296 research outputs found
Hydrophobic Targeting Ligand Modified Polyethyleneimine for Hepatic Cancer Gene Therapy
No full text<p>Mingzhuo Cao <sup>1,2*</sup>, Yong Gao <sup>3</sup>, Mengling Zhan<sup>2</sup>, Nasha Qiu <sup>1</sup>, Ying Piao<sup>1</sup>, Zhuxian Zhou<sup>1</sup>, Youqing Shen <sup>1</sup></p>
<p><sup>1</sup> Center for Bio-nanoengineering and Key Laboratory of Biomass Chemical Engineering, Ministry of Education, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027, China;</p>
<p><sup>2</sup> Scientific Research and Experimental Center, Henan University of Chinese Medicine, Zhengzhou, 450058, China.</p>
<p><sup>3</sup> Henan province food and drug Administration, Food and Drug Evaluation and Inspection Center, Zhengzhou, 450018, China.</p>
<p><strong>*</strong> Corresponding Author: Mingzhuo Cao, E-mail: <a href="mailto:[email protected]">[email protected]</a></p>
Water requirement for biorefinery to meet the renewable fuel standard in the contiguous United States
No full textRenewable biofuel production requires a considerable amount of water for biofuel conversion. However, it is still unclear how much water is needed in the Contiguous United States (CONUS) to convert feedstocks to biofuels and the associated impacts on local water availabilities. This study addresses this issue with the most up-to-date data of feedstock, water availability, and water requirements for biorefinery technologies. The multi-faceted nature of biofuel development, including feedstock production, water availability, transportation cost, biorefinery capacity, and biorefinery benefits and costs, is addressed through the delineation of a basic analysis unit: biorefinery planning boundary (RPB). The result suggests the total biorefinery water use in 2030 accounts for less than 0.01% of the total water availability in the CONUS. However, local water issues are found, especially in the Great Plains RPBs where biorefinery would consume up to 100% of the local water availabilities. This high level of water consumption shows possible pressures on local water use, water infrastructure, and water price. If a constraint on water consumption is imposed for biorefineries, up to 1.2 billion Gallon/year cellulosic biofuel production (7.5% of the renewable fuel standard mandated amount) will be affected. The total affected cellulosic biofuel production correlates strongly with the water use constraint when the biomass price is higher than $50/dry ton (dt), but such correlation diminishes as the biomass price becomes lower. Findings from this study will be beneficial for the sustainable planning of biofuel production.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2023-08-01The student, Ximin Piao, accepted the attached license on 2021-07-08 at 15:42.The student, Ximin Piao, submitted this Thesis for approval on 2021-07-08 at 15:44.This Thesis was approved for publication on 2021-07-11 at 08:58.DSpace SAF Submission Ingestion Package generated from Vireo submission #16809 on 2022-01-12 at 13:04:13Made available in DSpace on 2022-01-12T22:55:00Z (GMT). No. of bitstreams: 2
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Luan shi jia ren.
