New NMR Methods for Characterizing Nanoporous Structures and Nanoconfined Shale Gas

Nanoporous materials, such as activated carbons and gas shale rocks, play crucial roles in both industry and daily life. Activated carbons have been used in various areas, such as water filtration, supercapacitors, and catalysis carriers, and shale gas has contributed more than 50% of the annual natural gas production in the United States. In all those areas, the performance of nanoporous materials is controlled by the properties of nanopores. However, both accurate characterization of micropores in activated carbons and evaluation of adsorption capability of high-pressure nature gas in shale rocks are challenging problems. We first introduce a room temperature method for determining micropore size distribution of activated carbons based on 1H nuclear magnetic resonance (NMR) of adsorbed water under magic angle spinning (MAS). The observed NMR peak shift comes from the nucleus-independent chemical shift (NICS). The density functional theory computation of NICS yields a quantitative relationship between the observed peak shift and the micropore size. This relationship provides a direct link between the 1H MAS NMR lineshape and micropore size distribution. The NICS NMR porometry technique is shown to be useful for characterizing micropore structures of highly carbonized activated carbons. In the second part, we develop a novel method for the evaluation of the gas storage capability of gas shale based on NMR T2 contrast. The FT-NMR spectral lineshape of gas stored inside pores, which reveal the properties of nanopores, are also studied by experiments. The combined information from spectra, longitudinal relaxation, and transverse relaxation not only offers a powerful tool for the evaluation of gas storage quantity but also provides valuable information for gas storage mechanisms.Doctor of Philosoph

Enrollment Forecast for Clinical Trials at the Planning Phase with Study-Level Historical Data

Given progressive developments and demands on clinical trials, accurate enrollment timeline forecasting is increasingly crucial for both strategic decision-making and trial execution excellence. Naive approach assumes flat rates on enrollment using average of historical data, while traditional statistical approach applies simple Poisson-Gamma model using timeinvariant rates for site activation and subject recruitment. Both of them are lack of nontrivial factors such as time and location. We propose a novel two-segment statistical approach based on Quasi-Poisson regression for subject accrual rate and Poisson process for subject enrollment and site activation. The input study-level data is publicly accessible and it can be integrated with historical study data from user's organization to prospectively predict enrollment timeline. The new framework is neat and accurate compared to preceding works. We validate the performance of our proposed enrollment model and compare the results with other frameworks on 7 curated studies

Deep Learning-Based Psoriasis Assessment: Harnessing Clinical Trial Imaging for Accurate Psoriasis Area Severity Index Prediction

Introduction: Image-based machine learning holds great promise for facilitating clinical care; however, the datasets often used for model training differ from the interventional clinical trial-based findings frequently used to inform treatment guidelines. Here, we draw on longitudinal imaging of psoriasis patients undergoing treatment in the Ultima 2 clinical trial (NCT02684357), including 2,700 body images with psoriasis area severity index (PASI) annotations by uniformly trained dermatologists. Methods: An image-processing workflow integrating clinical photos of multiple body regions into one model pipeline was developed, which we refer to as the “One-Step PASI” framework due to its simultaneous body detection, lesion detection, and lesion severity classification. Group-stratified cross-validation was performed with 145 deep convolutional neural network models combined in an ensemble learning architecture. Results: The highest-performing model demonstrated a mean absolute error of 3.3, Lin’s concordance correlation coefficient of 0.86, and Pearson correlation coefficient of 0.90 across a wide range of PASI scores comprising disease classifications of clear skin, mild, and moderate-to-severe disease. Within-person, time-series analysis of model performance demonstrated that PASI predictions closely tracked the trajectory of physician scores from severe to clear skin without systematically over- or underestimating PASI scores or percent changes from baseline. Conclusion: This study demonstrates the potential of image processing and deep learning to translate otherwise inaccessible clinical trial data into accurate, extensible machine learning models to assess therapeutic efficacy

Wet and Dry Atmospheric Depositions of Inorganic Nitrogen during Plant Growing Season in the Coastal Zone of Yellow River Delta

