Developing Intensity-Duration-Frequency (IDF) Curves From Satellite-Based Precipitation: Methodology and Evaluation

Given the continuous advancement in the retrieval of precipitation from satellites, it is important to develop methods that incorporate satellite-based precipitation data sets in the design and planning of infrastructure. This is because in many regions around the world, in situ rainfall observations are sparse and have insufficient record length. A handful of studies examined the use of satellite-based precipitation to develop intensity-duration-frequency (IDF) curves; however, they have mostly focused on small spatial domains and relied on combining satellite-based with ground-based precipitation data sets. In this study, we explore this issue by providing a methodological framework with the potential to be applied in ungauged regions. This framework is based on accounting for the characteristics of satellite-based precipitation products, namely, adjustment of bias and transformation of areal to point rainfall. The latter method is based on previous studies on the reverse transformation (point to areal) commonly used to obtain catchment-scale IDF curves. The paper proceeds by applying this framework to develop IDF curves over the contiguous United States (CONUS); the data set used is Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks – Climate Data Record (PERSIANN-CDR). IDFs are then evaluated against National Oceanic and Atmospheric Administration (NOAA) Atlas 14 to provide a quantitative estimate of their accuracy. Results show that median errors are in the range of (17–22%), (6–12%), and (3–8%) for one-day, two-day and three-day IDFs, respectively, and return periods in the range (2–100) years. Furthermore, a considerable percentage of satellite-based IDFs lie within the confidence interval of NOAA Atlas 14

Computing with Memristor-based Nonlinear Oscillators

Among the recent disruptive technologies, volatile/nonvolatile memory-resistor (memristor) has attracted the researchers' attention as a fundamental computation element. It has been experimentally shown that memristive elements can emulate synaptic dynamics and are even capable of supporting spike timing dependent plasticity (STDP), an important adaptation rule for neuromorphic computing systems. The overall goal of this work is to provide an unconventional computing platform exploiting memristor-based nonlinear oscillators described by means of phase deviation equations. Experimental results show that the approach significantly outperforms conventional architectures used for pattern recognition tasks

Porosity measurements of interstellar ice mixtures using optical laser interference and extended effective medium approximations

Aims. This article aims to provide an alternative method of measuring the porosity of multi-phase composite ices from their refractive indices and of characterising how the abundance of a premixed contaminant (e.g., CO2) affects the porosity of water-rich ice mixtures during omni-directional deposition. Methods. We combine optical laser interference and extended effective medium approximations (EMAs) to measure the porosity of three astrophysically relevant ice mixtures: H2O:CO2=10:1, 4:1, and 2:1. Infrared spectroscopy is used as a benchmarking test of this new laboratory-based method. Results. By independently monitoring the O-H dangling modes of the different water-rich ice mixtures, we confirm the porosities predicted by the extended EMAs. We also demonstrate that CO2 premixed with water in the gas phase does not significantly affect the ice morphology during omni-directional deposition, as long as the physical conditions favourable to segregation are not reached. We propose a mechanism in which CO2 molecules diffuse on the surface of the growing ice sample prior to being incorporated into the bulk and then fill the pores partly or completely, depending on the relative abundance and the growth temperature.Comment: 9 pages, 6 figures, 1 table. Accepted for publication in A&

PLA scaffolds production from Thermally Induced Phase Separation: effect of process parameters and development of an environmentally improved route assisted by supercritical carbon dioxide

In this work, a relatively large scale of PLA scaffolds was produced using thermally induced phase separation (TIPS) combined with a supercritical carbon dioxide (SC-CO2) drying step as a green alternative. For the TIPS step, the phase separation of PLA and 1,4-dioxane solvent was controlled by adjusting the process conditions such as the polymer concentration and molecular weight, the 1,4-dioxane solvent power and the cooling conditions. The scaffolds morphology was analyzed by scanning electron microscopy. Their structural and mechanical properties were correlated together with the possibility to tune them by controlling the process conditions. An environmental analysis using the Life Cycle Assessment (LCA) methodology confirmed a reduction of at least 50% of the environmental impact of the whole process using the SC-CO2 drying compared to the traditional freeze-drying technology. This work is the first known attempt to conduct the LCA methodology on TIPS process for the PLA scaffolds production

