The Diversity of Modern Urbanism: An International Comparative Study of Urban Space

While industrialization and globalization are continuing to bridge cultural and geographical gaps on the earth, differences still exist. Today, Developing countries are undergoing massive urban transition; and the transition appears to pursue the path of developed countries. However, the belief that global paths of urbanism will converge into one road is not convincing. Many studies on urbanism have been discussed in the past. However, these studies are mainly focused on urban areas in developed countries, mostly located in North America and Europe. In the last ten years, researchers have done more studies in developing areas, especially in East Asia. Though the study of urban issues in developing countries is still basic and rough, the uniqueness of the massive urban transition in developing regions is beginning to emerge. The differences of urban space in East Asian, Europe, and America is becoming much clearer; however, very few study have analyzed these dissimilarities with a global scope. The purpose of this paper is to explore the nature of these dissimilarities. Using ArcGIS data-sets for global population count and man-made impervious surface, the study makes an international comparison of urban landscapes. In this paper, several values will be calculated and compared. Multi-distance spatial statistics and zonal statistics are applied as the analytical tools. This study gives a statistic evidence that there is diversity not uniformity in modern urbanism: 1. The disperse and low density American urban; 2. the clustered and high density Chinese urban; and 3. the clustered and medium density European urban.The significant differences in global urbanism may indicates the need for new directions for developed theories in the future. Adviser: Mark A. Hoista

Vegetation changes and land surface feedbacks drive shifts in local temperatures over Central Asia

Vegetation changes play a vital role in modifying local temperatures although, until now, the climate feedback effects of vegetation changes are still poorly known and large uncertainties exist, especially over Central Asia. In this study, using remote sensing and re-analysis of existing data, we evaluated the impact of vegetation changes on local temperatures. Our results indicate that vegetation changes have a significant unidirectional causality relationship with regard to local temperature changes. We found that vegetation greening over Central Asia as a whole induced a cooling effect on the local temperatures. We also found that evapotranspiration (ET) exhibits greater sensitivity to the increases of the Normalized Difference Vegetation Index (NDVI) as compared to albedo in arid/semi-arid/semi-humid regions, potentially leading to a cooling effect. However, in humid regions, albedo warming completely surpasses ET cooling, causing a pronounced warming. Our findings suggest that using appropriate strategies to protect vulnerable dryland ecosystems from degradation, should lead to future benefits related to greening ecosystems and mitigation for rising temperatures

Study on QSTR of Benzoic Acid Compounds with MCI

Quantitative structure-toxicity relationship (QSTR) plays an important role in toxicity prediction. With the modified method, the quantum chemistry parameters of 57 benzoic acid compounds were calculated with modified molecular connectivity index (MCI) using Visual Basic Program Software, and the QSTR of benzoic acid compounds in mice via oral LD50 (acute toxicity) was studied. A model was built to more accurately predict the toxicity of benzoic acid compounds in mice via oral LD50: 39 benzoic acid compounds were used as a training dataset for building the regression model and 18 others as a forecasting dataset to test the prediction ability of the model using SAS 9.0 Program Software. The model is LogLD50 = 1.2399 × 0JA +2.6911 × 1JA – 0.4445 × JB (R2 = 0.9860), where 0JA is zero order connectivity index, 1JA is the first order connectivity index and JB = 0JA × 1JA is the cross factor. The model was shown to have a good forecasting ability

Sub-daily simulation of mountain flood processes based on the modified soil water assessment tool (SWAT) model

Floods not only provide a large amount of water resources, but they also cause serious disasters. Although there have been numerous hydrological studies on flood processes, most of these investigations were based on rainfall-type floods in plain areas. Few studies have examined high temporal resolution snowmelt floods in high-altitude mountainous areas. The Soil Water Assessment Tool (SWAT) model is a typical semi-distributed, hydrological model widely used in runoff and water quality simulations. The degree-day factor method used in SWAT utilizes only the average daily temperature as the criterion of snow melting and ignores the influence of accumulated temperature. Therefore, the influence of accumulated temperature on snowmelt was added by increasing the discriminating conditions of rain and snow, making that more suitable for the simulation of snowmelt processes in high-altitude mountainous areas. On the basis of the daily scale, the simulation of the flood process was modeled on an hourly scale. This research compared the results before and after the modification and revealed that the peak error decreased by 77% and the time error was reduced from +/- 11 h to +/- 1 h. This study provides an important reference for flood simulation and forecasting in mountainous areas