The ecological problems caused by dry and wet deposition of atmospheric nitrogen have been widespread concern in the world. In this study, wet and dry atmospheric depositions were monitored in plant growing season in the coastal zone of the Yellow River Delta (YRD) using automatic sampling equipment. The results showed that SO42- and Na+ were the predominant anion and cation, respectively, in both wet and dry atmospheric depositions. The total atmospheric nitrogen deposition was ~2264.24 mg m−2, in which dry atmospheric nitrogen deposition was about 32.02%. The highest values of dry and wet atmospheric nitrogen deposition appeared in May and August, respectively. In the studied area, NO3-–N was the main nitrogen form in dry deposition, while the predominant nitrogen in wet atmospheric deposition was NH4+–N with ~56.51% of total wet atmospheric nitrogen deposition. The average monthly attribution rate of atmospheric deposition of NO3-–N and NH4+–N was ~31.38% and ~20.50% for the contents of NO3-–N and NH4+–N in 0–10 cm soil layer, respectively, suggested that the atmospheric nitrogen was one of main sources for soil nitrogen in coastal zone of the YRD

Nucleation and Growth Process of Water Adsorption in Micropores of Activated Carbon Revealed by NMR

Properties of liquids at solid interfaces play a central role in numerous important processes in nature. Nuclear magnetic resonance (NMR) is particularly useful for probing liquid/graphitic carbon interfacial properties. In particular, the nucleus-independent chemical shift (NICS) provides a sensitive measure of the distance between adsorbates and the graphitic carbon surface on the subnanometer scale, enabling NMR to acquire subnanometer scale spatial resolution. Here, by combining the information on thermodynamics obtained from in situ NMR-detected water isotherm and spatially resolved information on structure and dynamics obtained by NICS-resolved NMR, the microscopic process of water nucleation and growth inside the micropore of activated carbons is investigated. The formation of water clusters at surface sites, the cooperative growth process of pore bridging, and the final stage of horizontal pore filling are revealed in detail, demonstrating the potential of this comprehensive NMR approach for studying microscopic mechanisms at solid/liquid interfaces including electrochemical processes

Remote sensing retrieval of surface suspended sediment concentration in the Yellow River Estuary

Accurate assessment of surface suspended sediment concentration (SSSC) in estuary is essential to address several important issues: erosion, water pollution, human health risks, etc. In this study, an empirical cubic retrieval model was developed for the retrieval of SSSC from Yellow River Estuary. Based on sediments and seawater collected from the Yellow River and southeastern Laizhou Bay, SSSC conditions were reproduced in the laboratory at increasing concentrations within a range common to field observations. Continuous spectrum measurements of the various SSSCs ranging from 1 to 5700 mg/l were carried out using an AvaField-3 spectrometer. The results indicated the good correlation between water SSSC and spectral reflectance (R (rs)) was obtained in the spectral range of 726-900 nm. At SSSC greater than 2700 mg/L, the 740-900 nm spectral range was less susceptible to the effects of spectral reflectance saturation and more suitable for retrieval of high sediment concentrations. The best correlations were obtained for the reflectance ratio of 820 nm to 490 nm. Informed by the correlation between R (rs) and SSSC, a retrieval model was developed (R (2) = 0.992). The novel cubic model, which used the ratio of a near-infrared (NIR) band (740-900 nm) to a visible band (400-600 nm) as factors, provided robust quantification of high SSSC water samples. Two high SSSC centers, with an order of 10(3) mg/l, were found in the inversion results around the abandoned Diaokou River mouth, the present Yellow River mouth to the abandoned Qingshuigou River mouth. There was little sediment exchange between the two high SSSC centers due to the directions of the residual currents and vertical mixing

The evolutionary process of the geomorphology of tidal embayments in southern Jiaodong Peninsula, China

Based on the theory of flood/ebb asymmetry, the evolution of the geomorphology of representative bays along the southern coast of the Jiaodong Peninsula over the last 40 years was investigated using remote sensing and geographic information system technologies. The results showed that coastal features such as tidal flats and tidal inlets in the bays changed significantly over time. The studied bays are in a ring shaped geomorphic spatial pattern characterized by shallow water, and they were concentrically ringed by tidal flats and coastal plains before the early 1980s. Later, however, a number of ponds appeared between the coastal plains and tidal flats. The extent of sediment infill for each bay in the 1980s was greater than that in the 1970s. The conversion of flat -inlets and the erosion/deposition change of tidal inlets in these four bays during study period were not synchronized. Each bay was in a state of flood asymmetry, and both the net fine and net coarse sediment deposition took place in the 1970s. From the late 1960s to the early 1980s, Dingzi Bay was characterized by flood asymmetry, and its tidal asymmetry ratio increased. The Jinghai and the Wuleidao bays were in a state of flood asymmetry, and their tidal asymmetry ratios decreased, while Rushan Bay was in a transition state from flood to ebb asymmetry. However, intensive human activities over the last 30 years, especially the construction of coastal ponds, has greatly changed the hydrology and sedimentation of these bays, causing profound changes in geomorphic features; furthermore, these changes have guided the evolutionary process of the bays. Our results suggest that the intensive human activities were key factors that caused changes in the geomorphic evolution of the studied tidal embayments, especially the sudden change from a state of rising flood asymmetry to ebb asymmetry in Dingzi Bay. (C) 2017 Published by Elsevier Ltd

