726 research outputs found
SolvBERT for solvation free energy and solubility prediction: a demonstration of an NLP model for predicting the properties of molecular complexes
No full textData and Code for "SolvBERT for solvation free energy and solubility prediction: a demonstration of an NLP model for predicting the properties of molecular complexes" by Jiahui Yu, Chengwei Zhang, Yingying Cheng, Yun-Fang Yang, Yuan-Bin She, Fengfan Liu, Weike Su, and An Su</p
NCC_2024_Data
No full textRaw data for all figures in the manuscript by Ying Chen, Jian Zhang, Peng Gao, Changqing Yin, Jiahui Qian, Jin Liu, Xiao Wang, Changquan Cheng to be submitted to Chemical Geology.THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV
NCC_GCA_2024_Data
No full textRaw data for all figures in the manuscript by Ying Chen, Jian Zhang, Peng Gao, Changqing Yin, Jiahui Qian, Jin Liu, Xiao Wang, Changquan Cheng to be submitted to Geochimica et Cosmochimica Acta.THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV
Slimmable neural networks for edge devices
No full textWhile methods based on deep learning have witnessed major breakthroughs in machine perception and generative modeling, the problem of how to run neural networks within latency budget for edge devices remains unsolved. This thesis presents a new approach to train a single neural network executable at arbitrary widths for instant and adaptive accuracy-efficiency trade-offs at runtime.
First a simple and general method is presented to train a single neural network executable at different widths (number of channels in a layer). The width can be chosen from a predefined widths set to adaptively optimize accuracy-efficiency trade-offs at runtime. Instead of training individual networks with different width configurations, we train a shared network with switchable batch normalization. At runtime, the network can adjust its width on the fly according to on-device benchmarks and resource constraints, rather than downloading and offloading different models. Our trained networks, named slimmable neural networks, achieve ImageNet classification accuracy similar to (and in many cases better than) that of individually trained models of MobileNet v1, MobileNet v2, ShuffleNet and ResNet-50 at different widths. We also demonstrate better performance of slimmable models compared with individual ones across a wide range of applications including COCO bounding-box object detection, instance segmentation and person keypoint detection without tuning hyper-parameters. We visualize and discuss the learned features of slimmable networks.
Further, we propose a systematic approach to train universally slimmable networks (US-Nets), extending slimmable networks to execute at arbitrary width, and generalizing to networks both with and without batch normalization layers. In addition, we propose two improved training techniques for US-Nets, named the sandwich rule and the inplace distillation, to enhance training process and boost testing accuracy. We show improved performance of universally slimmable MobileNet v1 and MobileNet v2 on ImageNet classification task, compared with individually trained ones and 4-switch slimmable network baselines. We also evaluate the proposed US-Nets and improved training techniques on tasks of image super-resolution and deep reinforcement learning. Extensive ablation experiments on these representative tasks demonstrate the effectiveness of our proposed methods. Our discovery opens up the possibility to directly evaluate a FLOPs-Accuracy spectrum of network architectures. Finally, we demonstrate an application to search for channel number configurations based on proposed slimmable networks.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2021-05-01The student, Jiahui Yu, accepted the attached license on 2019-02-14 at 14:34.The student, Jiahui Yu, submitted this Thesis for approval on 2019-02-14 at 14:42.This Thesis was approved for publication on 2019-02-15 at 11:18.DSpace SAF Submission Ingestion Package generated from Vireo submission #13390 on 2019-08-22 at 16:19:49Made available in DSpace on 2019-08-23T20:44:31Z (GMT). No. of bitstreams: 2
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Previous issue date: 2019-02-15Embargo set by: Seth Robbins for item 112252
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Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemEmbargo set by: Seth Robbins for item 112252
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Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemEmbargo set by: Seth Robbins for item 112252
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Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemEmbargo set by: Seth Robbins for item 112252
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Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemLimited Restriction Lifted for Item 112252 on 2021-08-24T09:15:34Z
Estimating the effects of functional diversity and composition on the spatial variability of ecosystem multifunctionality in a large temperate forest region
