An Analysis of Social Mobility in Contemporary Shanghai

This thesis topic is social mobility in contemporary Shanghai. After China became the second-largest economic entity in the world, it has faced the same social problems as the South Korea and Japan, such as a declining economic growth rate, ageing population, declining fertility rate, rising divorce rate, and declining social mobility. This research focused on analysing the reason for social inequality in contemporary Shanghai and the problem it posed to social mobility in Shanghai. This thesis mainly studies social mobility in Shanghai from four aspects. The first part is the historical background of the hukou system and the reduction of social mobility caused by its negative impact. The second part is to use the ISEI (International Socio-Economic Index) model to measure the changes in social mobility in Shanghai from 2003 to 2019. This part mainly quantifies overall social mobility through structural changes in the labour market. The third part is to explore the impact of education on social mobility, including educational inequity and educational level. The overall education level in Shanghai is improving faster than the industrial upgrading in the labour market, leading to a gradual decline in the competitiveness of academic qualifications in the labour market. The fourth part is that Shanghai's overall expenditure level is higher than in the past, including a higher macro tax burden rate and higher basic necessities expenditures, especially the growth of housing expenditures

Ultrasonic Image's Annotation Removal: A Self-supervised Noise2Noise Approach

Accurately annotated ultrasonic images are vital components of a high-quality medical report. Hospitals often have strict guidelines on the types of annotations that should appear on imaging results. However, manually inspecting these images can be a cumbersome task. While a neural network could potentially automate the process, training such a model typically requires a dataset of paired input and target images, which in turn involves significant human labour. This study introduces an automated approach for detecting annotations in images. This is achieved by treating the annotations as noise, creating a self-supervised pretext task and using a model trained under the Noise2Noise scheme to restore the image to a clean state. We tested a variety of model structures on the denoising task against different types of annotation, including body marker annotation, radial line annotation, etc. Our results demonstrate that most models trained under the Noise2Noise scheme outperformed their counterparts trained with noisy-clean data pairs. The costumed U-Net yielded the most optimal outcome on the body marker annotation dataset, with high scores on segmentation precision and reconstruction similarity. We released our code at https://github.com/GrandArth/UltrasonicImage-N2N-Approach.Comment: 10 pages, 7 figure

Importance of soil thermal regime in terrestrial ecosystem carbon dynamics in the circumpolar north

© The Author(s), 2016. This is the author's version of the work and is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Global and Planetary Change 142 (2016): 28-40, doi:10.1016/j.gloplacha.2016.04.011.In the circumpolar north (45-90°N), permafrost plays an important role in vegetation and carbon (C) dynamics. Permafrost thawing has been accelerated by the warming climate and exerts a positive feedback to climate through increasing soil C release to the atmosphere. To evaluate the influence of permafrost on C dynamics, changes in soil temperature profiles should be considered in global C models. This study incorporates a sophisticated soil thermal model (STM) into a dynamic global vegetation model (LPJ-DGVM) to improve simulations of changes in soil temperature profiles from the ground surface to 3 m depth, and its impacts on C pools and fluxes during the 20th and 21st centuries.With cooler simulated soil temperatures during the summer, LPJ-STM estimates ~0.4 Pg C yr-1 lower present-day heterotrophic respiration but ~0.5 Pg C yr-1 higher net primary production than the original LPJ model resulting in an additional 0.8 to 1.0 Pg C yr-1 being sequestered in circumpolar ecosystems. Under a suite of projected warming scenarios, we show that the increasing active layer thickness results in the mobilization of permafrost C, which contributes to a more rapid increase in heterotrophic respiration in LPJ-STM compared to the stand-alone LPJ model. Except under the extreme warming conditions, increases in plant production due to warming and rising CO2, overwhelm the enhanced ecosystem respiration so that both boreal forest and arctic tundra ecosystems remain a net C sink over the 21st century. This study highlights the importance of considering changes in the soil thermal regime when quantifying the C budget in the circumpolar north.This research is supported by funded projects to Q. Z. National Science Foundation (NSF- 1028291 and NSF- 0919331), the NSF Carbon and Water in the Earth Program (NSF-0630319), the NASA Land Use and Land Cover Change program (NASA- NNX09AI26G), and Department of Energy (DE-FG02-08ER64599).2017-05-0

