Determining the Effects of Hailstone Impact on Flat Cold-Reduced Steel Roof Sheeting

Hail damage is responsible for significant economic losses in Australia, and the damage will likely be greater in the future due to increased incidence of severe hailstorms. One of the major costs comes from damaged roofs. Compared to the conventional asphalt shingle roofing and concrete tiled roofing, steel roofing is becoming popular due to its long service life, low maintenance cost, and better resistance to natural disasters. However, there is a lack of knowledge regarding the dent resistance of steel sheet to natural hailstone impact as a function of its yield stress and thickness. In the literature, either steel projectiles or ice balls are used as the artificial hailstones in the hail impact tests. However, there has been no study to correlate the indentation caused by a steel ball to that caused by a natural hailstone. On the other hand, the ice balls used by previous researchers shattered on impacting steel sheeting at velocities close to the terminal velocities of the natural hailstones, while some natural hailstones remain intact after impacting steel roof sheeting at their terminal velocities. When a hailstone remains intact on impact, more energy is available to damage the steel sheet. In this thesis, a new method to make water based artificial hailstones that remain intact after impacting flat steel roof sheeting at terminal velocities has been successfully developed with a combination of 88% water and 12% PVA (Polyvinyl alcohol). The indentation results of the present artificial hailstones have been validated against those of pure clear ice balls that happened to remain intact after impact at similar velocities. Five sheet thicknesses (0.35 mm, 0.42 mm, 0.55 mm, 0.75 mm and 1.00 mm) and two sheet steel grades (G300 and G550) are tested under the impact of five sizes of artificial hailstones (25 mm, 33 mm, 38 mm, 45 mm and 50.8 mm) at three designated impact velocities (20 m/s, 30 m/s, 40 m/s). Each sheeting is screwed to timber battens spaced at 600 mm from each other, and the projectile is aimed perpendicularly at the middle between the two battens. The dent depths caused by the PVA ice balls that remained intact after impact are significantly greater than those caused by the PVA ice balls that disintegrated upon impact. For the case involving intact artificial hailstones, the dent depth varies linearly with the square root of the impact energy, and is inversely proportional to the square roots of the sheet thickness and the yield stress. The findings (based on experimental observations and theoretical derivations) regarding the effects of the sheet thickness and the yield stress are believed to be original. Additional experimental findings are that the rebound energy of hailstones impacting steel roof sheeting is negligible (less than 1% of the impact energy), and that most energy loss of the impact energy is in the form of flexural vibration of the flat steel sheeting. Provided that denting takes place, the energy lost to flexural vibration is a function of the elastic flexural stiffness of the steel sheeting, and varies linearly with the impact energy. An empirical equation is proposed in this thesis to determine the proportion of impact energy that is lost to flexural vibration of the steel sheeting, based on the sheet thickness and the spacing between the battens. Once the flexural vibration energy and therefore the net impact energy is determined, the dent depth can be estimated from the sheet thickness and the yield stress under the assumption of a (partly) spherical dent

Radar-based Hail-producing Storm Detection Using Positive Unlabeled Classification

Machine learning methods have been widely used in many fields of weather forecasting. However, some severe weather, such as hailstorm, is difficult to be completely and accurately recorded. These inaccurate data sets will affect the performance of machine-learning-based forecasting models. In this paper, a weather-radar-based hail-producing storm detection method is proposed. This method utilizes the bagging class-weighted support vector machine to learn from partly labeled hail case data and the other unlabeled data, with features extracted from radar and sounding data. The real case data from three radars of North China are used for evaluation. Results suggest that the proposed method could improve both the forecast accuracy and the forecast lead time comparing with the commonly used radar parameter methods. Besides, the proposed method works better than the method with the supervised learning model in any situation, especially when the number of positive samples contaminated in the unlabeled set is large

Templando almas codiciosas en lagos de metal: Una imagen metalúrgica en la visión del más allá de Tespesio (Plutarco, De sera num. 30 567c-d)

