The impacts of climate change and agricultural activities on water cycling of Northern Eurasia

The ecosystems in Northern Eurasia (NE) are important due to their vast land coverage, high rate of observed and projected warming, and the potential feedbacks they can cause on the global climate system. To understand the impacts of climate change and agricultural activities on water cycling in NE, I analysed a variety of datasets and conducted series of studies by applying a combination of modeling, in-situ observations and remote sensing data, uncertainty analysis, and model-data fusion.^ Long-term unique in-situ measurements on soil moisture across multiple stations and discharge records at the outflow basins in Northern China (NC) provide us robust evidence to assess the trends of soil moisture and discharge in this region (Chapter 2). NC overlaps with NE and is one of the hot-spots experiencing the most severe water shortage in the world. Declines in soil moisture and stream flow detected via in-situ measurements in the last three decades indicate that water scarcity has been exacerbated. Multiple linear regression results indicate that intensification of agricultural activities including increase in fertilizer use, prevalence of water-expensive crops and cropland expansion appear to have aggravated these declines in this region.^ Scarce evapotranspiration (ET) measurements make ET estimation via model a necessary step for better regional-scale water management. Penman–Monteith based algorithms for plant transpiration and soil evaporation were introduced into the Terrestrial Ecosystem Model (TEM) to calculate ET (Chapter 3). I then examined the response of ET and water availability to changing climate and land cover on the Mongolian Plateau during the 21st century. It is shown that use of the Penman–Monteith based algorithms in the TEM substantially improved ET estimation on the Mongolia Plateau. Results show that regional annual ET varies from 188 to 286 mm yr−1 – with an increasing trend – across different climate change scenarios during the 21st century. Meanwhile, the differences between precipitation and ET suggest that the available water for human use will not change significantly during the 21st century. In addition, analyses also suggest that climate change is more important than land cover change in determining changes in regional ET.^ Improvement in the accuracy of ET estimation by introducing Penman–Monteith based algorithms into the TEM motivated me to further improve the model representation of ET processes. I further modified the TEM to incorporate more detailed ET processes including canopy interception loss, ET (evaporation) from wetland surfaces, wetlands and water bodies, and snow sublimation to examine spatiotemporal variation of ET in NE from 1948 to 2009 (Chapter 4). Those modifications lead to substantial enhancement in the accuracy of estimation of ET and runoff. The consideration of snow sublimation substantially improved the ET estimates and highlighted the importance of snow in the hydrometeorology of NE. The root mean square error of discharge from the six largest watersheds in NE decreased from 527.74 km 3 yr-1 to 126.23 km3 yr-1. Meanwhile, a systematic underestimation of river discharge after 1970 indicates that other water sources or dynamics not considered in the model (e.g., melting glaciers, permafrost thawing and fires) or bias in the precipitation forcing may also be important for the hydrology of the region.^ To better understand the possible causes of systematic bias in discharge estimates, I examined the impacts of forcing data uncertainty on ET and runoff estimation in NE by driving the modified TEM with five widely-used forcing data sets (Chapter 5). Estimates of regional ET vary between 263.5-369.3 mm yr-1 during 1979-2008 depending on the choice of forcing data, while the spatial variability of ET appears more consistent. Uncertainties in ETforcing propagate as well to estimates of runoff. Independent of the forcing dataset, the climatic variables that dominate ET temporal variability remain the same among all the five TEM simulated ET products. ET is dominated by air temperature in the north and by precipitation in the south during the growing season, and solar radiation and vapour pressure deficit explain the dynamics of ET for the rest of the year. While the Climate Research Unit (CRU) TS3.1 dataset of the University of East Anglia appears as a better choice of forcing via our assessment, the quality of forcing data remains a major challenge to accurately quantify the regional water balance in NE

