Synthesis of nanopowders with low agglomeration by elaborating Φ values for producing Gd2O3-MgO nanocomposites with extremely fine grain sizes and high mid-infrared transparency

Refining ceramic microstructures to the nanometric range to minimize light scattering provides an interesting methodology for developing novel optical ceramic materials. In this work, we reported the fabrication and properties of a new nanocomposite optical ceramic of Gd₂O₃-MgO. The citric acid sol-gel combustion method was adopted to fabricate Gd₂O₃-MgO nanocomposites with fine-grain sizes, dense microstructures and homogeneous phase domains. Nanopowders with low agglomeration and improved sinterability can be obtained by elaborating Φ values. Further refining of the microstructure of the nanocomposites was achieved by elaborating the hot-pressing conditions. The sample sintered at 65 MPa and 1300 °C showed a quite high hardness value of 14.3 ± 0.2 GPa, a high transmittance of 80.3 %–84.7 % over the 3?6 μm wavelength range, due mainly to its extremely fine-grain size of Gd₂O₃ and MgO (93 and 78 nm, respectively) and high density.     

Hydrogen Production from Catalytic Steam Reforming of Bio-Oils: A Critical Review

In the future, hydrogen will be an important energy carrier and industrial raw material. Catalytic steam reforming of bio-oils is a promising and economically viable technology for hydrogen production. However, during the reforming process, the catalysts are rapidly deactivated due to coke formation and sintering. Thus, maintaining the activity and stability of catalysts is the key issue in this process. Optimized operation conditions could extend the catalyst lifetime by affecting the coke morphology or promoting coke gasification. This article summarizes the recent developments in the field of catalytic steam reforming of bio-oils, focusing on the operation conditions, the properties of the catalysts, and the effects of the catalyst supports. The expected insights into the catalytic steam reforming of bio-oils will provide further guidance for hydrogen production from bio-oils.     

面向医院建筑项目的IPD模式应用研究

医院建筑项目是非常复杂且具有挑战性的建设项目。传统的交付模式无法满足人们对医院建筑建设、运营方面的高要求,为此开展面向医院建筑项目的IPD模式应用研究。在对IPD模式发展现状整理的基础上,阐述医院建筑项目IPD模式的适用性。分析采用IPD模式的医院建筑项目特点,并以上海市某公立三甲专科医院项目为例,对IPD模式在国内的应用进行探索性研究。     

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.

     

Chemotherapy response of pancreatic cancer by diffusion-weighted imaging (DWI) and intravoxel incoherent motion DWI (IVIM-DWI) in an orthotopic mouse model

Magnetic Resonance Materials in Physics, Biology and Medicine - To investigate the value of using diffusion-weighted imaging (DWI) and intravoxel incoherent motion DWI (IVIM-DWI) to assess the...     

亲子乐园空调送风方式的数值模拟研究

大型综合室内亲子乐园属于高大空间,设有游乐设施和游戏的特殊性使得对空间的舒适性要求一致,但是送风气流遇阻严重,室内存在较多气流死角,影响室内空气质量和儿童健康。因此其空调设计不仅需要考虑温度、风速的空间均匀度,还要考虑各点的空气龄和PMV-PPD指标。以天津某亲子乐园为研究对象,利用scSTREAM软件对适用于该房间的辐射供冷加新风、置换通风、混合通风三种空调方式的送风效果进行数值模拟分析,从流场的均匀性、人员的热舒适性等方面对模拟结果进行探讨,研究结果表明辐射供冷加新风方式的空间均匀性和PMV指标最佳,混合通风方式的空气龄最小。     

Precise Extraction of Charge Carrier Mobility for Organic Transistors

Unreliable mobility values, and particularly greatly overestimated values and severely distorted temperature dependences, have recently hampered the development of the organic transistor field. Given that organic field‐effect transistors (OFETs) have been routinely used to evaluate mobility, precise parameter extraction using the electrical properties of OFETs is thus of primary importance. This review examines the origins of the various mobilities that must be determined for OFET applications, the relevant extraction methods, and the data selection limitations, which help in avoiding conceptual errors during mobility extraction. For increased precision, the review also discusses device fabrication considerations, calibration of both the specific gate‐dielectric capacitance and the threshold voltage, the contact effects, and the bias and temperature dependences, which must actually be handled with great care but have mostly been overlooked to date. This review serves as a systematic overview of the OFET mobility extraction process to ensure high precision and will also aid in improving future research.