Contrasting soil thermal responses to fire in Alaskan tundra and boreal forest

Author Posting. © American Geophysical Union, 2015. 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: Earth Surface 120 (2015): 363–378, doi:10.1002/2014JF003180.Recent fire activity throughout Alaska has increased the need to understand postfire impacts on soils and permafrost vulnerability. Our study utilized data and modeling from a permafrost and ecosystem gradient to develop a mechanistic understanding of the short- and long-term impacts of tundra and boreal forest fires on soil thermal dynamics. Fires influenced a variety of factors that altered the surface energy budget, soil moisture, and the organic-layer thickness with the overall effect of increasing soil temperatures and thaw depth. The postfire thickness of the soil organic layer and its impact on soil thermal conductivity was the most important factor determining postfire soil temperatures and thaw depth. Boreal and tundra ecosystems underlain by permafrost experienced smaller postfire soil temperature increases than the nonpermafrost boreal forest from the direct and indirect effects of permafrost on drainage, soil moisture, and vegetation flammability. Permafrost decreased the loss of the insulating soil organic layer, decreased soil drying, increased surface water pooling, and created a significant heat sink to buffer postfire soil temperature and thaw depth changes. Ecosystem factors also played a role in determining postfire thaw depth with boreal forests taking several decades longer to recover their soil thermal properties than tundra. These factors resulted in tundra being less sensitive to postfire soil thermal changes than the nonpermafrost boreal forest. These results suggest that permafrost and soil organic carbon will be more vulnerable to fire as climate warms.We are pleased to acknowledge funding from the US National Science Foundation, grants DEB-1026843 and EF-1065587, to the Marine Biological Laboratory. Additional logistical support was provided by Toolik Field Station and CH2MHill, funded by NSF's Office of Polar Programs.2015-08-2

Combined network analysis and interpretable machine learning reveals the environmental adaptations of more than 10,000 ruminant microbial genomes

BackgroundThe ruminant gastrointestinal contains numerous microbiomes that serve a crucial role in sustaining the host’s productivity and health. In recent times, numerous studies have revealed that variations in influencing factors, including the environment, diet, and host, contribute to the shaping of gastrointestinal microbial adaptation to specific states. Therefore, understanding how host and environmental factors affect gastrointestinal microbes will help to improve the sustainability of ruminant production systems.ResultsBased on a graphical analysis perspective, this study elucidates the microbial topology and robustness of the gastrointestinal of different ruminant species, showing that the microbial network is more resistant to random attacks. The risk of transmission of high-risk metagenome-assembled genome (MAG) was also demonstrated based on a large-scale survey of the distribution of antibiotic resistance genes (ARG) in the microbiota of most types of ecosystems. In addition, an interpretable machine learning framework was developed to study the complex, high-dimensional data of the gastrointestinal microbial genome. The evolution of gastrointestinal microbial adaptations to the environment in ruminants were analyzed and the adaptability changes of microorganisms to different altitudes were identified, including microbial transcriptional repair.ConclusionOur findings indicate that the environment has an impact on the functional features of microbiomes in ruminant. The findings provide a new insight for the future development of microbial resources for the sustainable development in agriculture

Trends and Controls on Water-Use Efficiency of an Old-Growth Coniferous Forest in the Pacific Northwest

At the ecosystem scale, water-use efficiency (WUE) is defined broadly as the ratio of carbon assimilated to water evaporated by an ecosystem. WUE is an important aspect of carbon and water cycling and has been used to assess forest ecosystem responses to climate change and rising atmospheric CO2 concentrations. This study investigates the influence of meteorological and radiation variables on forest WUE by analyzing an 18 year (1998–2015) half-hourly time series of carbon and water fluxes measured with the eddy covariance technique in an old-growth conifer forest in the Pacific Northwest, USA. Three different metrics of WUE exhibit an overall increase over the period 1998–2007 mainly due to an increase in gross primary productivity (GPP) and a decrease in evapotranspiration (ET). However, the WUE metrics did not exhibit an increase across the period from 2008 to 2015 due to a greater reduction in GPP relative to ET. The strength of associations among particular meteorological variables and WUE varied with the scale of temporal aggregation used. In general, vapor pressure deficit and air temperature appear to control WUE at half-hourly and daily time scales, whereas atmospheric CO2 concentration was identified as the most important factor controlling monthly WUE. Carbon and water fluxes and the consequent WUE showed a weak correlation to the Standard Precipitation Index, while carbon fluxes were strongly dependent on the combined effect of multiple climate factors. The inferred patterns and controls on forest WUE highlighted have implications for improved understanding and prediction of possible adaptive adjustments of forest physiology in response to climate change and rising atmospheric CO2 concentrations