Coarse Grained Molecular Simulation of Exosome Squeezing for Drug Loading

In recent years, extracellular vesicles such as exosomes have become promising carriers as the next-generation drug delivery platforms. Effective loading of exogenous cargos without compromising the extracellular vesicle membrane is a major challenge. Rapid squeezing through nanofluidic channels is a widely used approach to load exogenous cargoes into the exosome through the nanopores generated temporarily on the membrane. However, the exact mechanism and dynamics of nanopores opening, as well as cargo loading through nanopores during the squeezing process remains unknown and is impossible to be visualized or quantified experimentally due to the small size of the exosome and the fast transient process. This paper developed a systemic algorithm to simulate nanopore formation and predict drug loading during exosome squeezing by leveraging the power of coarse-grain (CG) molecular dynamics simulations with fluid dynamics. The exosome CG beads are coupled with implicit Fluctuating Lattice Boltzmann solvent. Effects of exosome property and various squeezing test parameters, such as exosome size, flow velocity, channel width, and length, on pore formation and drug loading efficiency are analyzed. Based on the simulation results, a phase diagram is provided as a design guidance for nanochannel geometry and squeezing velocity to generate pores on membrane without damaging the exosome. This method can be utilized to perform a parametric study to optimize the nanofluidic device configuration and flow setup to obtain desired drug loading into exosomes

Performance of solar-induced chlorophyll fluorescence in estimating water-use efficiency in a temperate forest

© The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Remote Sensing 10 (2018): 796, doi:10.3390/rs10050796.Water-use efficiency (WUE) is a critical variable describing the interrelationship between carbon uptake and water loss in land ecosystems. Different WUE formulations (WUEs) including intrinsic water use efficiency (WUEi), inherent water use efficiency (IWUE), and underlying water use efficiency (uWUE) have been proposed. Based on continuous measurements of carbon and water fluxes and solar-induced chlorophyll fluorescence (SIF) at a temperate forest, we analyze the correlations between SIF emission and the different WUEs at the canopy level by using linear regression (LR) and Gaussian processes regression (GPR) models. Overall, we find that SIF emission has a good potential to estimate IWUE and uWUE, especially when a combination of different SIF bands and a GPR model is used. At an hourly time step, canopy-level SIF emission can explain as high as 65% and 61% of the variances in IWUE and uWUE. Specifically, we find that (1) a daily time step by averaging hourly values during daytime can enhance the SIF-IWUE correlations, (2) the SIF-IWUE correlations decrease when photosynthetically active radiation and air temperature exceed their optimal biological thresholds, (3) a low Leaf Area Index (LAI) has a negative effect on the SIF-IWUE correlations due to large evaporation fluxes, (4) a high LAI in summer also reduces the SIF-IWUE correlations most likely due to increasing scattering and (re)absorption of the SIF signal, and (5) the observation time during the day has a strong impact on the SIF-IWUE correlations and SIF measurements in the early morning have the lowest power to estimate IWUE due to the large evaporation of dew. This study provides a new way to evaluate the stomatal regulation of plant-gas exchange without complex parameterizations.This research was supported by U.S. Department of Energy Office of Biological and Environmental Research Grant DE-SC0006951, National Science Foundation Grants DBI 959333 and AGS-1005663, and the University of Chicago and the MBL Lillie Research Innovation Award to Jianwu Tang. This study was also supported by the open project grant (LBKF201701) of Key Laboratory of Land Surface Pattern and Simulation, Chinese Academy of Sciences

One-step hydrothermal synthesis of fluorescence carbon quantum dots with high product yield and quantum yield

A one-step hydrothermal synthesis of nitrogen and silicon co-doped fluorescence carbon quantum dots (N,Si-CQDs), from citric acid monohydrate and silane coupling agent KH-792 with a high product yield (PY) of 52.56% and high quantum yield (QY) of 97.32%, was developed. This greatly improves both the PY and QY of CQDs and provides a new approach for a large-scale production of high-quality CQDs. Furthermore, N,Si-CQDs were employed as phosphors without dispersants to fabricate white light-emitting diodes (WLEDs) with the color coordinates at (0.29, 0.32). It is suggested that N,Si-CQDs have great potential as promising fluorescent materials to be applied in WLEDs.Peer reviewe