Plutarch’s theological dialogue De sera numinis vindicta ends with an eschatological myth narrating the afterlife vision of Thespesius (22-33, 563b-568a), centred on the souls’ “purification” from their earthly vices – obtained by means of punishments – and on the process of their reincarnation. This myth includes symbolic images of metallurgic interest. The most elaborate of these corresponds to the description of the chastisement of the “insatiable” and “greedy” souls, which are cyclically immersed into lakes of gold, lead, and iron, enduring painful transformations in each lake (30, 567c-d). This article focuses on the analysis of the implications and literary genesis of this scene, in the frame of the rest of the myth and of the dialogic part of De sera num., of Plutarch’s ethical and scientific ideas, of his culture, and of the tendencies of his metaphorical and analogical prose (as evidenced by his other works). It begins with an introduction to Plutarch’s religious thought and use of Platonic myths, defending the assumption that these should be treated as non-literal “enigmatic” tales and thus interpreted symbolically. A section is then dedicated to the narrative frame of Thespesius’s vision – the story of the moral conversion of an unscrupulously hedonist and greedy man – and to Plutarch’s symbolic presentation of the stains of vice (26, 565b-d), each associated with a colour, focusing on the stain of “miserliness and greed”. After an overview of the other punishments witnessed by Thespesius, mainly to be interpreted as forms of contrapasso and exhibitions of the souls’ hidden, wicked selves, the analysis of Plutarch’s treatment of greed is completed with an extensive discussion of the scene of the metallic lakes. Previous scholarly treatments of the scene are also discussed, with a focus on those which connected it with alchemy. Considering a recently proposed comparison between Plutarch’s scene and some of the images used by the alchemist Zosimus in his allegorical dreams (MA X, XI, XII Mertens), the hypothesis of their affinity is explored with mainly negative results. However, a further hypothesis is suggested without full endorsement: namely, that the symbols used by Plutarch, like those used by Zosimus, were influenced by the aesthetics of Egyptian and/or Jewish religion in the syncretising environment of 1st-cent. CE Alexandria.El diálogo teológico de Plutarco De sera numinis vindicta termina con un mito escatológico que narra la visión del más allá de Tespesio (22-33, 563b-568a), centrada en la “purificación” de las almas de sus vicios terrenales – obtenido mediante castigos – y en el proceso de su reencarnación. Este mito incluye imágenes simbólicas de interés metalúrgico. La más elaborada de ellas corresponde a la descripción del castigo de las almas “insaciables” y “codiciosas”, que se sumergen cíclicamente en lagos de oro, plomo y hierro, sufriendo dolorosas transformaciones en cada lago (30, 567c-d). Este artículo se centra en el análisis de las implicaciones y génesis literaria de esta escena, en el marco del resto del mito y de la parte dialógica de De sera num., de las ideas éticas y científicas de Plutarco, de su cultura y de las tendencias de su prosa metafórica y analógica (como lo demuestran sus otras obras). Comienza con una introducción al pensamiento religioso de Plutarco y al uso de los mitos platónicos, defendiendo la suposición de que estos deben ser tratados como cuentos “enigmáticos” no literales y, por lo tanto, interpretados simbólicamente. Luego se dedica una sección al marco narrativo de la visión de Tespesio – la historia de la conversión moral de un hombre hedonista y codicioso sin escrúpulos – y a la presentación simbólica de Plutarco de las manchas del vicio (26, 565b-d), cada una asociada a un color, centrándose en la mancha de “la avaricia y la codicia”. Después de una descripción general de los otros castigos presenciados por Tespesio, principalmente interpretables como formas de contrapaso y exhibiciones del yo oculto y malvado de las almas, el análisis del tratamiento de Plutarco de la codicia se completa con una discusión extensa de la escena de los lagos metálicos. También se discuten los tratamientos académicos previos de la escena, con un enfoque en aquellos que la conectaron con la alquimia. A partir de una comparación propuesta recientemente entre la escena de Plutarco y algunas de las imágenes utilizadas por el alquimista Zósimo en sus sueños alegóricos (MA X, XI, XII Mertens), se explora la hipótesis de su afinidad con resultados mayoritariamente negativos. Sin embargo, se sugiere otra hipótesis sin respaldo total: a saber, que los símbolos utilizados por Plutarco, como los utilizados por Zósimo, fueron influenciados por la estética de la religión egipcia y/o judía en el entorno sincretizante de la Alejandría del I siglo d.C

Crowdsourcing of Twitter Social Media Data to Analyze the Hail Disaster in Surabaya

The purpose of this study is to describe the use of crowdsourcing data sources from social media, especially Twitter, in carrying out an initial analysis of an extreme weather event, in this case, hail which occurred in the city of Surabaya on February 21st, 2022. The method used in this study is data mining using data sourced from Twitter with the keywords "hujan AND es" (“Rain AND Ice”) . The initial data withdrawal was carried out twice. The first only pulled data from tweets sent from the Surabaya area and its surroundings, while the second pulled data from tweets sent from all locations. Tweet count aggregation and early tweet detection were used to estimate the time of occurrence. Extracting location data from tweets is used to map the location of the incident. Adding supporting data in the form of data on weather conditions at the time of the estimated event is carried out to enrich the information and validator information obtained through crowdsourcing on social media. Meteorological analysis was carried out at the incident's time and location based on the analysis's results using social media. The supporting data used in conducting meteorological analysis are data on air temperature, air humidity, wind speed at several locations of automatic weather stations. Based on Twitter data crowdsourcing, this study's results, hail in Surabaya on February 21st, 2022, occurred at around 14:50 Local Time (LT) and was located in the western part of Surabaya

