Midpalatal Suture Density CBCT Evaluation, Sex Gender and Growth Pattern Related Variability in 392 Adolescents Treated With Rapid Maxillary Expander Appliance

The aim of this paper was to evaluate the changes in the mean bone density values of the midpalatal suture in 392 young patients treated with the Rapid Palatal Expander appliance according to sex, gender, vertical and sagittal skeletal patterns. Materials and Methods. The evaluations were performed using the low-dose protocol cone-beam computed tomography scans at t0 (preoperatively) and t1 (1 year after the beginning of the therapy). The region of interest was used to calculate bone density in Hounsfield units (HU) in the area between the maxillary incisors. Results. CBCT scan data of 196 females and 196 males (mean age of 11,7 years) showed homogeneous and similar density values of the MPS at T0 (547.59 HU - 565.85 HU) and T1 (542.31 - 554.20 HU). Class III skeletal individuals showed a significant higher BD than the II class group at T0, but not at T1. Females showed significantly higher BD than males at t0 and t1. No significant differences were found between the other groups and between two-time points in terms of bone density values of the MPS. Conclusions. Females and III class groups showed significantly higher bone density values than males and II class, respectively. No statistically significant differences were found from T0 to T1 in any groups, suggesting that a similar rate of suture reorganization occurs after the use of the RPE, following reorganization and bone deposition along with the MPS.

An application of neighbourhoods in digraphs to the classification of binary dynamics

A binary state on a graph means an assignment of binary values to its vertices. A time dependent sequence of binary states is referred to as binary dynamics. We describe a method for the classification of binary dynamics of digraphs, using particular choices of closed neighbourhoods. Our motivation and application comes from neuroscience, where a directed graph is an abstraction of neurons and their connections, and where the simplification of large amounts of data is key to any computation. We present a topological/graph theoretic method for extracting information out of binary dynamics on a graph, based on a selection of a relatively small number of vertices and their neighbourhoods. We consider existing and introduce new real-valued functions on closed neighbourhoods, comparing them by their ability to accurately classify different binary dynamics. We describe a classification algorithm that uses two parameters and sets up a machine learning pipeline. We demonstrate the effectiveness of the method on simulated activity on a digital reconstruction of cortical tissue of a rat, and on a non-biological random graph with similar density.

Tunable X-ray dark-field imaging for sub-resolution feature size quantification in porous media

X-ray computed micro-tomography typically involves a trade-off between sample size and resolution, complicating the study at a micrometer scale of representative volumes of materials with broad feature size distributions (e.g. natural stones). X-ray dark-field tomography exploits scattering to probe sub-resolution features, promising to overcome this trade-off. In this work, we present a quantification method for sub-resolution feature sizes using dark-field tomograms obtained by tuning the autocorrelation length of a Talbot grating interferometer. Alumina particles with different nominal pore sizes (50 nm and 150 nm) were mixed and imaged at the TOMCAT beamline of the SLS synchrotron (PSI) at eighteen correlation lengths, covering the pore size range. The different particles cannot be distinguished by traditional absorption µCT due to their very similar density and the pores being unresolved at typical image resolutions. Nevertheless, by exploiting the scattering behavior of the samples, the proposed analysis method allowed to quantify the nominal pore sizes of individual particles. The robustness of this quantification was proven by reproducing the experiment with solid samples of alumina, and alumina particles that were kept separated. Our findings demonstrate the possibility to calibrate dark-field image analysis to quantify sub-resolution feature sizes, allowing multi-scale analyses of heterogeneous materials without subsampling.

Contrasting Cryptocurrencies with Other Assets: Full Distributions and the COVID Impact

We investigate any similarity and dependence based on the full distributions of cryptocurrency assets, stock indices and industry groups. We characterize full distributions with entropies to account for higher moments and non-Gaussianity of returns. Divergence and distance between distributions are measured by metric entropies, and are rigorously tested for statistical significance. We assess the stationarity and normality of assets, as well as the basic statistics of cryptocurrencies and traditional asset indices, before and after the COVID-19 pandemic outbreak. These assessments are not subjected to possible misspecifications of conditional time series models which are also examined for their own interests. We find that the NASDAQ daily return has the most similar density and co-dependence with Bitcoin daily return, generally, but after the COVID-19 outbreak in early 2020, even S&P500 daily return distribution is statistically closely dependent on, and indifferent from Bitcoin daily return. All asset distances have declined by 75% or more after the COVID-19 outbreak. We also find that the highest similarity before the COVID-19 outbreak is between Bitcoin and Coal, Steel and Mining industries, and after the COVID-19 outbreak is between Bitcoin and Business Supplies, Utilities, Tobacco Products and Restaurants, Hotels, Motels industries, compared to several others. This study shed light on examining distribution similarity and co-dependence between cryptocurrencies and other asset classes.

