Distribution of Bi–MnS Inclusions Existing in 1215MS Steels: Correlation with Thermal Physical Coefficient

Jian‑bo Xie,Bei‑bei Liu,Xiang‑yu Wu,Jian‑xun Fu 대한금속·재료학회 2022 METALS AND MATERIALS International Vol.28 No.5

This work aims to comprehensively summarize the types and distribution of the isolated Bi particles and MnS inclusions inthe Bi-bearing steels, to study the precipitated behavior of sulfide, and to study the effect of Bi particles on grain sizes andthe volume thermal expansion coefficients of the steels. Results show that the average percentage of the isolated Bi particles,semi-encapsulation, complete encapsulation, back-bridge, tiny encapsulation, cavity bridge Bi–MnS inclusions in the Bibearingsteels was 16.89%, 20.49%, 3.44%, 16.89%, 31.63%, 10.66%, respectively. The average equivalent diameters of thegrains in the 0 ppm, 130 ppm, 240 ppm, 760 ppm, 1200 ppm and 2300 ppm Bi content steels were 20.88, 20.17, 19.54, 18.13,13.98 and 13.25 μm, respectively. The precipitated equilibrium mass concentration product of the MnS (w[Mn]·w[S]) wascalculated to be 1.07, and the solid fraction fS value was 0.61. At 950 °C, the volume thermal expansion coefficient change(ΔVE) in 760 ppm Bi content steel was minimum 4 × 10–10%, while at 461.6 °C the ΔVE was maximum, 0.09%, which meansthat Bi affected the volume thermal expansion of the steel strongest in this temperature range.

Inter‑diffusion Based Analytical Model for Growth Kinetics of IMC Layers at Roll Bonded Cu/Al Interface During Annealing Process

Fu‑an Hua,Hong‑wu Song,Tao Sun,Jian‑ping Li 대한금속·재료학회 2020 METALS AND MATERIALS International Vol.26 No.3

A model based on inter-diffusion theory was established to predict growth kinetics of the intermetallic compounds (IMCs)formed in roll bonded Al/Cu sheets during annealing process. The model can give good prediction of both IMC layers growthkinetics and element concentration distribution at the interface of roll bonded Cu/Al sheets with different thickness underdifferent annealing conditions with certain roll reduction range. It is revealed that the calculated results of the proposedmodel are depended on the inter-diffusion coefficient of each components, which could be related to the interface bondingstate, i.e., bonding methods or rolling reductions for roll bonding. And there was big difference in inter-diffusion coefficientof Al and Cu matrix under different bonding state, while the inter-diffusion coefficient of IMCs changed slightly.

Disruption of ecdysis in Leptinotarsa decemlineata by knockdown of chitin deacetylase 1

Jian-Jian Wu,Li-Li Mu,Zhong-Chao Chen,Kai-Yun Fu,Wen-Chao Guo,Chao Li,Guo-Qing Li 한국응용곤충학회 2019 Journal of Asia-Pacific Entomology Vol.22 No.2

Chitin deacetylases (CDAs) catalyze N-deacetylation of chitin, a crucial process for chitin modification. In the present paper, LdCDA1 was identified in Leptinotarsa decemlineata. It was copiously expressed in larval foregut, hindgut and epidermis. Just before the molt in the first, second and third larval instars, the mRNA levels of LdCDA1 were high. In the fourth (final)-instar larvae, a peak occurred 4 days after ecdysis. In vivo results revealed that LdCDA1 transcriptionally responded, positively and negatively respectively, to 20-hydroxyecdysone and juvenile hormone titers. Moreover, knockdown of LdCDA1 significantly reduced foliage consumption, lengthened developing period and prevented growth in the final instar larvae. Three distinct lethal phenotypes were noted in the LdCDA1 RNAi larvae. About 30% of the RNAi larvae became moribund and finally died; approximately 50% of deformed pupae died as pharate adults; and around 20% of LdCDA1 depleted pupae finally emerged as abnormal adults and eventually died within 1 week after emergence. Furthermore, chitin content was low and the mRNA levels of five chitin biosynthesis transcripts (LdUAP1, LdUAP2, LdChSAa, LdChSAb and LdChSB) were significantly declined in the LdCDA1 RNAi larvae. In addition, glucose, trehalose and glycogen contents were increased in the LdCDA1 depleted hypomorphs, along with highly expressed genes coding for trehalose and glycogen synthesis enzymes. The findings provide a compelling piece of evidence that CDA1 is critical for chitin deposition in L. decemlineata. Moreover, LdCDA1 may be a potential target for control of the larvae.

