调度空间自相关性较强，虽有明显波动，但是呈现逐年加强的态势；影响耦合协调度的主要因素有从业人口数、固定资产投资额、人均生产总值、人口总数、[JP]文盲人口占比、工业污染排放、城镇化。     

Effect of heat treatment on structural,morphological, dielectric and magnetic properties of Mg–Zn ferrite nanoparticles

Green combustion was used to prepare a ferrite composition of Mg_0.4Zn_0.6Fe₂O₄ using a blend of fresh lemon juice as a natural fuel-reductant. Effect of heat treatment on phase, morphological, dielectric, and humidity sensor properties is discussed. The formation of a cubic spinel ferrite has been established by XRD-diffraction and vibrational spectroscopic studies. The experimental lattice parameter ranges from 8.3721 to 8.3631 Å. The broadening of octahedral band (υ₂) in the vibrational spectra is an identification for the existence of ferrite nanoparticles in various sizes. The typical crystallite size ranges from 10.2 to 36.9 nm. Using micrographs obtained from field-effect scanning electron microscopy (FESEM), researchers observed a spherical-shaped microstructure with agglomerated nanoparticles. Dielectric investigations have shown that the current ferrite composition has typical dielectric dispersion. The highest reported value for saturation magnetization (M_s) in the present study is 33 emu/g. Magnetic behaviour is primarily influenced by magnetocrystalline anisotropy, cation distribution, and crystallite size. The existence of void spaces in the sintered samples, as well as their porous nature, rendered them suitable for humidity sensor applications. Sintered samples have good sensing capability at 900 °C. The current findings are integrated in terms of cation distribution and magnetocrystalline anisotropy, assuming fine size effects of ferrite nanoparticles.     

中国智能机械制造评价及发展研究

以中国规模以上工业企业数据库为基础，结合在智能制造主要区域调研的结果，筛选出15145家智能制造企业，经同行评议后，生成322家候选企业名单；再由资深产业专家从“开发式创新”和“探索式创新”两个方面去考察候选企业的能力，得到中国智能制造百强排行榜；随后根据行业分类，得到智能机械制造企业排行榜。在概述了智能机械制造上榜企业的基本情况后，着重分析了前20强企业，并提出了中国智能机械制造发展路径和未来的发展趋势。     

Revealing Electrical-Poling-Induced Polarization Potential in Hybrid Perovskite Photodetectors

Despite recent rapid advances in metal halide perovskites for use in optoelectronics, the fundamental understanding of the electrical-poling-induced ion migration, accounting for many unusual attributes and thus performance in perovskite-based devices, remain comparatively elusive. Herein, the electrical-poling-promoted polarization potential is reported for rendering hybrid organic–inorganic perovskite photodetectors with high photocurrent and fast response time, displaying a tenfold enhancement in the photocurrent and a twofold decrease in the response time after an external electric field poling. First, a robust meniscus-assisted solution-printing strategy is employed to facilitate the oriented perovskite crystals over a large area. Subsequently, the electrical poling invokes the ion migration within perovskite crystals, thus inducing a polarization potential, as substantiated by the surface potential change assessed by Kelvin probe force microscopy. Such electrical-poling-induced polarization potential is responsible for the markedly enhanced photocurrent and largely shortened response time. This work presents new insights into the electrical-poling-triggered ion migration and, in turn, polarization potential as well as into the implication of the latter for optoelectronic devices with greater performance. As such, the utilization of ion-migration-produced polarization potential may represent an important endeavor toward a wide range of high-performance perovskite-based photodetectors, solar cells, transistors, scintillators, etc.     

Etching characteristics of thin SiON films using a liquefied perfluorocarbon precursor of C6F12O with a low global warming potential

Perfluorocarbon gas is widely used in the semiconductor industry. However, perfluorocarbon has a negative effect on the global environment owing to its high global warming potential (GWP) value. An alternative solution is essential. Therefore, we evaluated the possibility of replacing conventional perfluorocarbon etching gases such as CHF₃ with C₆F₁₂O, which has a low GWP and is in a liquid state at room temperature. In this study, silicon oxynitride (SiON) films were plasma-etched using inductively coupled CF₄ +C₆F₁₂O+O₂ mixed plasmas. Subsequently, the etching characteristics of the film, such as etching rate, etching profile, selectivity over Si, and photoresist, were investigated. A double Langmuir probe was used and optical emission spectroscopy was performed for plasma diagnostics. In addition, a contact angle goniometer and x-ray photoelectron spectroscope were used to confirm the change in the surface properties of the etched SiON film surface. Consequently, the etching characteristics of the C₆F₁₂O mixed plasma exhibited a lower etching rate, higher SiON/Si selectivity, lower plasma damage, and more vertical etched profiles than the conventional CHF₃ mixed plasma. In addition, the C₆F₁₂O gas can be recovered in the liquid state, thereby decreasing global warming. These results confirmed that the C₆F₁₂O precursor can sufficiently replace the conventional etching gas.     

Quantifying co-creative writing experiences

Collaboration with artificial intelligence (AI) is a growing trend even in the field of creativity. This paper examines which quantitative metrics can be used to comparatively analyse human-computer co-creativity with children. To study this question, 24 schoolchildren of age 10–11 wrote a poem with three co-creative poetry writing processes: a human-computer, a human-human, and a human-human-computer process. The computational participant in the processes was an AI-based application called the Poetry Machine. The children were asked to evaluate their user experience with a 5-point Likert-type questionnaire after each writing process and a comparative questionnaire after finishing all processes. The metrics used in the evaluation were immediate fun, long-term enjoyment, creativity, self-expression, outcome satisfaction, ease of starting and finishing writing, quality of ideas and support from others, and ownership.

Significant differences were found in fun, long-term enjoyment, quality of ideas, support, and ownership. The high number of statistically relevant results was enabled by exposing all participants to all writing processes, and the comparative questionnaire. The human-human-computer process was evaluated the best in long-term enjoyment and the human-computer process the weakest in support and idea quality. Creativity and ease of finishing writing turned out to be outlining metrics for the co-creative processes.