Industrial Agglomeration, Production Networks and FDI Promotion The Case Study of China

Chinas Industrial clustering is a distinguished economic phenomenon over the last 20 years. It began to enter into its fast track in the mid-1990s and developed rapidly in recent years. Both market-driven force and government-driven force contribute to Chinese industrial clusters. The opening and stable macroeconomic policies create a favorable climate for the industrial clustering. Local government has made its contribution to construction on both hardware and software environments for industrial clusters. The major contribution of FDI to the local industrial clustering lies in helping integrating Chinese domestic industries into international division of labor and at the same time forging a relatively integrated production chain for Chinese domestic industries. At present, China has stepped into the new phase of industrial clusters upgrading. Chinese government is gradually improving the local software infrastructure for industry clustering.Industrial Agglomeration, China, Production Networks, FDI, foreign direct investment

Optical Remote Sensing Of Snow On Sea Ice: Ground Measurements, Satellite Data Analysis, And Radiative Transfer Modeling

Thesis (Ph.D.) University of Alaska Fairbanks, 2002The successful launch of the Terra satellite on December 18, 1999 opened a new era of earth observation from space. This thesis is motivated by the need for validation and promotion of the use of snow and sea ice products derived from MODIS, one of the main sensors aboard the Terra and Aqua satellites. Three cruises were made in the Southern Ocean, in the Ross, Amundsen and Bellingshausen seas. Measurements of all-wave albedo, spectral albedo, BRDF, snow surface temperature, snow grain size, and snow stratification etc. were carried out on pack ice floes and landfast ice. In situ measurements were also carried out concurrently with MODIS. The effect of snow physical parameters on the radiative quantities such as all-wave albedo, spectral albedo and bidirectional reflectance are studied using statistical techniques and radiative transfer modeling, including single scattering and multiple scattering. The whole thesis consists of six major parts. The first part (chapter 1) is a review of the present research work on the optical remote sensing of snow. The second part (chapter 2) describes the instrumentation and data-collection of ground measurements of all-wave albedo, spectral albedo and bidirectional reflectance distribution function (BRDF) of snow and sea ice in the visible-near-infrared (VNIR) domain in Western Antarctica. The third part (chapter 3) contains a detailed multivariate correlation and regression analysis of the measured radiative quantities with snow physical parameters such as snow density, surface temperature, single and composite grain size and number density. The fourth part (chapter 4) describes the validation of MODIS satellite data acquired concurrently with the ground measurements. The radiances collected by the MODIS sensor are converted to ground snow surface reflectances by removing the atmospheric effect using a radiative transfer algorithm (6S). Ground measured reflectance is corrected for ice concentration at the subpixel level so that the in situ and space-borne measured reflectance data are comparable. The fifth part (chapter 5) investigates the single scattering properties (extinction optical depth, single albedo, and the phase function or asymmetry factor) of snow grains (single or composite), which were calculated using the geometrical optical method. A computer code, GOMsnow, is developed and is tested against benchmark results obtained from an exact Mie scattering code (MIE0) and a Monte Carlo code. The sixth part (chapter 6) describes radiative transfer modeling of spectral albedo using a multi-layer snow model with a multiple scattering algorithm (DISORT). The effect of snow stratification on the spectral albedo is explored. The vertical heterogeneity of the snow grain-size and snow mass density is investigated. It is found that optical remote sensing of snow physical parameters from satellite measurements should take the vertical variation of snow physical parameters into account. The albedo of near-infrared bands is more sensitive to the grain-size at the very top snow layer (<5cm), while the albedo of the visible bands is sensitive to the grain-size of a much thicker snow layer. Snow parameters (grain-size, for instance) retrieved with near-infrared channels only represent the very top snow layer (most probably 1--3 cm). Multi-band measurements from visible to near-infrared have the potential to retrieve the vertical profile of snow parameters up to a snow depth limited by the maximum penetration depth of blue light

Monitoring Kilauea Volcano’s Eruption in 2018 Using Various Remote Sensing Techniques

Monitoring volcanic eruptions is essential, as early warnings can be issued in case of emergency. In this study, we used Sentinel-1-A InSAR, Landsat 7 & 8 thermal infrared and airborne LiDAR to monitor the Kilauea volcano’s East Rift Zone (ERZ) eruption of 2018

LncRNAs: the bridge linking RNA and colorectal cancer.

