科研成果 by Year: 2021

2021
Tan Z, Wang H, Lu K, Dong HB, Liu Y, Zeng L, Hu M, Zhang Y. An Observational Based Modeling of the Surface Layer Particulate Nitrate in the North China Plain During Summertime. Journal of Geophysical Research: Atmospheres. 2021;126.
Zhang C, Song Y, Wang H, Zeng L, Hu M, Lu K, Xie S, Carter W. Observation-Based Estimations of Relative Ozone Impacts by Using Volatile Organic Compounds Reactivities. Environmental Science & Technology Letters. 2021.
Yang X, Lu K, Ma X, Liu Y, Wang H, Hu R, Li X, Lou S, Chen S, Dong HB, et al. Observations and modeling of OH and HO2 radicals in Chengdu, China in summer 2019. Science of the Total Environment [Internet]. 2021;772. 访问链接
Liu YJ, Misztal PK, Arata C, Weschler CJ, Nazaroff WW, Goldstein AH. Observing ozone chemistry in an occupied residence. Proceedings of the National Academy of Sciences [Internet]. 2021;118:e2018140118. 访问链接Abstract
It has been suggested that indoor exposure to ozone oxidation products contributes materially to the apparent associations between outdoor ozone concentration and morbidity and mortality. Our current understanding of indoor ozone chemistry derives mainly from studies with test surfaces under controlled conditions. Little is known about the overall impact of ozone chemistry on air composition in dynamically changing indoor residential environments. The results presented here reflect a quantitative characterization of overall indoor ozone chemistry in a normally occupied home. Findings reveal a strong influence of off-body skin lipids on indoor ozone chemistry. Being able to elucidate indoor air pollutants derived from ozone chemistry facilitates the investigation of causal links between outdoor ozone concentrations and adverse health effects.Outdoor ozone transported indoors initiates oxidative chemistry, forming volatile organic products. The influence of ozone chemistry on indoor air composition has not been directly quantified in normally occupied residences. Here, we explore indoor ozone chemistry in a house in California with two adult inhabitants. We utilize space- and time-resolved measurements of ozone and volatile organic compounds (VOCs) acquired over an 8-wk summer campaign. Despite overall low indoor ozone concentrations (mean value of 4.3 ppb) and a relatively low indoor ozone decay constant (1.3 h−1), we identified multiple VOCs exhibiting clear contributions from ozone-initiated chemistry indoors. These chemicals include 6-methyl-5-hepten-2-one (6-MHO), 4-oxopentanal (4-OPA), nonenal, and C8-C12 saturated aldehydes, which are among the commonly reported products from laboratory studies of ozone interactions with indoor surfaces and with human skin lipids. These VOCs together accounted for ≥12% molecular yield with respect to house-wide consumed ozone, with the highest net product yield for nonanal (≥3.5%), followed by 6-MHO (2.7%) and 4-OPA (2.6%). Although 6-MHO and 4-OPA are prominent ozonolysis products of skin lipids (specifically squalene), ozone reaction with the body envelopes of the two occupants in this house are insufficient to explain the observed yields. Relatedly, we observed that ozone-driven chemistry continued to produce 6-MHO and 4-OPA even after the occupants had been away from the house for 5 d. These observations provide evidence that skin lipids transferred to indoor surfaces made substantial contributions to ozone reactivity in the studied house.All study data are included in the article and supporting information.
Zhang Y, Li J, Lei Y, Yang T, Li Z, Zhang G, Cui B. On-Off Sketch: A Fast and Accurate Sketch on Persistence, in Proceedings of the VLDB Endowment. VLDB Endowment; 2021.
Ding J, Yu Z*, Tian YH*, Huang T. Optimal ANN-SNN Conversion for Fast and Accurate Inference in Deep Spiking Neural Networks, in Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI).; 2021:2328-2336. PDFAbstract
Spiking Neural Networks (SNNs), as bio-inspired energy-efficient neural networks, have attracted great attentions from researchers and industry. The most efficient way to train deep SNNs is through ANN-SNN conversion. However, the conversion usually suffers from accuracy loss and long inference time, which impede the practical application of SNN. In this paper, we theoretically analyze ANN-SNN conversion and derive sufficient conditions of the optimal conversion. To better correlate ANN-SNN and get greater accuracy, we propose Rate Norm Layer to replace the ReLU activation function in source ANN training, enabling direct conversion from a trained ANN to an SNN. Moreover, we propose an optimal fit curve to quantify the fit between the activation value of source ANN and the actual firing rate of target SNN. We show that the inference time can be reduced by optimizing the upper bound of the fit curve in the revised ANN to achieve fast inference. Our theory can explain the existing work on fast reasoning and get better results. The experimental results show that the proposed method achieves near loss-less conversion with VGG-16, PreActResNet-18, and deeper structures. Moreover, it can reach 8.6× faster reasoning performance under 0.265× energy consumption of the typical method. The code is available at https://github.com/DingJianhao/OptSNNConvertion-RNL-RIL.