Accurate simulation of ice and snow runoff for the mountainous terrain of the Kunlun Mountains, China

While mountain runoff provides great potential for the development and life quality of downstream populations, it also frequently causes seasonal disasters. The accurate modeling of hydrological processes in mountainous areas, as well as the amount of meltwater from ice and snow, is of great significance for the local sustainable development, hydropower regulations, and disaster prevention. In this study, an improved model, the Soil Water Assessment Tool with added ice-melt module (SWATAI) was developed based on the Soil Water Assessment Tool (SWAT), a semi-distributed hydrological model, to simulate ice and snow runoff. A temperature condition used to determine precipitation types has been added in the SWATAI model, along with an elevation threshold and an accumulative daily temperature threshold for ice melt, making it more consistent with the runoff process of ice and snow. As a supplementary reference, the comparison between the normalized difference vegetation index (NDVI) and the quantity of meltwater were conducted to verify the simulation results and assess the impact of meltwater on the ecology. Through these modifications, the accuracy of the daily flow simulation results has been considerably improved, and the contribution rate of ice and snow melt to the river discharge calculated by the model increased by 18.73%. The simulation comparison of the flooding process revealed that the accuracy of the simulated peak flood value by the SWATAI was 77.65% higher than that of the SWAT, and the temporal accuracy was 82.93% higher. The correlation between the meltwater calculated by the SWATAI and the NDVI has also improved significantly. This improved model could simulate the flooding processes with high temporal resolution in alpine regions. The simulation results could provide technical support for economic benefits and reasonable reference for flood prevention

Low temperature structure and the ferroelectric phase transitions in the CdTiO3 perovskite

The paraelectric-ferroelectric transition in CdTiO3 has been monitored using high resolution neutron diffraction data. This necessitated preparing a sample enriched in 114Cd. A subtle, but significant, anisotropy in the thermal expansion of the lattice parameters for CdTiO3 associated with the transition to the polar structure was observed. First-principles calculations are presented to understand energies, phonon dispersion, and structures of possible phases with different symmetries.Australian Research Counci

Stacking up electron-rich and electron-deficient monolayers to achieve extraordinary mid- to far-infrared excitonic absorption: Interlayer excitons in the C3B/C3N bilayer

Our ability to efficiently detect and generate far-infrared (i.e., terahertz) radiation is vital in areas spanning from biomedical imaging to interstellar spectroscopy. Despite decades of intense research, bridging the terahertz gap between electronics and optics remains a major challenge due to the lack of robust materials that can efficiently operate in this frequency range, and two-dimensional (2D) type-II heterostructures may be ideal candidates to fill this gap. Herein, using highly accurate many-body perturbation theory within the GW plus Bethe-Salpeter equation approach, we predict that a type-II heterostructure consisting of an electron rich C3N and an electron deficient C3B monolayers can give rise to extraordinary optical activities in the mid- to far-infrared range. C3N and C3B are two graphene-derived 2D materials that have attracted increasing research attention. Although both C3N and C3B monolayers are moderate gap 2D materials, and they only couple through the rather weak van der Waals interactions, the bilayer heterostructure surprisingly supports extremely bright, low-energy interlayer excitons with large binding energies of 0.2 ~ 0.4 eV, offering an ideal material with interlayer excitonic states for mid-to far-infrared applications at room temperature. We also investigate in detail the properties and formation mechanism of the inter- and intra-layer excitons.Comment: 15 pages, 6 figure

Comparing bias correction methods used in downscaling precipitation and temperature from regional climate models : a case study from the Kaidu River Basin in Western China

The systemic biases of Regional Climate Models (RCMs) impede their application in regional hydrological climate-change effects analysis and lead to errors. As a consequence, bias correction has become a necessary prerequisite for the study of climate change. This paper compares the performance of available bias correction methods that focus on the performance of precipitation and temperature projections. The hydrological effects of these correction methods are evaluated by the modelled discharges of the Kaidu River Basin. The results show that all used methods improve the performance of the original RCM precipitation and temperature simulations across a number of levels. The corrected results obtained by precipitation correction methods demonstrate larger diversities than those produced by the temperature correction methods. The performance of hydrological modelling is highly influenced by the choice of precipitation correction methods. Furthermore, no substantial differences can be identified from the results of the temperature-corrected methods. The biases from input data are often greater from the works of hydrological modelling. The suitability of these approaches depends upon the regional context and the RCM model, while their application procedure and a number of results can be adapted from region to region