No full text王光鼐編劇.據美國密西爾的《飄》改編.Play.Wang Guangnai bian ju.Ju Meiguo Mixier de "Piao" gai bian
초고 변형률속도에서의 금속재료의 경화거동 및 파단특성에 관한 연구
No full text학위논문(박사) - 한국과학기술원 : 기계공학과, 2017.8,[viii, 135 p. :]This dissertation is concerned with the dynamic hardening and fracture behaviors of metallic materials at a wide range of strain rates from /s to /s. The main outcomes of this dissertation are: (i) experiments to obtain hardening behaviors and fracture strains at a wide range of strain rates from /s to /s and temperatures from 25 to 200(ii) consideration of thermal softening effect at various strain rates due to large plastic deformation(iii) development of a rate and temperature dependent constitutive model to describe strain rate hardening and thermal softening behaviors(iv) investigation of a novel systematic procedure to calibrate hardening behaviors at ultra-high strain rates ranging from /s to /s where hardening behaviors are difficult to acquire from conventional experiments(v) development of a strain rate dependent fracture criterion which can decently estimate experiment results at various strain rates and loading pathsand (vi) prediction of sequential deformed shapes and fractured shapes of projectiles from Taylor impact tests for different metallic materials.한국과학기술원 :기계공학과
Zai zhong he piao yi ya suo shi yan zhong de mai chong chang du suo jian yu zai shi yan ceng mian shang de li zi shu zong xiang can shu de tao lun
No full textShih, Kai = 在中和漂移壓縮實驗中的脈衝長度縮減與在實驗層面上的粒子束縱向參數的討論 / 師愷.Thesis M.Phil. Chinese University of Hong Kong 2014.Includes bibliographical references (leaves 94-96).Abstracts also in Chinese.Title from PDF title page (viewed on 27, September, 2016).Shih, Kai = Zai zhong he piao yi ya suo shi yan zhong de mai chong chang du suo jian yu zai shi yan ceng mian shang de li zi shu zong xiang can shu de tao lun / Shi Kai
SensiMix: Sensitivity-Aware 8-bit index & 1-bit value mixed precision quantization for BERT compression
No full text© 2022 Piao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Given a pre-trained BERT, how can we compress it to a fast and lightweight one while maintaining its accuracy? Pre-training language model, such as BERT, is effective for improving the performance of natural language processing (NLP) tasks. However, heavy models like BERT have problems of large memory cost and long inference time. In this paper, we propose SENSIMIX (Sensitivity-Aware Mixed Precision Quantization), a novel quantizationbased BERT compression method that considers the sensitivity of different modules of BERT. SENSIMIX effectively applies 8-bit index quantization and 1-bit value quantization to the sensitive and insensitive parts of BERT, maximizing the compression rate while minimizing the accuracy drop. We also propose three novel 1-bit training methods to minimize the accuracy drop: Absolute Binary Weight Regularization, Prioritized Training, and Inverse Layer-wise Fine-tuning. Moreover, for fast inference, we apply FP16 general matrix multiplication (GEMM) and XNOR-Count GEMM for 8-bit and 1-bit quantization parts of the model, respectively. Experiments on four GLUE downstream tasks show that SENSIMIX compresses the original BERT model to an equally effective but lightweight one, reducing the model size by a factor of 8× and shrinking the inference time by around 80% without noticeable accuracy drop.N
Divergence of climate impacts on maize yield in Northeast China
No full textNortheast China (NEC), the most productive maize growing area in China, has experienced pronounced climate change. However, the impacts of historical climate changes on maize production and their spatial variations remain uncertain. In this study, we used yield statistics at prefecture scale over the past three decades, along with contemporary climate data, to explore the yield-climate relationship and its spatial variations. At the regional scale, maximum and minimum temperature changes had opposite impacts on maize yield, which increased by 10.0 +/- 7.7% in response to a 1 degrees C increase in growing season mean daily minimum temperature (T-min), but decreased by 13.4 +/- 7.1% in response to a 1 degrees C increase in growing season mean daily maximum temperature (T-max). Variations in precipitation seemed to have small impacts on the maize yield variations (-0.9 +/- 5.2%/100 mm). However, these responses of maize yield to climate variations were subject to large spatial differences in terms of both the sign and the magnitude. similar to 30% of the prefectures showed a positive response of maize yield to rising T-max, which was in contrast to the negative response at the regional scale. Our results further indicate that the spatial variations in the yield response to climate change can be partly explained by variations in local climate conditions. The growing season mean temperature was significantly correlated with the response of maize yield to T-max (R= -0.67, P < 0.01), which changes from positive to negative when the growing season mean temperature exceeds 17.9 +/- 0.2 degrees C. Precipitation became the dominant climatic factor driving maize yield variations when growing season precipitation was lower than similar to 400 mm, but had a weaker influence than temperature over most of the study area. We conclude that, although NEC is a region spanning only more than one millions of kilometer squares, the divergence of the yield response to climatic variations highlights the need to analyze the yield-climate relationship at fine spatial scales. (C) 2014 Elsevier B.V. All rights reserved.Agriculture, MultidisciplinaryEcologyEnvironmental SciencesSCI(E)[email protected]
Characterization of Hardening Behaviors for 4130 Steel, OFHC Copper, and Ti6Al4V Alloy at High Strain Rate and High Temperature
No full text- …