Primary progressive aphasia : neuropsychological analysis and evolution

Tese de doutoramento, Ciências Biomédicas (Neurociências), Universidade de Lisboa, Faculdade de Medicina, 2015Frontotemporal lobar degeneration (FTLD) is the second leading cause of early-onset ( 2) revealed some clusters composed mostly by nonfluent or by semantic PPA cases. However, we could not evidence any group chiefly composed of logopenic PPA cases. Hence, findings obtained with the application of unsupervised data mining approaches do not clearly support a logopenic PPA. However further, supervised learning studies may indicate distinct results. Behaviour changes may occur early in PPA but the frequency of these symptoms across the three variants is still controversial. In the third study, 94 consecutive PPA patients (26 nonfluent, 36 semantic, 32 logopenic) underwent language and neuropsychological assessments. The presence of behavioural changes was ascertained by semi-structured informant-based interviews using the Blessed Dementia Rating Scale. Eighty-two percent of the cases endorsed at least one behaviour change. Nonfluent patients presented significantly more behaviour changes and scored more often (46.2%) the item “hobbies relinquished” when compared to logopenic patients. These differences in behaviour symptoms probably reflect distinct underlying neurodegenerative diseases. PPA is a neurodegenerative disorder with no effective pharmacological treatment. Cognition-based interventions are adequate alternatives, but their benefit has not been thoroughly explored. The aim of this last investigation was to study the effect of speech and language therapy (SLT) on naming ability in PPA. An open parallel prospective longitudinal study involving two centers was designed to compare patients with PPA submitted to SLT (1 h/week for 11 months, on average) with patients receiving no therapy. Twenty patients were enrolled and undertook baseline language and neuropsychological assessments; among them, 10 received SLT and 10 constituted an age- and education-matched historical control group. The primary outcome measure was the change in group mean performance on the Snodgrass and Vanderwart Naming Test between baseline and follow-up assessments. Intervention and control groups did not significantly differ on demographic and clinical variables at baseline. A mixed repeated measures ANOVA revealed a significant main effect of therapy (F(1,18) = 10.763; p = 0.005) on the performance on the Snodgrass and Vanderwart Naming Test. Although limited by a non-randomized open study design with a historical control group, the present study suggests that SLT may have a benefit in PPA, and it should prompt a randomized, controlled, rater-blind clinical trial. Conclusion: Despite the recent harmonization efforts, the delineation of certain PPA variants is still controversial. The present results show that neuropsychology is a key instrument not only for the clear definition of PPA subtypes but also for the study of the abnormal mechanisms and features underlying the main forms of PPA. Moreover, a neuropsychological approach to disease management seems to be feasible. Specifically, SLT emerges as an alternative and adequate approach to tackle the increasing language deficits experienced in all PPA phenotypes for some time. The emergence of promising disease-modifying therapies in the context of FTLD, in association with these cognitive-based interventions, will certainly be the future of PPA disease management

Primary progressive aphasia: six questions in search of an answer

Here, we review recent progress in the diagnosis and management of primary progressive aphasia—the language-led dementias. We pose six key unanswered questions that challenge current assumptions and highlight the unresolved difficulties that surround these diseases. How many syndromes of primary progressive aphasia are there—and is syndromic diagnosis even useful? Are these truly ‘language-led’ dementias? How can we diagnose (and track) primary progressive aphasia better? Can brain pathology be predicted in these diseases? What is their core pathophysiology? In addition, how can primary progressive aphasia best be treated? We propose that pathophysiological mechanisms linking proteinopathies to phenotypes may help resolve the clinical complexity of primary progressive aphasia, and may suggest novel diagnostic tools and markers and guide the deployment of effective therapies

Measuring Hydrometeors with a Precipitation Microphysical Characteristics Sensor: Calibration and Field Measurements