No full textAbstract Functional diversity and composition have been shown to significantly influence the temporal variability of ecosystem functioning. However, their impact on the spatial variability of multiple ecosystem functions (multifunctionality) is still unknown. Therefore, this study aims to explore how functional diversity and composition affect the spatial variability of ecosystem multifunctionality (EMF-SV) under different environmental conditions in a temperate forest region. Regional communities representing specific spatial scales were established by assembling different numbers of sample plots. The EMF-SV was represented by the ratio of the standard deviation to the mean value of ecosystem multifunctionality within each regional community. Linear mixed-effects models were used to evaluate the effects of functional diversity and composition on the EMF-SV at different spatial scales. Structural equation models were applied to explore the direct and indirect pathways of functional diversity and composition influencing the EMF-SV. Our results show that functional diversity and composition had significant effects on the EMF-SV, and these effects changed with spatial scales and environmental conditions. They affected the EMF-SV directly or indirectly through species asynchrony and population stability. Our results demonstrate the role of functional traits in regulating the EMF-SV across spatial scales and explore the main impact mechanisms. This will contribute to our understanding and protection of ecosystem multifunctionality in temperate forests.the National Key R&D Program of Chinathe Program of National Natural Science Foundation of China http://dx.doi.org/10.13039/50110000180
Model-based myelin water fraction mapping: analyses and improvement
No full textIn this thesis, the problem of model-based myelin water fraction (MWF) mapping is addressed. We first focus on three of the most widely used signal models for T2*-myelin water imaging (MWI), i.e., the NNLS-multi-exponential model, the magnitude-3-exponential model, and the complex-3-exponential model, and investigate their sensitivities to practical perturbations such as random noise and field-related structured errors. We demonstrate through both Cramér-Rao lower bound (CRLB) analyses and Monte Carlo simulations that the three signal models are all very unstable inherently. Comparatively speaking, however, we demonstrate the theoretical advantage of the 3-exponential models over the multi-exponential model in handling noise, and the practical advantage of the magnitude models over the complex model in handling phase-related perturbations for T2*-MWI. We also illustrate the necessity and effects of incorporating various types of constraints for additional sensitivity gain.
Using the insights obtained in the sensitivity analyses, we then propose a new MWF fitting scheme that leverages an improved signal model and a set of more effective constraints. In particular, a relaxed magnitude-3-exponential model with additional frequency compensation terms is introduced to better represent voxels with large field variations; a set of statistical distributions learned from in vivo training data is further imposed on the model parameters for additional constraints. Using phantom simulation and in vivo experiments, we then evaluate and compare the proposed method with several popular conventional MWF fitting schemes to demonstrate the improved accuracy and robustness of the proposed method.
In this thesis, a literature review on the study of myelin and the development of MWF mapping is provided at the start of the work. Background materials on the CRLB theories are also provided to facilitate reading.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2022-12-01The student, Jiahui Xiong, accepted the attached license on 2020-11-17 at 12:52.The student, Jiahui Xiong, submitted this Thesis for approval on 2020-11-17 at 13:03.This Thesis was approved for publication on 2020-11-18 at 14:00.DSpace SAF Submission Ingestion Package generated from Vireo submission #15895 on 2021-03-04 at 16:31:59Made available in DSpace on 2021-03-05T21:45:32Z (GMT). No. of bitstreams: 2
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Previous issue date: 2020-11-18Embargo set by: Seth Robbins for item 117288
Lift date: 2023-03-05T21:45:47Z
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Microbial life-history strategies and genomic traits between pristine and cropland soils
No full textABSTRACT Microbial life-history strategies [inferred from ribosomal RNA operon ( rrn ) gene copy numbers] and associated genomic traits and metabolism potentials in soil significantly influence ecosystem properties and functions globally. Yet, the differences in microbial strategies and traits between disturbed (cropland) and pristine soils, along with their dominant driving factors, remain underexplored. Our large-scale survey of 153 sites, including 84 croplands and 69 pristine soils, combined with long-term field experiments demonstrates that cropland soils support microbial communities with more candidate r-strategies characterized by higher rrn copy numbers and genomic traits conducive to rapid resource utilization. Conversely, pristine soils tend to host communities aligned with more candidate K-strategies marked by high resource use potentials. Elevated nitrogen (N) and phosphorus (P) levels in cropland soils emerge as key factors promoting these candidate r-strategies, overshadowing the influence of organic carbon content, soil structure, or climatic conditions. Results from four long-term field experiments also corroborate that sustained N and P inputs significantly elevate rrn copy numbers, favoring these candidate r-strategists. Our findings highlight that land use and fertilization practices critically shape microbial life-history strategies, with nutrient availability being a decisive factor in increasing the r-strategists in cropland soils. IMPORTANCE Microbial life-history strategies and genomic traits are key determinants shaping the response of populations to environmental impacts. In this paper, 84 cropland and 69 pristine soil samples were studied, and microorganisms in two ecosystems were categorized into two types of