Derivation of Probabilistic Thresholds of Spatially Distributed Rainfall for Flood Forecasting

“Rainfall threshold” is considered as one of the evolving flood forecasting approaches. When the cumulative rainfall depth for a given initial soil moisture condition intersects the corresponding moisture curve, the peak discharge is expected to be equal or greater than the threshold discharge for flooding at the target site. Besides the total rainfall depth, spatial and temporal distribution of rainfall can influence the peak discharge and the time to peak. In the few past studies on the extraction of rainfall threshold curves for flood forecasting, the rainfall assumed to be uniform in space whereas the temporal distribution was subjected to certain assumptions. In the present study, the spatial distribution of rainfall was simulated with the Monte Carlo (MC) method and the mean Huff pattern for all rainfall durations was imposed for the temporal distribution. For each of the MC run, the random weight assigned to every sub-watershed follows the pdf of weights in historical rainfall events. The HEC–HMS model with two different infiltration methods namely SCS–CN and Green–Ampt and Muskingum river routing were adopted as the hydrologic model. After the calibration and validation of the model for Madarsoo watershed in Golestan province in Northeastern Iran, the MC simulations were performed for 1, 2, 6 and 12 h durations. The outputs from the SCS–CN method exhibit only a slight increase in threshold values with respect to duration and was not in the range of our expectations from watershed response, i.e. the rainfalls with greater durations should be greater in depth to produce a specific peak discharge. For the Green–Ampt infiltration method, the rainfall thresholds with 50% probability associated with the critical discharge under dry soil moisture condition were 44.5, 49.0, 64.2 and 94.6 mm for 1, 2, 6 and 12 h durations, respectively. Results for July 2001 flooding revealed that the cumulative rainfall intersected all 10%, 50% and 90% rainfall threshold curves but for July 2005 flooding the 10% curve was only intersected by the cumulative rainfall curve. The advantage of MC-derived rainfall threshold curves in real-time operations is that decision-makers have the flexibility to adopt a curve more consistent with flood observations in the region.     

Instability and transport of metal catalyst in the growth of tapered silicon nanowires

During metal-catalyzed growth of tapered silicon nanowires, or silicon nanocones (SiNCs), Au-Si eutectic particles are seen to undergo significant and reproducible reductions in their diameters. The reductions are accompanied by the transfer of eutectic droplet mass to adjacent, initially metal catalyst-free substrates, producing secondary nucleation and growth of SiNCs. Remarkably, the catalyst particle diameters on the SiNCs grown on the adjacent substrates are strongly correlated with those on the SiNCs grown on the initially Au-nanoparticle-coated substrate. These post-growth nanoparticle sizes depend on temperature and are found to be independent of the initial nanoparticle sizes. Our modeling and analysis indicates that the size reduction and mass transfer could be explained by electrostatic charge-induced dissociation of the droplet. The reduction in size enables the controlled growth of SiNCs with tip sharpnesses approaching the atomic scale, indicating that metal-catalyst nanoparticles can play an even more dynamic role than previously thought, and suggesting additional modes of control of shape, and of nucleation and growth location.     

Accurate crop-type classification using multi-temporal optical and multi-polarization SAR data in an object-based image analysis framework