Single-cell analysis reveals specific neuronal transition during mouse corticogenesis

Background: Currently, the mechanism(s) underlying corticogenesis is still under characterization.Methods: We curated the most comprehensive single-cell RNA-seq (scRNA-seq) datasets from mouse and human fetal cortexes for data analysis and confirmed the findings with co-immunostaining experiments.Results: By analyzing the developmental trajectories with scRNA-seq datasets in mice, we identified a specific developmental sub-path contributed by a cell-population expressing both deep- and upper-layer neurons (DLNs and ULNs) specific markers, which occurred on E13.5 but was absent in adults. In this cell-population, the percentages of cells expressing DLN and ULN markers decreased and increased, respectively, during the development suggesting direct neuronal transition (namely D-T-U). Whilst genes significantly highly/uniquely expressed in D-T-U cell population were significantly enriched in PTN/MDK signaling pathways related to cell migration. Both findings were further confirmed by co-immunostaining with DLNs, ULNs and D-T-U specific markers across different timepoints. Furthermore, six genes (co-expressed with D-T-U specific markers in mice) showing a potential opposite temporal expression between human and mouse during fetal cortical development were associated with neuronal migration and cognitive functions. In adult prefrontal cortexes (PFC), D-T-U specific genes were expressed in neurons from different layers between humans and mice.Conclusion: Our study characterizes a specific cell population D-T-U showing direct DLNs to ULNs neuronal transition and migration during fetal cortical development in mice. It is potentially associated with the difference of cortical development in humans and mice

Modeling wildfire regimes in northern North America

Wildfires have a significant impact on climate and ecosystems in Canada and Alaska. Characterizing fire regimes and projecting fire recurrence intervals for different biomes are important in managing those ecosystems and quantifying carbon dynamics of those ecosystems. Wildfires statistics for the conterminous Canada and Alaska are examined in a spatially and temporally explicit manner. The effort in this thesis used Canadian wildfire datasets, 1980–1999, to characterize relationships between number of fires and burned area for 13 ecozones, and to calculate wildfire recurrence intervals for each ecozone, using the parameters of the power-law frequency-area distributions. For the conterminous Canada, we find that: (a) Despite the many complexities concerning their initiation and propagation, wildfires exhibit power-law frequency-area statistics over many orders of magnitude in each ecozone and the whole of Canada; (b) The ratio of number of small to large fires generally increases from north to south of Canada; (c) Human ignition sources have higher probability to cause larger ratio of number of large to small fires; (d) Fire recurrence intervals ranged from 1 to 32 years for burned areas larger than 2 km 2, and from 1 to 100 years for burned areas larger than 10 km 2 in every 10,000 km2 spatial area for each ecozone. The results have a number of practical implications. First, the frequency-area distribution of small and medium fires can be used to quantify the risk of large fires. Second, the behavior of the forest fire model can be used to assess the role of controlled burns to reduce the hazard of very large fires. The findings of this study will also be a benefit to future efforts in quantifying carbon dynamics in Canadian boreal terrestrial ecosystems. Further effort should be put on the impact of fire disturbance on ecosystem structure and carbon dynamics. Interaction between fire and climate also needs much more attention, especially in a global warming period

Modeling permafrost impacts on vegetation and carbon dynamics in northern high latitudes