nn-body Correlation of Tonks-Girardeau Gas

For the well-known exponential complexity it is a giant challenge to calculate the correlation function for general many-body wave function. We investigate the ground state $n$th-order correlation functions of the Tonks-Girardeau (TG) gases. Basing on the wavefunction of free fermions and Bose-Fermi mapping method we obtain the exact ground state wavefunction of TG gases. Utilizing the properties of Vandermonde determinant and Toeplitz matrix, the $n$th-order correlation function is formulated as $(N-n)$-order Toeplitz determinant, whose element is the integral dependent on 2$(N-n)$ sign functions and can be computed analytically. By reducing the integral on domain $[0,2\pi]$ into the summation of the integral on several independent domains, we obtain the explicit form of the Toeplitz matrix element ultimately. As the applications we deduce the concise formula of the reduced two-body density matrix and discuss its properties. The corresponding natural orbitals and their occupation distribution are plotted. Furthermore, we give a concise formula of the reduced three-body density matrix and discuss its properties. It is shown that in the successive second measurements, atoms appear in the regions where atoms populate with the maximum probability in the first measurement.Comment: 8 pages, 7 figure

Measuring cell deformation by microfluidics

Microfluidics is an increasingly popular method for studying cell deformation, with various applications in fields such as cell biology, biophysics, and medical research. Characterizing cell deformation offers insights into fundamental cell processes, such as migration, division, and signaling. This review summarizes recent advances in microfluidic techniques for measuring cellular deformation, including the different types of microfluidic devices and methods used to induce cell deformation. Recent applications of microfluidics-based approaches for studying cell deformation are highlighted. Compared to traditional methods, microfluidic chips can control the direction and velocity of cell flow by establishing microfluidic channels and microcolumn arrays, enabling the measurement of cell shape changes. Overall, microfluidics-based approaches provide a powerful platform for studying cell deformation. It is expected that future developments will lead to more intelligent and diverse microfluidic chips, further promoting the application of microfluidics-based methods in biomedical research, providing more effective tools for disease diagnosis, drug screening, and treatment

Comparison of phenology estimated from reflectance-based indices and solar-induced chlorophyll fluorescence (SIF) observations in a temperate forest using GPP-based phenology as the standard

© The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Remote Sensing 10 (2018): 932, doi:10.3390/rs10060932.We assessed the performance of reflectance-based vegetation indices and solar-induced chlorophyll fluorescence (SIF) datasets with various spatial and temporal resolutions in monitoring the Gross Primary Production (GPP)-based phenology in a temperate deciduous forest. The reflectance-based indices include the green chromatic coordinate (GCC), field measured and satellite remotely sensed Normalized Difference Vegetation Index (NDVI); and the SIF datasets include ground-based measurement and satellite-based products. We found that, if negative impacts due to coarse spatial and temporal resolutions are effectively reduced, all these data can serve as good indicators of phenological metrics for spring. However, the autumn phenological metrics derived from all reflectance-based datasets are later than the those derived from ground-based GPP estimates (flux sites). This is because the reflectance-based observations estimate phenology by tracking physiological properties including leaf area index (LAI) and leaf chlorophyll content (Chl), which does not reflect instantaneous changes in phenophase transitions, and thus the estimated fall phenological events may be later than GPP-based phenology. In contrast, we found that SIF has a good potential to track seasonal transition of photosynthetic activities in both spring and fall seasons. The advantage of SIF in estimating the GPP-based phenology lies in its inherent link to photosynthesis activities such that SIF can respond quickly to all factors regulating phenological events. Despite uncertainties in phenological metrics estimated from current spaceborne SIF observations due to their coarse spatial and temporal resolutions, dates in middle spring and autumn—the two most important metrics—can still be reasonably estimated from satellite SIF. Our study reveals that SIF provides a better way to monitor GPP-based phenological metrics.This research was supported by U. S. Department of Energy Office of Biological and Environmental Research Grant DE-SC0006951, National Science Foundation Grants DBI 959333 and AGS-1005663, and the University of Chicago and the MBL Lillie Research Innovation Award to Jianwu Tang and China Scholarship Council No. 201506190095 to Z. Liu. Xiaoliang Lu was also supported by the open project grant (LBKF201701) of Key Laboratory of Land Surface Pattern and Simulation, Chinese Academy of Sciences