Abstract MP36: Human Urinary Exosomes Contain Functional ACE2

The Ang II convertase and SARS-COV-2 co-receptor ACE2 is highly expressed on proximal tubules within the kidney. ACE2 is also present in urine and reportedly correlates with various renal pathologies that may reflect enhanced shedding of the peptidase through activation of ADAMs. Indeed, 95 kDa ACE2 is typically detected in urine consistent with a shorter, soluble form of the peptidase; however, the full-length, membrane-bound form of ACE2 (120 kDa) is also evident in urine which is difficult to reconcile with ACE2 shedding. To account for these isoforms, we evaluated ACE2 expression in exosomes isolated from human urine. Morning collections from males [50 to 64 years of age, non-smokers] were immediately processed for exosome isolation by cibacron blue binding of albumin followed by 0.2 μmicron filtration to remove microvesicles and apoptotic bodies, Amicon 100 kDa concentration, and ultracentrifugation (UC) to pellet exosomes. Analysis of the UC pellet fraction revealed the exosomal markers ALIX, CD63 and HSP70, as well as the proximal tubule peptidases neprilysin (NEP) and ACE2. Exosomal ACE2 content was 45 ± 11 ng/mL (mean ± SEM; N=5) by ELISA and exosomal activity hydrolyzed Ang II to Ang-(1-7) that was abolished by the ACE2 inhibitor MLN4760. Fluorescent nanotracking analysis (f-NTA) with Alexa Fluor antibodies and CellMask Deep Red membrane stain (CMDR) demonstrate a similar density of ACE2+ and NEP+ exosomes that were ~50% of total urinary exosomes (*P<0.05 vs. CD63+, N=3) while particle sizes were comparable and in the expected range of exosomes (100-150 nm). We conclude that human urinary exosomes express functional ACE2 which may originate from proximal tubule release.

Light, strong, and stable nanoporous aluminum with native oxide shell

Aluminum (Al) metal is highly reactive but has excellent corrosion resistance because of the formation of a self-healing passive oxide layer on the surface. Here, we report that this native aluminum oxide shell can also stabilize and strengthen porous Al when the ligament (strut) size is decreased to the submicron or nanometer scale. The nanoporous Al with native oxide shell, which is a nanoporous Al-Al2O3 core-shell composite self-organized in a galvanic replacement reaction, is nonflammable under ambient conditions and stable against coarsening near melting temperatures. This material is stronger than conventional foams of similar density consisting of pure Al or Al-based composites, and also lighter and stronger than most nanoporous metals reported previously. Its light weight, high strength, and excellent stability warrant the explorations of functional and structural applications of this material, if more efficient and scalable synthesis processes are developed in the future.

Cuttings Transport With Oil- and Water-Based Drilling Fluids

Deviated well sections are common in modern well construction. In mature areas like the North Sea region, practically all producers or injector wells will have highly deviated sections. These wells must be drilled and completed in an optimal manner with respect to drill time, cost, risk and functionality. Most cuttings transport and hydraulic models are developed based on tests with model fluids and often in small diameter test sections. Hole cleaning properties and hydraulic behaviour of field fluids differ from those of most model fluids. Furthermore, results from small diameter tests may not always be relevant for, nor scalable to, field applications due to time, length and other scale differences. Hence, there is a need for studies in controlled laboratory environments with various field application designed drilling fluids to improve engineering models and practices. This paper presents results from laboratory tests using field applied fluids. The drilling fluids have similar density and viscosity within the relevant shear rate range applied during drilling operations and in the tests. One of the fluids is oil-based and the other one is an inhibitive water-based drilling fluid.

Dynamic Analysis of Machine Foundation with and without Geosynthetic Reinforced Soil Beds

Most of the machine foundations are located in the regions with poorly graded soil including loose sand. Hence, the experimental studies are undertaken to evaluate the dynamic parameters of geosynthetics using cyclic PLT. This paper presents the results of the 10 m2 area of the model cyclic plate load test conducted on geosynthetics reinforced soil beds with similar density, supporting square footing, the results of cyclic PLT from the laboratory-model tests on square footings resting on a sand bed. The various intensity of cyclic load (loading-unloading) applying on the footing and then the elastic recovery of the footing alike to each intensity of loading obtains during the tests to determine the coefficient of elastic uniform compression (Cu) of sand. Results showes that the provision of geosynthetics like geogrid and jute the value of Cu decreases due to elastic recovery increases as compared to unreinforced soil bed, by 06% to 94% and natural frequency 03% to 76% . Introduction of planer geogrid at the base of the geosynthetic matress not only enhance the load carrying capacity but also increasing the elastic recovery to making them more elastic and prevents footing to failure due to vibration. In addition to the experiments also analyses various dynamic parameters of the machine foundation using cyclic PLT on the geosynthetics

A strong statistical link between aerosol indirect effects and the self-similarity of rainfall distributions

We use convective-scale simulations of monsoonal clouds to reveal a self-similar probability density function that underpins surface rainfall statistics. This density is independent of cloud-droplet number concentration and is unchanged by aerosol perturbations. It therefore represents an invariant property of our model with respect to cloud-aerosol interactions. For a given aerosol concentration, if the dependence of at least one moment of the rainfall distribution on cloud-droplet number is a known input parameter, then the self-similar density can be used to reconstruct the entire rainfall distribution to a useful degree of accuracy. In particular, we present both single-moment and double-moment reconstructions that are able to predict the responses of the rainfall distributions to changes in aerosol concentration. In doing so we show that the seemingly high-dimensional space of possible aerosol-induced rainfall-distribution transformations can be parametrized by a surprisingly small (at most three) independent “degrees of freedom”: the self-similar density, and auxiliary information about two moments of the rainfall distribution. This suggests that, although aerosol-indirect effects on any specific hydro-meteorological system may be multifarious in terms of rainfall changes and physical mechanisms, there may, nevertheless, be a universal constraint on the number of independent degrees of freedom needed to represent the dependencies of rainfall on aerosols.