The Prediction Research of Population Density Based on Deep Learning in Grain Stored Insects

Wu Jian-Jun,Dang Hao,Li Miao,Sun Fu-Yan,Zhu Yu-Hua,Zhen Tong,Zou Bing-Qiang 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.10

Precision of pests, in stored grain insect population density, has been a hot and difficult research in pest detection and control system. The accuracy of prediction of pest density will directly affect to warehouse grain temperature and the food quality etc. In order to improve the accuracy, the paper which using the depth study method, established an insects density prediction mode with the depth of the belief network as the core. The model is applied to the algorithm of deep learning predictive control. According to the temperature and humidity of the grain obtained from the actual measurement and the initial density of the pest, we predicted the pest density. Simulation results show that the root mean square error is small between the predictive value and actual value, high prediction accuracy. The deep learning algorithm is applied to the population density of pests is effective.

Analysis of Volatile Compounds of Jasmine Scented Tea during the Orthodox Manufacturing Process Using HS-SPME/GC-MS

Jian Lu,De-Jun Fu,Dong-Fen Wu,Yu Liu,Yao-Ping Luo 한국차학회 2015 한국차학회지 Vol.- No.S

Volatile components of jasmine-scented tea during the orthodox manufacturing process were extracted using Headspace solid-phase microextraction (HS-SPME) and the major flavor compounds were identified by Gas chromatography-mass spectrometry/Retention indices (GC-MS/RI). The major volatile compounds extracted by SDE could also be obtained by HS-SPME, which appears more suitable for extraction of aromatic compounds, for its advantages of simplicity and convenience. The GC-MS chromatograms of tea samples showed that the aromatic constituents of jasmine tea had been identified in composition after 1st scenting, which contained 6 apparently high peaks representing linalool, benzyl acetate, α-farnesene, (Z)-3-hexenyl benzoate, methyl anthranilate, and indole. According to the change of peak area of major volatile compounds, (Z)-3-hexenyl acetate and (Z)-3-hexenyl butyrate with green grass aroma reduced by 71.13% and 63.10% respectively in jasmine tea product, while 7 compounds with favorable flowery fruity aroma-benzyl acetate, (Z)-3-hexenyl benzoate, linalool, benzyl alcohol, α-farnesene, methyl anthranilate and indole- increased by 17.84%, 28.33 times, 32.49%, 1.70 times, 6.67 times, 11.84 times and 21.48 times respectively, comparing to the base tea. Besides, nerolidol (fruity-flowery) and germacrene D (woody), not detected in the base tea also gradually increased. The quality grade of jasmine tea was potentially correlated to the ratio of peak area of the 9 favorable compounds to that of the 2 grass compounds. After 1st scenting, the peak areas of compounds from jasmine flower increased by 1.81×105-18.24×105, and decreased by 36.14%-69.95% after the 1st drying. The peak areas of some components detected in both the base tea and jasmine flowers, like (Z)-3-hexenyl acetate and methyl salicylate, increased by 9.05%-57.60% of those of the base tea after 1st scenting, and lost more than 100% after the 1st drying, while the increased peak areas of some other components both detected, like α-farnesene and indole, were more than peak areas of the base tea, with 30%- 95% loss after the 1st drying. The content change tendency of volatiles during 2nd scenting and the 2nd drying were consistent with those during 1st scenting and the 1st drying. After raising fragrance, the contents of some low boiling point volatiles and compounds not detected in the base tea increased.

MFMAP: Learning to Maximize MAP with Matrix Factorization for Implicit Feedback in Recommender System

( Jianli Zhao ),( Zhengbin Fu ),( Qiuxia Sun ),( Sheng Fang ),( Wenmin Wu ),( Yang Zhang ),( Wei Wang ) 한국인터넷정보학회 2019 KSII Transactions on Internet and Information Syst Vol.13 No.5

Traditional recommendation algorithms on Collaborative Filtering (CF) mainly focus on the rating prediction with explicit ratings, and cannot be applied to the top-N recommendation with implicit feedbacks. To tackle this problem, we propose a new collaborative filtering approach namely Maximize MAP with Matrix Factorization (MFMAP). In addition, in order to solve the problem of non-smoothing loss function in learning to rank (LTR) algorithm based on pairwise, we also propose a smooth MAP measure which can be easily implemented by standard optimization approaches. We perform experiments on three different datasets, and the experimental results show that the performance of MFMAP is significantly better than other recommendation approaches.