A large-scale methane model by incorporating the surface water transport

Author Posting. © American Geophysical Union, 2016. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Biogeosciences 121 (2016): 1657–1674, doi:10.1002/2016JG003321.The effect of surface water movement on methane emissions is not explicitly considered in most of the current methane models. In this study, a surface water routing was coupled into our previously developed large-scale methane model. The revised methane model was then used to simulate global methane emissions during 2006–2010. From our simulations, the global mean annual maximum inundation extent is 10.6 ± 1.9 km2 and the methane emission is 297 ± 11 Tg C/yr in the study period. In comparison to the currently used TOPMODEL-based approach, we found that the incorporation of surface water routing leads to 24.7% increase in the annual maximum inundation extent and 30.8% increase in the methane emissions at the global scale for the study period, respectively. The effect of surface water transport on methane emissions varies in different regions: (1) the largest difference occurs in flat and moist regions, such as Eastern China; (2) high-latitude regions, hot spots in methane emissions, show a small increase in both inundation extent and methane emissions with the consideration of surface water movement; and (3) in arid regions, the new model yields significantly larger maximum flooded areas and a relatively small increase in the methane emissions. Although surface water is a small component in the terrestrial water balance, it plays an important role in determining inundation extent and methane emissions, especially in flat regions. This study indicates that future quantification of methane emissions shall consider the effects of surface water transport.The finacial support for this work is from the Open Fund of State Key Laboratory of Remote Sensing Science of China (OFSLRSS201501); 2 Supported by the Fundamental Research Funds for the Central Universities (20720160109).2016-12-2

Market Discipline and City Commercial Banks’ Risk Taking

Since the end of 2006, commitment period of China’s joining into the WTO is over, Chinese bank industry fully opened, and market competition has become stronger. But China has an implicit deposit insurance, under this circumstances whether market discipline exists in city commercial banks has become an important question. This paper used data from 60 city commercial banks between 2003 and 2010 to analyze this issue. Study shows that before Chinese bank sector fully opened, the power of market is weak, market is unable to restrict city commercial bank’s risk effectively; in the wake of Chinese bank sector opening at the end of 2006, the power of market discipline gradually appeared, which controlled risk taking efficiently by price mechanism, but quantity discipline is always not obvious.Key words: Market discipline; Banking sector; Risk takin

Taming Gradient Variance in Federated Learning with Networked Control Variates

Federated learning, a decentralized approach to machine learning, faces significant challenges such as extensive communication overheads, slow convergence, and unstable improvements. These challenges primarily stem from the gradient variance due to heterogeneous client data distributions. To address this, we introduce a novel Networked Control Variates (FedNCV) framework for Federated Learning. We adopt the REINFORCE Leave-One-Out (RLOO) as a fundamental control variate unit in the FedNCV framework, implemented at both client and server levels. At the client level, the RLOO control variate is employed to optimize local gradient updates, mitigating the variance introduced by data samples. Once relayed to the server, the RLOO-based estimator further provides an unbiased and low-variance aggregated gradient, leading to robust global updates. This dual-side application is formalized as a linear combination of composite control variates. We provide a mathematical expression capturing this integration of double control variates within FedNCV and present three theoretical results with corresponding proofs. This unique dual structure equips FedNCV to address data heterogeneity and scalability issues, thus potentially paving the way for large-scale applications. Moreover, we tested FedNCV on six diverse datasets under a Dirichlet distribution with {\alpha} = 0.1, and benchmarked its performance against six SOTA methods, demonstrating its superiority.Comment: 14 page