Recurrent Primary Intrasellar Paraganglioma

We describe a case of an 81-year-old male presenting with bitemporal visual field defects and blurry vision in the right eye. The patient was found to have a recurrent primary paraganglioma in the sellar and suprasellar region requiring a repeat transsphenoidal endoscopic resection. Immunohistochemical examination confirmed paraganglioma with the classic zellballen appearance which stained positive for chromogranin, synaptophysin, and S-100 in the periphery. Paragangliomas (PGLs) in the sella turcica are a rare entity; only 19 cases have ever been reported in the literature. PGLs in the sellar region are often misdiagnosed or diagnosed in a delayed fashion. Earlier diagnosis of this locally aggressive tumor and meticulous debulking can prevent morbidity secondary to the tumor's compressive effects. This report highlights the effectiveness of surgical interventions in treatment of paragangliomas. More research is still needed to determine the need for adjuvant therapies such as radiation

RSAT™ process development for post-combustion CO2 capture: Scale-up from laboratory and pilot test data to commercial process design

AbstractIt is believed that a RSAT™ (Regenerable Solvent Absorption Technology) process is the most viable nearterm technology for post-combustion CO2 capture from power plant flue gas. The Babcock & Wilcox Power Generation Group, Inc. (B&W) has deployed a suite of research tools to evaluate and develop the CO2 scrubbing technology, including laboratory, pilot-scale, and simulation modeling capabilities. Since the construction and operation of test facilities require significant resources, it is essential to effectively utilize these research tools by choosing a scale-up approach which provides robust design data for a commercial process while minimizing the amount of experimentation required.The scale-up protocol used for RSAT CO2 scrubbing processes was rigorously developed using rate-based modeling concurrent with acquiring fundamental laboratory and pilot plant data for process validation. These development activities were not conducted in series but rather overlapped to yield an optimized commercial CO2 scrubbing process in a reasonable time frame with a high degree of design confidence [1,2].This paper presents the scale-up protocol used in evaluating the RSAT process which encompasses both laboratory and pilot-scale testing as well as rate-based modeling to achieve a commercial-scale RSAT process design. This document demonstrates the qualification of test data from a packed tower scale-up point of view. Solvent screening research activities recently conducted within B&W successfully demonstrate the scale-up protocol used for RSAT process development. The time and cost of process development can be significantly reduced through rigorous rate-based modeling in conjunction with laboratory experiments and pilot plant validation

Multimodal Brain Changes in First-Episode Mania: A Voxel-Based Morphometry, Functional Magnetic Resonance Imaging, and Connectivity Study

Background: Brain structural and functional changes in bipolar disorder (BD) are well-established findings, but it is uncertain whether these changes are already present in first episode mania (FEM). Methods: We compared 31 FEM subjects, with 31 healthy individuals matched for age, sex, and premorbid IQ. Whole-brain voxel-wise morphometry, functional magnetic resonance imaging during the n-back task, and a functional connectivity analysis were performed. Results: There were no volumetric differences between the 2 groups. During the 2-back task, FEM patients did not perform differently from controls and activated similar regions, but they showed less deactivation in the ventromedial prefrontal cortex (vmPFC), the anterior hub of the default mode network (DMN). They showed preserved functional connectivity between the vmPFC and other regions of the DMN, but increased connectivity with the superior frontal gyrus. Conclusions: The absence of volumetric changes in FEM patients suggests that these changes could be related to progression of the illness. On the other hand, the failure of deactivation of the anterior hub of the DMN is present from the onset of the illness and may represent a core pathophysiological feature of BD

The UK Crop Microbiome Cryobank: a utility and model for supporting Phytobiomes research

Plant microbiomes are the microbial communities essential to the functioning of the phytobiome—the system that consist of plants, their environment, and their associated communities of organisms. A healthy, functional phytobiome is critical to crop health, improved yields and quality food. However, crop microbiomes are relatively under-researched, and this is associated with a fundamental need to underpin phytobiome research through the provision of a supporting infrastructure. The UK Crop Microbiome Cryobank (UKCMC) project is developing a unique, integrated and open-access resource to enable the development of solutions to improve soil and crop health. Six economically important crops (Barley, Fava Bean, Oats, Oil Seed Rape, Sugar Beet and Wheat) are targeted, and the methods as well as data outputs will underpin research activity both in the UK and internationally. This manuscript describes the approaches being taken, from characterisation, cryopreservation and analysis of the crop microbiome through to potential applications. We believe that the model research framework proposed is transferable to different crop and soil systems, acting not only as a mechanism to conserve biodiversity, but as a potential facilitator of sustainable agriculture systems