Accurate crop-type classification is a challenging task due, primarily, to the high within-class spectral variations of individual crops during the growing season (phenological development) and, second, to the high between-class spectral similarity of crop types. Utilizing within-season multi-temporal optical and multi-polarization synthetic aperture radar (SAR) data, this study introduces a combined object- and pixel-based image classification methodology for accurate crop-type classification. Particularly, the study investigates the improvement of crop-type classification by using the least number of multi-temporal RapidEye (RE) images and multi-polarization Radarsat-2 (RS-2) data utilized in an object- and pixel-based image analysis framework. The method was tested on a study area in Manitoba, Canada, using three different classifiers including the standard Maximum Likelihood (ML), Decision Tree (DT), and Random Forest (RF) classifiers. Using only two RE images of July and August, the proposed method results in overall accuracies (OAs) of about 95%, 78%, and 93% for the ML, DT, and RF classifiers, respectively. Moreover, the use of only two quad-pol images of RS-2 of June and September resulted in OAs of 92%, 75%, and 90% for the ML, DT, and RF classifiers, respectively. The best classification results were achieved by the synergistic use of two RE and two RS-2 images. In this case, the overall classification accuracies were 97% for both ML and RF classifiers. In addition, the average producer’s accuracies of 95% and 96% were achieved by the ML and RF classifiers, respectively, whereas the average user accuracy was 94% for both classifiers. The results indicated promising potentials for rapid and cost-effective local-scale crop-type classification using a limited number of high-resolution optical and multi-polarization SAR images. Very accurate classification results can be considered as a replacement for sampling the agricultural fields at the local scale. The result of this very accurate classification at discrete locations (approximately 25 × 25 km frames) can be applied in a separate procedure to increase the accuracy of crop area estimation at the regional to provincial scale by linking these local very accurate spatially discrete results to national wall-to-wall continuous crop classification maps.     

CD36+ Fibroblasts Secrete Protein Ligands That Growth-Suppress Triple-Negative Breast Cancer Cells While Elevating Adipogenic Markers for a Model of Cancer-Associated Fibroblast

Tumor and stroma coevolve to facilitate tumor growth. Hence, effective tumor therapeutics would not only induce growth suppression of tumor cells but also revert pro-tumor stroma into anti-tumoral type. Previously, we showed that coculturing triple-negative or luminal A breast cancer cells with CD36⁺ fibroblasts (FBs) in a three-dimensional extracellular matrix induced their growth suppression or phenotypic reversion, respectively. Then, we identified SLIT3, FBLN-1, and PENK as active protein ligands secreted from CD36⁺ FBs that induced growth suppression of MDA-MB-231 breast cancer cells and determined their minimum effective concentrations. Here, we have expanded our analyses to include additional triple-negative cancer cell lines, BT549 and Hs578T, as well as HCC1937 carrying a BRCA1 mutation. We show that the ectopic addition of each of the three ligands to cancer-associated fibroblasts (CAFs) elevates the expression of CD36, as well as the adipogenic marker FABP4. Lastly, we show that an agonist antibody for one of the PENK receptors induces growth suppression of all cancer cell lines tested but not for non-transformed MCF10A cells. These results clearly suggest that proteins secreted from CD36⁺ FBs induce not only growth suppression of tumor cells through binding the cognate receptors but also increasing adipogenic markers of CAFs to reprogram tumor stroma.     

A stabilized foam formulation using FTP-SDS surfactants for wettability alteration and flow diversion in carbonate fractured oil reservoirs

Foam injection contributes to improved oil recovery through flow diversion, reduction of interfacial tension (IFT), and wettability alteration of the rock while its stability is an issue. In this article, nitrogen-foam was optimally formulated using fluorocarbon tubiguard protect (FTP) surfactant stabilized with sodium dodecyl sulfate (SDS) co-surfactant that was later experimentally considered for oil recovery in a fractured carbonate rock taken from an oil field in the Middle East. The results showed that the 5:1 volume ratio of fluorocarbon surfactant and SDS (FS51) generates a stable foaming agent with ability of changing the wettability of the carbonate rock surfaces to an intermediate gas-wet state. A series of core-flood experiments at HPHT conditions were also carried out and designed to properly represent matrix-fracture media using both a horizontally and vertically oriented setup. The oil saturated cores were flooded with nitrogen gas first followed by foam injection. It was concluded that foam can divert the gas to flow from fractures to the matrix blocks and result in a significant oil recovery. The contact angle tests that performed after core-flood experiments revealed the wettability changes of fracture surfaces from an oil-wet to a gas-wet state. This allows gas to be imbibed into the matrix blocks by capillary force and results in enhancement of ultimate oil recovery. This study revealed that trapped oil in matrixes blocks that had not been drained during the gas injection process could be produced by designing a stable foam that sustainably diverts injected fluid from fractures to matrix zone.     

Retraction Note: A new structure and modeling of a three-axis MEMS capacitive accelerometer with high dynamic range and sensitivity

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