Aiming at the simultaneous measurement of the size, shape, and fall velocity of precipitation particles in the natural environment, we present here a new ground-based precipitation microphysical characteristics sensor (PMCS) based on the particle imaging velocimetry technology. The PMCS can capture autocorrelated images of precipitation particles by double-exposure in one frame, by which the size, axis ratio, and fall velocity of precipitation particles can be calculated. The PMCS is calibrated by a series of glass balls with certain diameters under varying light conditions, and a self-adaptive threshold method is proposed. The shape, axis ratio, and fall velocity of raindrops were calculated and discussed based on the field measurement results of PMCS. The typical shape of large raindrop is an oblate ellipsoid, the axis ratio of raindrops decreases linearly with the diameter, the fall velocity of raindrops approaches its asymptote, and the above observed results are in good agreement with the empirical models; the synchronous observation of a PMCS, an OTT PARSIVEL disdrometer, and a rain gauge shows that the PMCS is able to measure the rain intensity, accumulated rainfall, and drop size distribution with high accuracy. These results have validated the performance of PMCS

Mechanisms of auditory signal decoding in the progressive aphasias

The primary progressive aphasias (PPA) are a diverse group of neurodegenerative disorders that selectively target brain networks mediating language. The pathophysiology of PPA remains poorly understood, but emerging evidence suggests that deficits in auditory processing accompany and may precede language symptoms in these patients. In four studies, I have probed the pathophysiology of auditory signal decoding in patient cohorts representing all major PPA syndromes – nonfluent variant PPA (nfvPPA), semantic variant PPA (svPPA), and logopenic variant PPA (lvPPA) – in relation to healthy age-matched controls. In my first experiment, I presented sequences of spoken syllables manipulated for temporal regularity, spectrotemporal structure and entropy. I used voxel-based morphometry to define critical brain substrates for the processing of these attributes, identifying correlates of behavioural performance within a cortico-subcortical network extending beyond canonical language areas. In my second experiment, I used activation functional magnetic resonance imaging (fMRI) with the same stimuli. I identified network signatures of particular signal attributes: nfvPPA was associated with reduced activity in anterior cingulate for processing temporal irregularity; lvPPA with reduced activation of posterior superior temporal cortex for processing spectrotemporal structure; and svPPA with reduced activation of caudate and anterior cingulate for processing signal entropy. In my third experiment, I manipulated the auditory feedback via which participants heard their own voices during speech production. Healthy control participants spoke significantly less fluently under delayed auditory feedback, but patients with nfvPPA and lvPPA were affected significantly less. In my final experiment, I probed residual capacity for dynamic auditory signal processing and perceptual learning in PPA, using sinewave speech. Patients with nfvPPA and lvPPA showed severely attenuated learning to the degraded stimuli, while patients with svPPA showed intact early perceptual processing, but deficient integration of semantic knowledge. Together, these experiments represent the most concerted and comprehensive attempt to date to define the pathophysiology of auditory signal decoding in PPA

Klimawandel vor unserer Haustür: Wie sich unser Leben heute bereits verändert = Climate change at our doorstep: How our lives are already changing

DAS REKLIM JUBILÄUMSMAGAZIN berichtet in Geschichten und Bildern von der Themenvielfalt und den Ergebnissen des Forschungsverbundes und erläutert, wie die Wissenschaft im Dialog mit der Gesellschaft arbeitet, um Fragen unserer Zeit aufzugreifen. Lassen Sie sich begeistern! THE REKLIM ANNIVERSARY MAGAZINE reports, in stories and images, on the research network’s findings and broad range of focus areas. In addition, it demonstrates how the research community can and is working in dialogue with society in order to address the most pressing questions of our time. Check it out

Gridded Hail Nowcasting using UNets, Lightning Observations, and the Warn-on-Forecast System

Hailstorms cause around 1 billion dollars in damage across the United States each year. At least a portion of this cost is associated with the inability to protect personal assets from damage in the short window of time offered by a severe weather warning. To address this problem, we developed a nowcasting model that uses UNet style convolutional neural networks (CNNs) to produce gridded severe hail forecasts for the next hour. One of the advantages of machine learning models is their ability to fuse large quantities of data from traditionally disparate sources such as ground observations and model output to produce a forecast. To exploit this hybrid predictor potential, these models are trained on the high-resolution (3 km spatial, 5 min temporal) output from the Warn-on-Forecast System (WoFS) numerical weather prediction (NWP) ensemble and remote sensing observations from Vaisala’s NLDN lightning detection system. Maximum expected size of hail (MESH) from the gridded NEXRAD WSR-88D radar (GridRad) dataset is used as the model’s truth labels. In addition to traditional machine learning optimization techniques such as hyperparameter searches and predictive feature selection, several different UNet architectures are compared to obtain a better machine learning model. The high-resolution nature of this data enables strategies such as using time as an additional dimension in a 3D UNet. This 3D model is compared against the effectiveness of a traditional 2D UNet. Finally, both models are compared against HAILCAST and simple logistic regression trained on 2 to 5 km updraft helicity to investigate their effectiveness