Standard and Anomalous Wave Transport Inside Random Media

This thesis is a study of wave transport inside random media using random matrix theory. Anderson localization plays a central role in wave transport in random media. As a consequence of destructive interference in multiple scattering, the wave function decays exponentially inside random systems. Anderson localization is a wave effect that applies to both classical waves and quantum waves. Random matrix theory has been successfully applied to study the statistical properties of transport and localization of waves. Particularly, the solution of the Dorokhov-Mello-Pereyra-Kumar (DMPK) equation gives the distribution of transmission. For wave transport in standard one dimensional random systems in which the average number of scatterers per unit length is a constant, we get the ensemble average of the logarithm of transmission scales linearly with system length L, ⟨ln T⟩=-L/l, where l is the mean free path. The average transmission scales exponentially with L for deeply localized systems, ⟨T⟩∝exp⁡(-L/2l). We have also investigated the statistics of intensity inside the random systems and obtained the analytical expression of average intensity ⟨I(x)⟩. In addition, we find the average of the logarithm of intensity falls linearly with depth x, ⟨ln I(x)⟩=-x/l. We have explored the statistics of anomalous wave transport inside random systems with Lévy disorder, in which waves perform Lévy flights. We find the average logarithm of transmission scales as a power law with system length, ⟨ln T⟩∝-L^α, and the mean transmission scales as a power law for large L, ⟨T⟩→L^(-α), where α is the stability parameter of the α-stable distribution associated with the Lévy flights. We have also investigated the statistics of intensity in the interior of the random systems for Lévy flights of waves. We obtain an analytical expression for the average intensity and find the average of the logarithm of intensity falls as a power law with depth x, ⟨ln I(x)⟩∝-x^α. We have also studied the impact of internal and edge reflection on the statistics of wave transport in random media. We find that the statistics of transmission is independent of the location of the reflector. When a reflector is present in a random system, the average of the logarithm of transmission is shifted by ln Γ, ⟨ln T⟩=-L/l+ln Γ, where Γ is the transmission coefficient of the reflector. The parameter Γ can be found in term of the statistics of transmission by Γ=1-[1-(2⟨1/T⟩-1) e^2⟨ln⁡T ⟩ ]^2. Thus, the transmission of the reflector can be obtained from the information of transmission measured outside the system. We have also investigated the statistics of intensity inside random media and calculated the average intensity, which depends on the location of the reflector. The average logarithm of intensity is not affected by the presence of reflector before the reflector, and shifts by ln Γ beyond the reflector

Imbalanced Profit Margins of Urban Online Car-hailing Services: A Case from Didi Service Platform of China

Online car-hailing services are driven by the emergence and development of network technology and information sharing, which breaks the traditional balance of Chinese taxi market and reconstitutes profit allocation, bringing new opportunities and challenges to the development and management of traditional taxi industry. To improve the operation efficiency of taxi and promote the effective utilization of resources, this study presented a calculation method for the capacity utilization rate and constructed a taxi service profit rate model. Taking Beijing and Shanghai of China as examples, the profit margins of ride-hailing and online taxi services using the Didi trajectory data from December 22 to December 24, 2017 were compared and analyzed. Results demonstrate that the profits of different car-hailing services in China are imbalanced in terms of time and space dimensions. The search costs for drivers and passengers are high, especially during morning and evening rush hours. The low capacity utilization rates for taxis and ride-hailing services resulted in a conflict between low supply and high demand. The profit margins of taxis are much higher than those of car-hailing services. Moreover, profits on weekends are higher than those on workdays. Long distance orders (>15 km) and relatively short ones (<3km) generate higher profits. Relevant departments should rationally plan the holding volume of online car-hailing services and coordinate the service profit margins in different service modes to realize the sustainable development of the new and old taxi industry

