Vertical wind tunnel experiments and a theoretical study on the microphysics of melting low-density graupel

Vertical wind tunnel experiments were carried out to investigate the melting of low-density lump graupel while floating at their terminal velocities. The graupel characteristics such as maximum dimension, density, and axis ratio, were 0.39 ± 0.06 cm, 0.41 ± 0.07 g cm−3, and 0.89 ± 0.06. The air stream of the wind tunnel was gradually heated simulating lapse rates between 4.5 K km−1 and 3.21 K km−1. Each experimental run was performed at a constant relative humidity that was varied between 12 % and 92 % from one experiment to the other. From the image processing of video recordings, variations in minimum and maximum dimension, volume, aspect ratio, density, volume equivalent radius, and ice core radius were obtained. New parameterizations of the terminal velocity prior to melting and during melting were developed. It was found that mass and heat transfer in the dry stage is two times higher compared to that of liquid drops at the same Reynolds number. Based on the experimental results a model was developed from which the external and internal convective enhancement factors during melting due to surface irregularities and internal motions inside the melt water were derived using a Monte Carlo approach. The modelled total melting times and distances deviated by 10 % from the experimental results. Sensitivity tests with the developed model revealed strong dependencies of the melting process on relative humidity, lapse rate, initial graupel density, and graupel size. In dependence on these parameters, the total melting distance varied between 600 m and 1200 m for typical conditions of a falling graupel.

Mass of different snow crystal shapes derived from fall speed measurements

Meteorological forecast and climate models require good knowledge of the microphysical properties of hydrometeors and the atmospheric snow and ice crystals in clouds, for instance, their size, cross-sectional area, shape, mass, and fall speed. Especially shape is an important parameter in that it strongly affects the scattering properties of ice particles and consequently their response to remote sensing techniques. The fall speed and mass of ice particles are other important parameters for both numerical forecast models and the representation of snow and ice clouds in climate models. In the case of fall speed, it is responsible for the rate of removal of ice from these models. The particle mass is a key quantity that connects the cloud microphysical properties to radiative properties. Using an empirical relationship between the dimensionless Reynolds and Best numbers, fall speed and mass can be derived from each other if particle size and cross-sectional area are also known. In this study, ground-based in situ measurements of snow particle microphysical properties are used to analyse mass as a function of shape and the other properties particle size, cross-sectional area, and fall speed. The measurements for this study were done in Kiruna, Sweden, during snowfall seasons of 2014 to 2019 and using the ground-based in situ Dual Ice Crystal Imager (D-ICI) instrument, which takes high-resolution side- and top-view images of natural hydrometeors. From these images, particle size (maximum dimension), cross-sectional area, and fall speed of individual particles are determined. The particles are shape-classified according to the scheme presented in our previous study, in which particles sort into 15 different shape groups depending on their shape and morphology. Particle masses of individual ice particles are estimated from measured particle size, cross-sectional area, and fall speed. The selected dataset covers sizes from about 0.1 to 3.2 mm, fall speeds from 0.1 to 1.6 m s−1, and masses from 0.2 to 450 µg. In our previous study, the fall speed relationships between particle size and cross-sectional area were studied. In this study, the same dataset is used to determine the particle mass, and consequently, the mass relationships between particle size, cross-sectional area, and fall speed are studied for these 15 shape groups. Furthermore, the mass relationships presented in this study are compared with the previous studies. For certain crystal habits, in particular columnar shapes, the maximum dimension is unsuitable for determining Reynolds number. Using a selection of columns, for which the simple geometry allows the verification of an empirical Best-number-to-Reynolds-number relationship, we show that Reynolds number and fall speed are more closely related to the diameter of the basal facet than the maximum dimension. The agreement with the empirical relationship is further improved using a modified Best number, a function of an area ratio based on the falling particle seen in the vertical direction.

Assessing fall velocity-maximum dimension relationships and particle size distributions for snowfall