Liu Z, Ying H, Chen M, Bai J, Xue Y, Yin Y, Batchelor WD, Yang Y, Bai Z, Du M, et al. Optimization of China’s maize and soy production can ensure feed sufficiency at lower nitrogen and carbon footprints. Nature Food [Internet]. 2021;2:426–433. pdfAbstract
China purchases around 66% of the soy that is traded internationally. This strains the global food supply and contributes to greenhouse gas emissions. Here we show that optimizing the maize and soy production of China can improve its self-sufficiency and also alleviate adverse environmental effects. Using data from more than 1,800 counties in China, we estimate the area-weighted yield potential (Ypot) and yield gaps, setting the attainable yield (Yatt) as the yield achieved by the top 10% of producers per county. We also map out county-by-county acreage allocation and calculate the attainable production capacity according to a set of sustainability criteria. Under optimized conditions, China would be able to produce all the maize and 45% of the soy needed by 2035—while reducing nitrogen fertilizer use by 26%, reactive nitrogen loss by 28% and greenhouse gas emissions by 19%—with the same acreage as 2017, our reference year.
Jiang X, Han Y, Qiu X, Chai Q, Zhang H, Chen X, Cheng Z, Wang Y, Fan Y, Xue T, et al. Organic Components of Personal PM2.5 Exposure Associated with Inflammation: Evidence from an Untargeted Exposomic Approach. Environmental Science & TechnologyEnvironmental Science & Technology. 2021;55:10589-10596.
Shi X, Qiu X, Chen Q, Chen S, Hu M, Rudich Y, Zhu T. Organic Iodine Compounds in Fine Particulate Matter from a Continental Urban Region: Insights into Secondary Formation in the Atmosphere. Environmental Science & Technology. 2021;55:1508-1514.
Wu B, Sun J, Huang Q, Yuan X. Overlapped grouping measurement: A unified framework for measuring quantum states. arXiv preprint arXiv:2105.13091. 2021.
Jie L, TANG X, Liu J, Shen L, Li S, Sun N, Flynn MP. An Overview of Noise-Shaping SAR ADC: From Fundamentals to the Frontier. IEEE Open Journal of the Solid-State Circuits Society. 2021;1:149-161.Abstract
The Noise-Shaping (NS) SAR is an attractive new ADC architecture that emerged in the last decade. It combines the advantages of the SAR and the DSM architectures. NS SAR shows excellent potential for high efficiency and low cost, and is highly suited to process scaling. This paper gives an overview of the history of NS-SAR, reviews the fundamentals challenges, and summarizes the latest developments, including advanced loop filtering techniques, DAC mismatch mitigation, kT/C mitigation, and bandwidth boosting. A comprehensive comparison of the state-of-the-art NS-SAR ADCs is provided, and conclusions are derived.
Ma J, Chen L, Liu Y, Xu T, Ji H, Duan J, Sun F, Liu W. Oxygen defective titanate nanotubes induced by iron deposition for enhanced peroxymonosulfate activation and acetaminophen degradation: Mechanisms, water chemistry effects, and theoretical calculation. Journal of Hazardous Materials [Internet]. 2021;418:126180. 访问链接Abstract
The large consumption of acetaminophen (APAP) worldwide and unsatisfactory treatment efficiencies by conventional wastewater treatment processes give rise to the seeking of new technology for its effective removal. Herein, we proposed a facile one-step hydrothermal method to synthesize defective iron deposited titanate nanotubes (Fe/TNTs) for peroxymonosulfate (PMS) activation and APAP degradation. The retarded first-order reaction rate of APAP degradation by Fe/TNTs was 5.1 times higher than that of neat TNTs. Characterizations indicated iron deposition effectively induced oxygen vacancies and Ti3+, facilitating the electrical conductivity and PMS binding affinity of Fe/TNTs. Besides, oxygen vacancies could act as an electron mediator through PMS activation by iron. Moreover, the formation of Fe–O–Ti bond facilitated the synergistic redox coupling between Fe and Ti, further enhancing the PMS activation. SO4•− was the major radical, causing C–N bond cleavage and decreasing the overall toxicity. In contrast, APAP degradation by neat TNTs-PMS system mainly works through nonradical reaction. The Fe/TNTs activated PMS showed desired APAP removal under mild water chemistry conditions and good reusability. This work is expected to expand the potential application of titanate nanomaterials for PMS activation, and shed light on facile synthesis of oxygen defective materials for sulfate-radical-based advanced oxidation processes.