Responses of seasonal indicators to extreme droughts in southwest China

Significant impact of extreme droughts on human society and ecosystem has occurred in many places of the world, for example, Southwest China (SWC). Considerable research concentrated on analyzing causes and effects of droughts in SWC, but few studies have examined seasonal indicators, such as variations of surface water and vegetation phenology. With the ongoing satellite missions, more and more earth observation data become available to environmental studies. Exploring the responses of seasonal indicators from satellite data to drought is helpful for the future drought forecast and management. This study analyzed the seasonal responses of surface water and vegetation phenology to drought in SWC using the multi-source data including Seasonal Water Area (SWA), Permanent Water Area (PWA), Start of Season (SOS), End of Season (EOS), Length of Season (LOS), precipitation, temperature, solar radiation, evapotranspiration, the Palmer Drought Severity Index (PDSI), the Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), Gross Primary Productivity (GPP) and data from water conservancy construction. The results showed that SWA and LOS effectively revealed the development and recovery of droughts. There were two obvious drought periods from 2000 to 2017. In the first period (from August 2003 to June 2007), SWA decreased by 11.81% and LOS shortened by 5 days. They reduced by 21.04% and 9 days respectively in the second period (from September 2009 to June 2014), which indicated that there are more severe droughts in the second period. The SOS during two drought periods delayed by 3~6 days in spring, while the EOS advanced 1~3 days in autumn. All of PDSI, SWA and LOS could reflect the period of droughts in SWC, but the LOS and PDSI were very sensitive to the meteorological events, such as precipitation and temperature, while the SWA performed a more stable reaction to drought and could be a good indicator for the drought periodicity. This made it possible for using SWA in drought forecast because of the strong correlation between SWA and drought. Our results improved the understanding of seasonal responses to extreme droughts in SWC, which will be helpful to the drought monitoring and mitigation for different seasons in this ecologically fragile region

Influencing factors of different development stages of green food industry: a system dynamic model

The green food industry is important for China because it bears the additional expectation of promoting the rural economy Heilongjiang Province is a representative example, which is one of the main production bases of green food With this in mind, this paper takes Heilongjiang Province as an example to research the main influencing factor of the green food industry This article uses system dynamics methods to construct research models and uses mathematical models to calculate the industry lifecycle. Different from previous studies, this paper provides the life cycle of the industry and discusses the effects of influencing factors during the different periods The main conclusion includes: The stage before 2011 is the termination period, the stage from 2011 to 2019 is the growth period, and the stage after 2019 is the property period By the final time of the simulation, there are no signs of filtering; The enterprise scale is the main influencing factor that can make positive effects on the output value of the green food industry from the growth period, and others have no objective impact from beginning to end; Undesirably high level of financial investment will execute a negative effect for industrial development in the property period, at least in terms of output value

Microbial metabolism influences microplastic perturbation of dissolved organic matter in agricultural soils

An estimated 258 million tons of plastic enter the soil annually. Joining persistent types of microplastic (MP), there will be an increasing demand for biodegradable plastics. There are still many unknowns about plastic pollution by either type, and one large gap is the fate and composition of dissolved organic matter (DOM) released from MPs as well as how they interact with soil microbiomes in agricultural systems. In this study, polyethylene MPs, photoaged to different degrees, and virgin polylactic acid MPs were added to agricultural soil at different levels and incubated for 100 days to address this knowledge gap. We find that, upon MP addition, labile components of low aromaticity were degraded and transformed, resulting in increased aromaticity and oxidation degree, reduced molecular diversity, and changed nitrogen and sulfur contents of soil DOM. Terephthalate, acetate, oxalate, and L-lactate in DOM released by polylactic acid MPs and 4-nitrophenol, propanoate, and nitrate in DOM released by polyethylene MPs were the major molecules available to the soil microbiomes. The bacteria involved in the metabolism of DOM released by MPs are mainly concentrated in Proteobacteria, Actinobacteriota, and Bacteroidota, and fungi are mainly in Ascomycota and Basidiomycota. Our study provides an in-depth understanding of the microbial transformation of DOM released by MPs and its effects of DOM evolution in agricultural soils

Meta-analysis of the effect of expression of MYB transcription factor genes on abiotic stress