Snowfall is an atmospheric phenomenon that can cause significant impacts to many aspects of daily life in Missouri. Further, no two snowfall events are exactly the same, as even small differences in environmental characteristics can result in differing snow crystal types dominating the event, which in turn can result in differing impacts from event to event. Therefore, it is necessary to understand snowfall behavior so that better forecasts and in situ analyses may be made. In this study, snowflake maximum dimension and fall velocity measurements were recorded using the OTT Parsivel Laser Disdrometer. In conjunction with distribution of measured maximum dimensions, RAP Analysis soundings were used to determine snow crystal type. From there, the relationships between fall velocity and maximum dimension and the particle size distributions of snowflakes from many snowfall events were analyzed. Observed relationships between fall velocity and maximum dimension were compared with previously derived relationships, and it was found that, in most cases, no single curve represented the relationship in the observed data well, with discrepancies caused by instrumentation error and lack of a single dominant crystal type. To analyze particle size distributions, several distribution functions were fit to the observed distribution using a least-squares regression method in MATLAB. It was found that, overall, the triple Gaussian distribution function performed the best in modeling particle size distributions in snow, but there were some instances where the gamma function modeled the distribution best. Further study, especially with the inclusion of field observations in addition to instrument observations, is necessary to develop a better understanding of these snowfall events.

SCALE-INVARIANT AND WAVE NATURE OF THE HUBBLE PARAMETER

The value of the global Hubble parameter corresponding to astrophysical observations was determined theoretically without using ʌСDM models. A nonlinear fractal model of the connection between the distance to the observed galaxy and its coordinate is proposed. Distance is defined as a fractal measure, the measurement scale of which, in contrast to the known fractal models, corresponds to the deviation of the desired measure itself from its fixed value (radius of zero gravity), relative to which the scale invariance is assumed. We used the dimension of our proposed specific anisotropic fractal, which simulates the increase in the distance to the observation point. It is shown that this dimension is also the maximum dimension of the strange attractor of the phase portrait of the equation of gravitational waves and sets of galaxies from different catalogs.

A Nomogram for Preoperatively Predicting the Ki-67 Index of a Pituitary Tumor: A Retrospective Cohort Study

BackgroundThe Ki-67 index is an indicator of proliferation and aggressive behavior in pituitary adenomas (PAs). This study aims to develop and validate a predictive nomogram for forecasting Ki-67 index levels preoperatively in PAs.MethodsA total of 439 patients with PAs underwent PA resection at the Department of Neurosurgery in Jinling Hospital between January 2018 and October 2020; they were enrolled in this retrospective study and were classified randomly into a training cohort (n = 300) and a validation cohort (n = 139). A range of clinical, radiological, and laboratory characteristics were collected. The Ki-67 index was classified into the low Ki-67 index (<3%) and the high Ki-67 index (≥3%). Least absolute shrinkage and selection operator algorithm and uni- and multivariate logistic regression analyses were applied to identify independent risk factors associated with Ki-67. A nomogram was constructed to visualize these risk factors. The receiver operation characteristic curve and calibration curve were computed to evaluate the predictive performance of the nomogram model.ResultsAge, primary-recurrence subtype, maximum dimension, and prolactin were included in the nomogram model. The areas under the curve (AUCs) of the nomogram model were 0.694 in the training cohort and 0.658 in the validation cohort. A well-fitted calibration curve was also generated for the nomogram model. A subgroup analysis revealed stable predictive performance for the nomogram model. A correlation analysis revealed that age (R = −0.23; p < 0.01), maximum dimension (R = 0.17; p < 0.01), and prolactin (R = 0.16; p < 0.01) were all significantly correlated with the Ki-67 index level.ConclusionsAge, primary-recurrence subtype, maximum dimension, and prolactin are independent predictors for the Ki-67 index level. The current study provides a novel and feasible nomogram, which can further assist neurosurgeons to develop better, more individualized treatment strategies for patients with PAs by predicting the Ki-67 index level preoperatively.

Environmental and Radar Characteristics of Gargantuan Hail-Producing Storms

Storms that produce gargantuan hail (defined here as ≥ 6 inches or 15 cm in maximum dimension), although seemingly rare, can cause extensive damage to property and infrastructure, and cause injury or even death to humans and animals. Currently, we are limited in our ability to accurately predict gargantuan hail and detect gargantuan hail on radar. In this study, we analyze the environments and radar characteristics of gargantuan hail-producing storms to define the parameter space of environments in which gargantuan hail occurs, and compare environmental parameters and radar signatures in these storms to storms producing other sizes of hail. We find that traditionally used environmental parameters used for severe storms prediction, such as most unstable convective available potential energy (MUCAPE) and 0–6 km vertical wind shear, display considerable overlap between gargantuan hail-producing storm environments and those that produce smaller hail. There is a slight tendency for larger MUCAPE values for gargantuan hail cases, however. Additionally, gargantuan hail-producing storms seem to have larger low-level storm-relative winds and larger updraft widths than those storms producing smaller hail, implying updrafts less diluted by entrainment and perhaps maximizing the liquid water content available for hail growth. Moreover, radar reflectivity or products derived from it are not different from cases of smaller hail sizes. However, inferred mesocyclonic rotational velocities within the hail growth region of storms that produce gargantuan hail are significantly stronger than the rotational velocities found for smaller hail categories.