In the northern high latitudes, vegetation distribution and carbon cycling have been continuously changed in the past and could change more rapidly as the climate warming. The purpose of my PhD dissertation is to quantify the uncertainty in modeling vegetatidynamics and to assess the effect of permafrost on vegetation dynamics and carbon cycling in the northern high latitudes under different levels of warming conditions. The uncertainty in current modeling of vegetation dynamics is considerably large. The first part of this study is to assess how high-latitude vegetation may respond under various climate scenarios during the 21st Century with a focus on analyzing model parameters induced uncertainty and how this uncertainty compares to the uncertainty induced by various climates. The analysis was based on a set of 10,000 Monte Carlo ensemble LPJ simulations for the 45°N polewards region from 1900 to 2100. LPJ-DGVM was run under contemporary and future climates from four Special Report Emission Scenarios (SRES), A1FI, A2, B1, and B2, based on the Hadley Centre General Circulation Model (GCM), and six climate scenarios, X901M, X902L, X903H, X904M, X905L, and X906H from the Integrated Global System Model (IGSM) at the Massachusetts Institute of Technology (MIT). In the current dynamic vegetation model, some parameters are more important than others in determining the vegetation distribution. Parameters that control plant carbon uptake and light-use efficiency have the predominant influence on the vegetation distribution of both woody and herbaceous plant functional types. The relative importance of different parameters varies temporally and spatially and is influenced by climate inputs. In addition to climate, these parameters play an important role in determining the vegetation distribution in the region. The parameter-based uncertainties contribute most to the total uncertainty. The current warming conditions lead to a complexity of vegetation responses in the region. Temperate trees will be more sensitive to climate variability, compared with boreal forest trees and C3 perennial grasses. This sensitivity would result in a unanimous northward greenness migration due to anomalous warming in the northern high latitudes. Temporally, boreal needle-leaved evergreen plants are projected to decline considerably, and a large portion of C3 perennial grass is projected to disappear by the end of the 21st century. In contrast, the area of temperate trees would increase, especially under the most extreme A1FI scenario. As the warming continues, the northward greenness expansion in the Arctic region could continue. Permafrost is a key component that largely affects the vegetation dynamics and carbon cycling, however it is slowly incorporated into current ecosystem modeling. The second part of this study applied a well-developed numerical algorithm to simulate the thawing and freezing processes at daily time steps across multiple sites that vary with vegetation cover, disturbance history, and climate. The model performance was evaluated by comparing modeled and measured soil temperatures at different depths for both boreal forest stands and tundra stands. We used the model to explore the influence of climate, fire disturbance, and topography (north- and south-facing slopes) on soil thermal dynamics. Modeled soil temperatures agree well with measured values for both boreal forest and tundra ecosystems at the site level. Combustion of organic soil horizons from wildfire alters the surface energy balance and increases the downward heat flux through the soil profile, resulting in the warming and thawing of near-surface permafrost. A projection for the 21 st century indicates that as the climate warms, the active layer thickness could possibly increase more than three meters in the boreal forest site and deeper than one meter in the tundra site, which are both rates faster than expectations of previous studies. We concluded that the presented soil thermal model is able to simulate the soil thermal dynamics in permafrost regions well and could be used as a tool to analyze the influence of climate change and wildfire disturbance on permafrost thawing. As climate warming continues, permafrost degradation could be exacerbated and consequently exert considerable effects on terrestrial ecosystem in the region. The third part of this dissertation incorporates the soil thermal model into a dynamic global vegetation model (LPJ-DGVM) to improve the simulations of soil thermal, vegetation and carbon dynamics. The coupled model was applied to assess the impact of permafrost on ecosystem and carbon dynamics in the region during the 21st century. We found that (i) the near-surface permafrost would degrade significantly with the southern boundary of permafrost moving northward in the northern north America and the western boundary moving eastward in the northern Eurasia, especially under extreme climate scenarios (e.g., A1FI); (ii) the incorporation of permafrost into LPJ affects the distribution of boreal forests; (iii) climate variability and elevated CO2 fertilization both exert significant effects on vegetation distribution and carbon cycling with and without permafrost, while the CO2 fertilization plays a larger effects than climate; (iv) the overall effect of the addition of permafrost into LPJ results in an increase in net ecosystem production (NEP); however the permafrost degradation would lead to a faster decreasing NEP by 3 - 6 Tg C yr-1 because of more rapid increase in heterotrophic respiration (3 - 13 Tg C yr-1) than net primary production (0 - 8 Tg C yr-1); (v) permafrost largely suppresses soil carbon loss by 56.5 - 90.8 Pg C but slightly change vegetation carbon gain by -2.2 - 2.7 Pg C by year 2100. As the climate warms, the northern high latitudes region is predicted to turn into a substantial carbon source. Coupling the soil thermal model into LPJ improves the simulation of the seasonality of carbon cycles and constrains the uncertainty in modeling future vegetation distribution and carbon dynamics in the region