ecological groups using the classical copiotroph–oligotroph dichotomy, promoting a general understanding of the ecological roles of microorganisms. This study is the first to investigate the microbial life-history strategies under different land uses across five climatic zones in China. The results showed that the microbes in cropland soils are more copiotrophic than pristine soils. It also demonstrates that elevated levels of nitrogen and phosphorus in cropland soils are the key factors promoting these r-strategies. This observation emphasizes the critical role of nutrient management in shaping microbial community dynamics and ecosystem functioning and lays the foundation for predicting the response of microbial community composition under resource perturbation.Microbial life-history strategies and genomic traits are key determinants shaping the response of populations to environmental impacts. In this paper, 84 cropland and 69 pristine soil samples were studied, and microorganisms in two ecosystems were categorized into two types of ecological groups using the classical copiotroph–oligotroph dichotomy, promoting a general understanding of the ecological roles of microorganisms. This study is the first to investigate the microbial life-history strategies under different land uses across five climatic zones in China. The results showed that the microbes in cropland soils are more copiotrophic than pristine soils. It also demonstrates that elevated levels of nitrogen and phosphorus in cropland soils are the key factors promoting these r-strategies. This observation emphasizes the critical role of nutrient management in shaping microbial community dynamics and ecosystem functioning and lays the foundation for predicting the response of microbial community composition under resource perturbation.ABSTRACT Microbial life-history strategies [inferred from ribosomal RNA operon ( rrn ) gene copy numbers] and associated genomic traits and metabolism potentials in soil significantly influence ecosystem properties and functions globally. Yet, the differences in microbial strategies and traits between disturbed (cropland) and pristine soils, along with their dominant driving factors, remain underexplored. Our large-scale survey of 153 sites, including 84 croplands and 69 pristine soils, combined with long-term field experiments demonstrates that cropland soils support microbial communities with more candidate r-strategies characterized by higher rrn copy numbers and genomic traits conducive to rapid resource utilization. Conversely, pristine soils tend to host communities aligned with more candidate K-strategies marked by high resource use potentials. Elevated nitrogen (N) and phosphorus (P) levels in cropland soils emerge as key factors promoting these candidate r-strategies, overshadowing the influence of organic carbon content, soil structure, or climatic conditions. Results from four long-term field experiments also corroborate that sustained N and P inputs significantly elevate rrn copy numbers, favoring these candidate r-strategists. Our findings highlight that land use and fertilization practices critically shape microbial life-history strategies, with nutrient availability being a decisive factor in increasing the r-strategists in cropland soils. IMPORTANCE Microbial life-history strategies and genomic traits are key determinants shaping the response of populations to environmental impacts. In this paper, 84 cropland and 69 pristine soil samples were studied, and microorganisms in two ecosystems were categorized into two types of ecological groups using the classical copiotroph–oligotroph dichotomy, promoting a general understanding of the ecological roles of microorganisms. This study is the first to investigate the microbial life-history strategies under different land uses across five climatic zones in China. The results showed that the microbes in cropland soils are more copiotrophic than pristine soils. It also demonstrates that elevated levels of nitrogen and phosphorus in cropland soils are the key factors promoting these r-strategies. This observation emphasizes the critical role of nutrient management in shaping microbial community dynamics and ecosystem functioning and lays the foundation for predicting the response of microbial community composition under resource perturbation.Microbial life-history strategies and genomic traits are key determinants shaping the response of populations to environmental impacts. In this paper, 84 cropland and 69 pristine soil samples were studied, and microorganisms in two ecosystems were categorized into two types of ecological groups using the classical copiotroph–oligotroph dichotomy, promoting a general understanding of the ecological roles of microorganisms. This study is the first to investigate the microbial life-history strategies under different land uses across five climatic zones in China. The results showed that the microbes in cropland soils are more copiotrophic than pristine soils. It also demonstrates that elevated levels of nitrogen and phosphorus in cropland soils are the key factors promoting these r-strategies. This observation emphasizes the critical role of nutrient management in shaping microbial community dynamics and ecosystem functioning and lays the foundation for predicting the response of microbial community composition under resource perturbation
DEVELOPMENT OF FLEXIBLE NEURAL INTERFACE AND NEROMUSCULAR MODEL AIMING AT NEUROPROSTHETIC APPLCATIONS
No full textPh.DDOCTOR OF PHILOSOPHY (FOE
Climate-energy modelling of urban housing stock transformation towards carbon neutral: A study of Taiyuan, China
No full text- …