Background MYB proteins are a large group of transcription factors. The overexpression of MYB genes has been reported to improve abiotic stress tolerance in plant. However, due to the variety of plant species studied and the types of gene donors/recipients, along with different experimental conditions, it is difficult to interpret the roles of MYB in abiotic stress tolerance from published data. Methods Using meta-analysis approach, we investigated the plant characteristics involved in cold, drought, and salt stress in MYB-overexpressing plants and analyzed the degrees of influence on plant performance by experimental variables. Results The results show that two of the four measured plant parameters in cold-stressed plants, two of the six in drought-stressed, and four of the 13 in salt-stressed were significantly impacted by MYB overexpression by 22% or more, and the treatment medium, donor/recipient species, and donor type significantly influence the effects of MYB-overexpression on drought stress tolerance. Also, the donor/recipient species, donor type, and stress duration all significantly affected the extent of MYB-mediated salt stress tolerance. In summary, this study compiles and analyzes the data across studies to help us understand the complex interactions that dictate the efficacy of heterologous MYB expression designed for improved abiotic stress tolerance in plants

Global land surface temperature influenced by vegetation cover and PM2.5 from 2001 to 2016

Land surface temperature (LST) is an important parameter to evaluate environmental changes. In this paper, time series analysis was conducted to estimate the interannual variations in global LST from 2001 to 2016 based on moderate resolution imaging spectroradiometer (MODIS) LST, and normalized difference vegetation index (NDVI) products and fine particulate matter (PM2.5) data from the Atmospheric Composition Analysis Group. The results showed that LST, seasonally integrated normalized difference vegetation index (SINDVI), and PM2.5 increased by 0.17 K, 0.04, and 1.02 �g/m3 in the period of 2001–2016, respectively. During the past 16 years, LST showed an increasing trend in most areas, with two peaks of 1.58 K and 1.85 K at 72�N and 48�S, respectively. Marked warming also appeared in the Arctic. On the contrary, remarkable decrease in LST occurred in Antarctic. In most parts of the world, LST was affected by the variation in vegetation cover and air pollutant, which can be detected by the satellite. In the Northern Hemisphere, positive relations between SINDVI and LST were found; however, in the Southern Hemisphere, negative correlations were detected. The impact of PM2.5 on LST was more complex. On the whole, LST increased with a small increase in PM2.5 concentrations but decreased with a marked increase in PM2.5. The study provides insights on the complex relationship between vegetation cover, air pollution, and land surface temperature

Land use change and climate variation in the Three Gorges Reservoir Catchment from 2000 to 2015 based on the Google Earth Engine

Possible environmental change and ecosystem degradation have received increasing attention since the construction of Three Gorges Reservoir Catchment (TGRC) in China. The advanced Google Earth Engine (GEE) cloud-based platform and the large number of Geosciences and Remote Sensing datasets archived in GEE were used to analyze the land use and land cover change (LULCC) and climate variation in TGRC. GlobeLand30 data were used to evaluate the spatial land dynamics from 2000 to 2010 and Landsat 8 Operational Land Imager (OLI) images were applied for land use in 2015. The interannual variations in the Land Surface Temperature (LST) and seasonally integrated normalized difference vegetation index (SINDVI) were estimated using Moderate Resolution Imaging Spectroradiometer (MODIS) products. The climate factors including air temperature, precipitation and evapotranspiration were investigated based on the data from the Global Land Data Assimilation System (GLDAS). The results indicated that from 2000 to 2015, the cultivated land and grassland decreased by 2.05% and 6.02%, while the forest, wetland, artificial surface, shrub land and waterbody increased by 3.64%, 0.94%, 0.87%, 1.17% and 1.45%, respectively. The SINDVI increased by 3.209 in the period of 2000-2015, while the LST decreased by 0.253 °C from 2001 to 2015. The LST showed an increasing trend primarily in urbanized area, with a decreasing trend mainly in forest area. In particular, Chongqing City had the highest LST during the research period. A marked decrease in SINDVI occurred primarily in urbanized areas. Good vegetation areas were primarily located in the eastern part of the TGRC, such as Wuxi County, Wushan County, and Xingshan County. During the 2000–2015 period, the air temperature, precipitation and evapotranspiration rose by 0.0678 °C/a, 1.0844 mm/a, and 0.4105 mm/a, respectively. The climate change in the TGRC was influenced by LULCC, but the effect was limited. What is more, the climate change was affected by regional climate change in Southwest China. Marked changes in land use have occurred in the TGRC, and they have resulted in changes in the LST and SINDVI. There was a significantly negative relationship between LST and SINDVI in most parts of the TGRC, especially in expanding urban areas and growing forest areas. Our study highlighted the importance of environmental protection, particularly proper management of land use, for sustainable development in the catchment