A comparative study on hygroscopic and physiochemical properties of chicken powders obtained by different drying methods

Abstract

Different drying methods (spray drying (SD), vacuum drying (VD), microwave vacuum drying (MVD), and infrared vacuum drying (IFVD)) were applied in order to compare the hygroscopicity behavior of chicken powders. The hygroscopicity curves and glass transition temperature were used to evaluate the influence of ambient humidity and temperature on moisture absorption of powders. The results showed that the chicken powder dried by MVD had the lowest moisture absorption, followed by IFVD, VD, and SD. The hygroscopicity of SD chicken powders was different from other three kinds of chicken powders due to the physical properties of particles and the changes of protein secondary structure as detected by the Fourier transform-infrared spectrometer. For the three vacuum drying methods, the difference of protein secondary structure was the main reason of differences in hygroscopicity. Although MVD chicken powders were slightly inferior to SD chicken powders in taste, MVD chicken powders were the best in terms of smell and color as suggested by instrumental sensory parameter evaluations. It was found that MVD had a positive effect on reducing moisture absorption and maintaining sensory quality of chicken powders.     

长走向平行钒铁矿体协同开采方案研究

七角井矿区的钒、铁双层矿体走向长度超4 km且呈近似平行产出，下盘铁矿开采时损失贫化率高且上盘钒矿资源保护难度大。根据钒铁矿体走向长、近平行产出、厚度负相关、空区隐患大的开采技术条件 特征，采用平面分区、开采时序规划、采矿方法优化、区域稳定性控制等技术来实现钒铁矿协同开采。根据铁矿“中间厚、两端薄”、钒矿“中间薄、两端厚”的形态特征，将长走向的钒铁矿体分为东区、中区及西 区。工程空间上，双层矿体共用一套开拓、采准、运输等开采系统；开采时序上，在提高铁矿生产能力的同时保证了钒矿开采的时间灵活性；采矿方法上，东区及西区铁矿采用阶段矿房嗣后膏体微胶结充填法，中区 铁矿采用阶段矿房法转崩落法；此外，通过中区崩落顶板及上盘围岩，东、西区膏体充填方式保证了矿区开采时及开采后的区域稳定性。研究表明：所提出的协同开采方案使矿山铁矿设计开采储量增加了1 064.7万t ，膏体充填每年消耗干抛层、尾矿等矿山固废86万t以上，矿山安全及经济效益明显。     

Simultaneous improvement of thermal conductivity and mechanical properties for mechanically mixed ABS/h-BN composites by using small amounts of hyperbranched polymer additives

Recently, thermal interface materials (TIMs) are in great demands for modern electronics. For mechanically mixed polymer composite TIMs, the thermal conductivity and the mechanical properties are generally lower than expected values due to the sharply increased viscosity and poor filler dispersion. This work shows that addition of a small amount of polyester-based hyperbranched polymer (HBP) avoided the trade-off in mechanically mixed ABS/hexagonal boron nitride (h-BN) composites. After adding 0.5 wt% HBP, the maximum h-BN content in the composites increased from 50 to 60 wt%. The out-of-plane, in-plane thermal conductivity, and tensile strength of ABS/h-BN with 50 wt% h-BN were 0.408, 0.517 W/mK, and 18 MPa, respectively, and were increased to 0.729, 0.847 W/mK, and 32 MPa by adding 0.5 wt% HBP, while 0.972, 1.12 W/mK, and 29.5 MPa were achieved for ABS/h-BN/HBP with 60 wt% h-BN. The morphological and rheological results proved that these enhancements are due to the improved h-BN dispersion by decreasing viscosity of composites during mixing. Theoretical modeling based on the modified effective medium theory confirmed such results and showed that the interfacial thermal resistance also decreased slightly. Thus, this work demonstrates a facile and scalable method for simultaneously improving the thermal conductivity and mechanical properties of thermoplastic-based TIMs.     

基于物联网的智慧林业可持续发展策略研究

随着我国科技的不断进步,在“互联网+”大数据的背景下,林业的智慧化发展是必经之路。虽然我国智慧林业的发展已经取得了一定的突破,但是仍然存在着许多问题。基于此,文章在物联网技术的基础上,对智慧林业的可持续发展策略进行探讨。     

iRGD-reinforced,photo-transformable nanoclusters toward cooperative enhancement of intratumoral penetration and antitumor efficacy

Nano Research - Insufficient intratumoral penetration greatly hurdles the anticancer performance of nanomedicine. To realize highly efficient tumor penetration in a precisely and spatiotemporally...     

Reconstructing gene regulatory networks with a memetic-neural hybrid based on fuzzy cognitive maps

Reconstructing gene regulatory networks (GRNs) plays an important role in identifying the complicated regulatory relationships, uncovering regulatory patterns in cells, and gaining a systematic view for biological processes. In order to reconstruct large-scale GRNs accurately, in this paper, we first use fuzzy cognitive maps (FCMs), which are a kind of cognition fuzzy influence graphs based on fuzzy logic and neural networks, to model GRNs. Then, a novel hybrid method is proposed to reconstruct GRNs from time series expression profiles using memetic algorithm (MA) combined with neural network (NN), which is labeled as MANN_FCM-GRN. In MANN_FCM-GRN, the MA is used to determine regulatory connections in GRNs and the NN is used to determine the interaction strength of the regulatory connections. In the experiments, the performance of MANN_FCM-GRN is validated on both synthetic data and the benchmark dataset DREAM3 and DREAM4. The experimental results demonstrate the efficacy of MANN_FCM-GRN and show that MANN_FCM-GRN can reconstruct GRNs with high accuracy without expert knowledge. The comparison with existing algorithms also shows that MANN_FCM-GRN outperforms ant colony optimization, non-linear Hebbian learning, and real-coded genetic algorithms.

     

MPE: a mobility pattern embedding model for predicting next locations

World Wide Web - The wide spread use of positioning and photographing devices gives rise to a deluge of traffic trajectory data (e.g., vehicle passage records and taxi trajectory data), with each...