Shape dependence of snow crystal fall speed

Improved snowfall predictions require accurate knowledge of the properties of ice crystals and snow particles, such as their size, cross-sectional area, shape, and fall speed. The fall speed of ice particles is a critical parameter for the representation of ice clouds and snow in atmospheric numerical models, as it determines the rate of removal of ice from the modelled clouds. Fall speed is also required for snowfall predictions alongside other properties such as ice particle size, cross-sectional area, and shape. For example, shape is important as it strongly influences the scattering properties of these ice particles and thus their response to remote sensing techniques. This work analyzes fall speed as a function of particle size (maximum dimension), cross-sectional area, and shape using ground-based in situ measurements. The measurements for this study were done in Kiruna, Sweden, during the snowfall seasons of 2014 to 2019, using the ground-based in situ instrument Dual Ice Crystal Imager (D-ICI). The resulting data consist of high-resolution images of falling hydrometeors from two viewing geometries that are used to determine particle size (maximum dimension), cross-sectional area, area ratio, orientation, and the fall speed of individual particles. The selected dataset covers sizes from about 0.06 to 3.2 mm and fall speeds from 0.06 to 1.6 m s−1. Relationships between particle size, cross-sectional area, and fall speed are studied for different shapes. The data show in general low correlations to fitted fall speed relationships due to large spread observed in fall speed. After binning the data according to size or cross-sectional area, correlations improve, and we can report reliable parameterizations of fall speed vs. particle size or cross-sectional area for part of the shapes. For most of these shapes, the fall speed is better correlated with cross-sectional area than with particle size. The effects of orientation and area ratio on the fall speed are also studied, and measurements show that vertically oriented particles fall faster on average. However, most particles for which orientation can be defined fall horizontally.

Breakthrough in purification of fossil pollen for dating of sediments by a new large-particle on-chip sorter

Particle sorting is a fundamental method in various fields of medical and biological research. However, existing sorting applications are not capable for high-throughput sorting of large-size (>100 micrometers) particles. Here, we present a novel on-chip sorting method using traveling vortices generated by on-demand microjet flows, which locally exceed laminar flow condition, allowing for high-throughput sorting (5 kilohertz) with a record-wide sorting area of 520 micrometers. Using an activation system based on fluorescence detection, the method successfully sorted 160-micrometer microbeads and purified fossil pollen (maximum dimension around 170 micrometers) from lake sediments. Radiocarbon dates of sorting-derived fossil pollen concentrates proved accurate, demonstrating the method’s ability to enhance building chronologies for paleoenvironmental records from sedimentary archives. The method is capable to cover urgent needs for high-throughput large-particle sorting in genomics, metabolomics, and regenerative medicine and opens up new opportunities for the use of pollen and other microfossils in geochronology, paleoecology, and paleoclimatology.

Radical Surgical Excision and Use of Axillary Flap for Intractable Axillary Hidradenitis Suppurativa

Background: Current treatments for hidradenitis suppurativa (HS) include prolonged courses of antibiotics, retinoids, immunosuppressants, and biologics. Severe cases that are resistant to prolonged medical treatment pose a therapeutic challenge. We propose radical excision and reconstruction with axillary flap as a treatment option for such cases. Objectives: The purpose of the study was to see the outcome after radical surgical excision and coverage with axillary flap for intractable Hidradenitis suppurativa. Methods: This prospective observational study was carried out from July, 2014 to June,2016. Patients admitted at the Plastic Surgery Department of Dhaka Medical College Hospital with intractable Hydradenitis suppurativa were included the study population. Result:Among 20 cases, 12 cases were female and 8 cases were male. Maximum dimension of the soft tissue defect was 15x6.5 cm2 = (97.5 cm2). Maximum dimension of the flap was 17x7 cm2 = (119 cm2).Flap survived completely with minimum donor site morbidity. Result of reconstruction of 90% of the patients exhibited excellent outcome. In 10% patient’s outcome was considered good. Conclusion:With a suitable flap coverage option, the management paradigm of intractable Hydradenitis Suppurativa should shift from prolonged medical treatment to allowdecisive radical excision, which will improve the quality of life for patients. Axilary flap is the flap of choice to cover the defect. Journal of Surgical Sciences (2020) Vol. 24 (2) : 51-56