Long noncoding RNAs (lncRNAs) are transcribed by genomic regions (exceeding 200 nucleotides in length) that do not encode proteins. While the exquisite regulation of lncRNA transcription can provide signals of malignant transformation, lncRNAs control pleiotropic cancer phenotypes through interactions with other cellular molecules including DNA, protein, and RNA. Recent studies have demonstrated that dysregulation of lncRNAs is influential in proliferation, angiogenesis, metastasis, invasion, apoptosis, stemness, and genome instability in colorectal cancer (CRC), with consequent clinical implications. In this review, we explicate the roles of different lncRNAs in CRC, and the potential implications for their clinical application

Towards graphane field emitters.

We report on the improved field emission performance of graphene foam (GF) following transient exposure to hydrogen plasma. The enhanced field emission mechanism associated with hydrogenation has been investigated using Fourier transform infrared spectroscopy, plasma spectrophotometry, Raman spectroscopy, and scanning electron microscopy. The observed enhanced electron emissionhas been attributed to an increase in the areal density of lattice defects and the formation of a partially hydrogenated, graphane-like material. The treated GF emitter demonstrated a much reduced macroscopic turn-on field (2.5 V μm-1), with an increased maximum current density from 0.21 mA cm-2 (pristine) to 8.27 mA cm-2 (treated). The treated GFs vertically orientated protrusions, after plasma etching, effectively increased the local electric field resulting in a 2.2-fold reduction in the turn-on electric field. The observed enhancement is further attributed to hydrogenation and the subsequent formation of a partially hydrogenated structured 2D material, which advantageously shifts the emitter work function. Alongside augmentation of the nominal crystallite size of the graphitic superstructure, surface bound species are believed to play a key role in the enhanced emission. The hydrogen plasma treatment was also noted to increase the emission spatial uniformity, with an approximate four times reduction in the per unit area variation in emission current density. Our findings suggest that plasma treatments, and particularly hydrogen and hydrogen-containing precursors, may provide an efficient, simple, and low cost means of realizing enhanced nanocarbon-based field emission devices via the engineered degradation of the nascent lattice, and adjustment of the surface work function.For assistance in ATR FTIR and EDXRF measurements we thank Dr Bob Keighley and Dr Ralph Vokes of Shimadzu Corp; and for plasma optical spectrophotometry analysis, Dr Thomas Schűtte of PLASUS GmbH. This work is supported by National Key Basic Research Program 973(2010CB327705), National Natural Science Foundation Project (51120125001, 51002031, 61101023, 51202028), Foundation of Doctoral Program of Ministry of Education (20100092110015), an EPSRC Impact Acceleration grant, and the Research Fund for International Young Scientists from NSFC (510501101 42, 51350110232). MT Cole thanks the Oppenheimer Trust for their generous financial support.This is the author accepted manuscript. The final version is available from the Royal Society of Chemistry via http://dx.doi.org/10.1039/C5RA20771

Identification of Heavy Metal Contaminants in the Upper Clark Fork River Basin Using Laser Induced Spectroscopy and Hyperspectral Spectroscopy

The Upper Clark Fork River Basin is home to many current and abandoned mining sites which contribute to the presence of heavy metals. Heavy metals on surface sediments can harm human and ecological health, so it is important to identify these contaminants for removal. Laser Induced Breakdown Spectroscopy (LIBS) is an active spectroscopy method because it uses a laser pulse to remove a small amount of mass through laser ablation. As the electrons return to their ground states, the unique spectral signatures and intensity can determine the percentage of the element in the sample. Hyperspectral Spectroscopy (HS) is a passive method that uses natural light reflected from the sample to determine the range and concentration of the wavelength emitted. The resulting plot compares reflectance versus wavelength. HS can be applied to an airborne survey