Selective Removal of Al(III) from Rare Earth Solutions Using Peas-based Activated Carbon

Fu-Qiang An,Rui-Yan Wu,Zhi-Guo Yuan,Tuo-Ping Hu,Jian-Feng Gao 대한화학회 2017 대한화학회지 Vol.61 No.5

Efficiently removing Al(III) from rare earth is very significant because even trace amount of Al(III) can cause serious harm to the rare earth materials. In this paper, a nitrogen-containing activated carbon, AC-P700, was synthesized using peas as raw materials. The AC-P700 was characterized by surface area analyzer, FT-IR, and XPS methods. The adsorption and recognition properties of AC-P700 towards Al(III) were investigated, and the recognition mechanism was also analyzed. The BET special surface area of AC-P700 was 1277.1 m2·g−1, and the average pore diameter was 1.90 nm. The AC-P700 possesses strong adsorption affinity and excellent recognition selectivity towards Al(III). The adsorption capacity for Al(III) could reach to 0.53 mmol·g−1, and relative selectivity coefficients relative to La(III) and Ce(III) is 9.6 and 8.7, respectively. Besides, ACP700 possesses better regeneration ability and reusability.

Selective Removal of Al(III) from Rare Earth Solutions Using Peas-based Activated Carbon

An, Fu-Qiang,Wu, Rui-Yan,Li, Min,Yuan, Zhi-Guo,Hu, Tuo-Ping,Gao, Jian-Feng Korean Chemical Society 2017 대한화학회지 Vol.61 No.5

Efficiently removing Al(III) from rare earth is very significant because even trace amount of Al(III) can cause serious harm to the rare earth materials. In this paper, a nitrogen-containing activated carbon, AC-P700, was synthesized using peas as raw materials. The AC-P700 was characterized by surface area analyzer, FT-IR, and XPS methods. The adsorption and recognition properties of AC-P700 towards Al(III) were investigated, and the recognition mechanism was also analyzed. The BET special surface area of AC-P700 was $1277.1m^2{\cdot}g^{-1}$, and the average pore diameter was 1.90 nm. The AC-P700 possesses strong adsorption affinity and excellent recognition selectivity towards Al(III). The adsorption capacity for Al(III) could reach to $0.53mmol{\cdot}g^{-1}$, and relative selectivity coefficients relative to La(III) and Ce(III) is 9.6 and 8.7, respectively. Besides, AC-P700 possesses better regeneration ability and reusability.

Decentralized Iterative Learning Control for Large-Scale Interconnected Linear Systems with Fixed Initial Shifts

Qin Fu,Pan-Pan Gu,Jian-Rong Wu 제어·로봇·시스템학회 2017 International Journal of Control, Automation, and Vol.15 No.5

This paper deals with the problem of iterative learning control for large-scale interconnected linear systemsin the presence of fixed initial shifts. According to the characteristics of the systems, iterative learning controllaws are proposed for such large-scale interconnected linear systems based on the PD-type learning schemes. Theproposed controller of each subsystem only relies on local output variables without any information exchanges withother subsystems. Using the contraction mapping method, we show that the schemes can guarantee the output ofthe system converges uniformly to the corresponding output limiting trajectory over the whole time interval alongthe iteration axis. Simulation examples illustrate the effectiveness of the proposed method.

Iterative Learning Control for a Class of Mixed Hyperbolic-parabolic Distributed Parameter Systems

Qin Fu,Wei-Guo Gu,Pan-Pan Gu,Jian-Rong Wu 제어·로봇·시스템학회 2016 International Journal of Control, Automation, and Vol.14 No.6

This paper deals with the problem of iterative learning control algorithm for a class of mixed distributedparameter systems. Here, the considered distributed parameter systems are composed of mixed hyperbolicparabolicpartial differential equations. The domain of the system is divided into two parts in which the system ishyperbolic and parabolic, respectively, with transmission conditions at the interface. According to the characteristicsof the systems, iterative learning control laws are proposed for such mixed hyperbolic-parabolic distributedparameter systems based on P-type learning scheme. Using the contraction mapping method, it is shown that thescheme can guarantee the output tracking errors on L2 space converge along the iteration axis. A simulation exampleillustrates the effectiveness of the proposed method.