Wet and Dry Atmospheric Depositions of Inorganic Nitrogen during Plant Growing Season in the Coastal Zone of Yellow River Delta

The ecological problems caused by dry and wet deposition of atmospheric nitrogen have been widespread concern in the world. In this study, wet and dry atmospheric depositions were monitored in plant growing season in the coastal zone of the Yellow River Delta (YRD) using automatic sampling equipment. The results showed that SO42- and Na+ were the predominant anion and cation, respectively, in both wet and dry atmospheric depositions. The total atmospheric nitrogen deposition was similar to 2264.24mg m(-2), in which dry atmospheric nitrogen deposition was about 32.02%. The highest values of dry and wet atmospheric nitrogen deposition appeared in May and August, respectively. In the studied area, NO3- -N was the main nitrogen form in dry deposition, while the predominant nitrogen in wet atmospheric deposition was NH4+ -N with similar to 56.51% of total wet atmospheric nitrogen deposition. The average monthly attribution rate of atmospheric deposition of NO3- -N and NH4+ -N was similar to 31.38% and similar to 20.50% for the contents of NO3- -N and NH4+ -N in 0-10 cm soil layer, respectively, suggested that the atmospheric nitrogen was one of main sources for soil nitrogen in coastal zone of the YRD.The ecological problems caused by dry and wet deposition of atmospheric nitrogen have been widespread concern in the world. In this study, wet and dry atmospheric depositions were monitored in plant growing season in the coastal zone of the Yellow River Delta (YRD) using automatic sampling equipment. The results showed that SO42- and Na+ were the predominant anion and cation, respectively, in both wet and dry atmospheric depositions. The total atmospheric nitrogen deposition was similar to 2264.24mg m(-2), in which dry atmospheric nitrogen deposition was about 32.02%. The highest values of dry and wet atmospheric nitrogen deposition appeared in May and August, respectively. In the studied area, NO3- -N was the main nitrogen form in dry deposition, while the predominant nitrogen in wet atmospheric deposition was NH4+ -N with similar to 56.51% of total wet atmospheric nitrogen deposition. The average monthly attribution rate of atmospheric deposition of NO3- -N and NH4+ -N was similar to 31.38% and similar to 20.50% for the contents of NO3- -N and NH4+ -N in 0-10 cm soil layer, respectively, suggested that the atmospheric nitrogen was one of main sources for soil nitrogen in coastal zone of the YRD

Distribution of carbon, nitrogen and phosphorus in coastal wetland soil related land use in the Modern Yellow River Delta

The delivery and distribution of nutrients in coastal wetland ecosystems is much related to the land use. The spatial variations of TOC, TN, NH4+-N, NO3--N and TP and associated soil salinity with depth in 9 kinds land uses in coastal zone of the modern Yellow River Delta (YRD) was evaluated based on monitoring data in field from 2009 to 2015. The results showed that the average contents of soil TOC, TN, NO3--N, NH4+-N and TP were 4.21 +/- 2.40 g kg(-1), 375.91 +/- 213.44, 5.36 +/- 9.59 and 7.20 +/- 5.58 and 591.27 +/- 91.16 mg kg(-1), respectively. The high N and C contents were found in cropland in southern part and low values in natural wetland, while TP was relatively stable both in profiles and in different land uses. The land use, land formation age and salinity were important factors influencing distributions of TOC and N. Higher contents of TOC and N were observed in older formation age lands in whole study region, while the opposite regulation were found in new-born natural wetland, indicating that the anthropogenic activities could greatly alter the original distribution regulations of nutrients in coastal natural wetlands by changing the regional land use