Fan C, Meng Y, Sun X, Wu F, Zhang T, Li J. Parameter Estimation for the SEIR Model Using Recurrent Nets. arXiv preprint arXiv:2105.14524. 2021.
Fan C, Tian Y, Meng Y, Peng N, Sun X, Wu F, Li J. Paraphrase Generation as Unsupervised Machine Translation. arXiv preprint arXiv:2109.02950. 2021.
Ge Z, Li L, Qu T. Partially Matching Projection Decoding Method Evaluation Under Different Playback Conditions. IEEE/ACM Transactions on Audio, Speech, and Language Processing. 2021;29:1411-1423.
Zong T, Wang H, Wu Z, Lu K, Wang Y, Zhu Y, Shang D, Xin F, HUANG X, He L, et al. Particle hygroscopicity inhomogeneity and its impact on reactive uptake. Science of The Total Environment. 2021:151364.
Liu Y, Meng X, Wu Z, Huang D, Wang H, Chen J, Chen J, Zong T, Fang X, Tan T, et al. The particle phase state during the biomass burning events. Science of the Total EnvironmentScience of the Total Environment. 2021;792.
Li Y, Chen Y, Sandanov D, Luo A, Lyv T, Su X, Liu Y, Wang Q, Chepinoga V, Dudov S, et al. Patterns and environmental drivers of Ranunculaceae species richness and phylogenetic diversity across eastern Eurasia. Biodiversity ScienceBiodiversity Science. 2021;29:561-574.Abstract
<p id="C2"><strong>Aims:</strong> Ranunculaceae, one of the basal clades in eudicots of angiosperms, has a variety of medicinal plants and is of high conservation value. However, large-scale patterns in species richness and phylogenetic diversity of Ranunculaceae based on high-resolution distribution data and their environmental determinants remain poorly understood. We aims to: (1) establish a Ranunculaceae distribution database in eastern Eurasia, estimate the species diversity and phylogenetic diversity pattern of different life forms, and explore the formation mechanism of the pattern; (2) analysis the relationship between species diversity and phylogenetic diversity of Ranunculaceae, and determine the diversity hot spots to provide basis for Ranunculaceae conservation planning.<br><strong>Methods:</strong> Here, we established the first species distribution database for 1,688 Ranunculaceae species across eastern Eurasia by compiling distribution data from regional and local floral records from across China, Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, Uzbekistan, Mongolia, and Russia at a spatial resolution of 100 km × 100 km. Using this database, we mapped large-scale patterns in species richness and phylogenetic diversity for species with different life forms and explored the mechanisms underlying these patterns. We also quantified the relationship between species richness and phylogenetic diversity and identified hotspots of Ranunculaceae phylogenetic diversity.<br><strong>Results:</strong> We found a latitudinal gradient in both species richness and phylogenetic diversity and revealed that Ranunculaceae in eastern Eurasia have particularly high levels of species and phylogenetic diversity in mountainous areas. Contemporary climate, habitat heterogeneity, and climate changes since the Last Glacial Maximum (LGM) all influenced spatial patterns in species richness and phylogenetic diversity, but their relative contributions varied across life forms. Phylogenetic diversity at mid and high latitudes was higher than expected when controlling for species richness, which suggests that these latitudes may represent a paleo-biodiversity hotspot of Ranunculaceae.<br><strong>Conclusion:</strong> Consequently, these regions should be considered a key conservation priority for this important family.</p>
Wang M, Zhan D, Wang X, Hu Q, Gu C, Li X, Wu Y. Performance optimization of atomic layer deposited ZnO thin-film transistors by vacuum annealing. IEEE Electron Device Letters. 2021;42:716–719.
Sun J, Endo S, Lin H, Hayden P, Vedral V, Yuan X. Perturbative quantum simulation. arXiv preprint arXiv:2106.05938. 2021.

Pages