Long-term hail risk assessment with deep neural networks

Hail risk assessment is necessary to estimate and reduce damage to crops, orchards, and infrastructure. Also, it helps to estimate and reduce consequent losses for businesses and, particularly, insurance companies. But hail forecasting is challenging. Data used for designing models for this purpose are tree-dimensional geospatial time series. Hail is a very local event with respect to the resolution of available datasets. Also, hail events are rare - only 1% of targets in observations are marked as "hail". Models for nowcasting and short-term hail forecasts are improving. Introducing machine learning models to the meteorology field is not new. There are also various climate models reflecting possible scenarios of climate change in the future. But there are no machine learning models for data-driven forecasting of changes in hail frequency for a given area. The first possible approach for the latter task is to ignore spatial and temporal structure and develop a model capable of classifying a given vertical profile of meteorological variables as favorable to hail formation or not. Although such an approach certainly neglects important information, it is very light weighted and easily scalable because it treats observations as independent from each other. The more advanced approach is to design a neural network capable to process geospatial data. Our idea here is to combine convolutional layers responsible for the processing of spatial data with recurrent neural network blocks capable to work with temporal structure. This study compares two approaches and introduces a model suitable for the task of forecasting changes in hail frequency for ongoing decades

A smoothing monotonic convergent optimal control algorithm for NMR pulse sequence design

The past decade has demonstrated increasing interests in using optimal control based methods within coherent quantum controllable systems. The versatility of such methods has been demonstrated with particular elegance within nuclear magnetic resonance (NMR) where natural separation between coherent and dissipative spin dynamics processes has enabled coherent quantum control over long periods of time to shape the experiment to almost ideal adoption to the spin system and external manipulations. This has led to new design principles as well as powerful new experimental methods within magnetic resonance imaging, liquid-state and solid-state NMR spectroscopy. For this development to continue and expand, it is crucially important to constantly improve the underlying numerical algorithms to provide numerical solutions which are optimally compatible with implementation on current instrumentation and at same time are numerically stable and offer fast monotonic convergence towards the target. Addressing such aims, we here present a smoothing monotonically convergent algorithm for pulse sequence design in magnetic resonance which with improved optimization stability lead to smooth pulse sequence easier to implement experimentally and potentially understand within the analytical framework of modern NMR spectroscopy

Исследование эффективности работы центробежно-ударного измельчителя фуражного зерна новой конструкции

Crushing feed grain involves hammer crushers, which are characterized by high specific energy consumption and its uneven fractional composition. It is possible to obtain high-quality shredded grain with less energy when using a centrifugal-impact crusher of the new design with a hole in the loading neck to supply the chopping chamber with additional air at a rate of up to 4.8 m/s. An additional hole provides a 1.8...13-time increase in the airspeed through the unloading neck when the rotor’s rotation frequency changes from 3,750 to 2,250 min–1, thereby enabling the timely evacuation of the shredded material from the crusher.The regression equations have been derived to determine the structural and regime parameters of the shredder, which ensure the maximal performance and minimal unit energy costs. The greatest impact on crusher productivity is exerted by the diameter of the sieve holes and the area of the bunker’s unloading window. The greatest effect on the specific energy intensity of the grinding process is exerted by the diameter of the sieve holes. The maximal performance of the crusher, 1,440 kg/h, and the minimal energy capacity, taking into consideration the achieved grinding degree, of 2.1 W∙s/(kg∙grinding degree unit), are observed when using a sieve with the holes’ diameter of 7 mm, the rotor’s rotation frequency of 3,500 min–1, and the maximally open unloading window of the bunker, at F=1.458 m2·10–3. The specific energy consumption for chopping barley is less by 1.22...1.89 times than that of the hammer crushers RVO 35, DB-5, KD-2A. The dust-like fraction is less than 5.74 %, which is half the amount of the hammer crusher DM-6. The rational crusher operation modes have been determined in order to prepare feed grain for feeding farm animals of different species and agesДля измельчения фуражного зерна используют молотковые дробилки, которым свойственны высокий удельный расход энергии и его неравномерный фракционный состав. Получение качественно измельченного зерна с меньшими энергозатратами возможно на центробежно-ударном измельчителе новой конструкции с отверстием в загрузочной горловине для дополнительной подачи воздуха в камеру измельчения со скоростью до 4,8 м/с. Дополнительное отверстие обеспечивает повышение скорости воздуха в выгрузной горловине в 1,8…13 раз при изменении частоты вращения ротора с 3750 до 2250 мин-1, своевременную эвакуацию измельченного материала из измельчителя.Получены уравнения регрессии, позволяющие определить конструкционные и режимные параметры измельчителя, обеспечивающие максимум производительности и минимум удельных энергозатрат. Наибольшее влияние на производительность измельчителя оказывают диаметр отверстий решет и площадь выгрузного окна бункера. Наибольшее влияние на удельную энергоемкость процесса измельчения оказывает диаметр отверстий решета. Максимальная производительность измельчителя – 1440 кг/ч и минимальная энергоёмкость с учетом достигнутой степени измельчения 2,1 Вт∙с/(кг∙ед.ст.изм.) наблюдается при использовании решета с диаметром отверстий 7 мм, частоте вращения ротора 3500 мин-1 имаксимально открытом выгрузном окне бункера при F=1,458 м2·10-3. Удельный расход энергии на измельчение ячменя меньше в 1,22…1,89 раза, чем у молотковых дробилок RVO 35, ДБ-5, КД-2А. Содержание пылевидной фракции составляет менее 5,74 %, что в 2 раза меньше, по сравнению с молотковой дробилкой ДЗМ-6. Определены рациональные режимы работы измельчителя для подготовки фуражного зерна к скармливанию для сельскохозяйственных животных различных видов и возрасто

Алгоритм и технические решения динамического конфигурирования клиент-серверных вычислительных сетей

Проанализированы основные факторы, обуславливающие расширение возможностей и повышение результативности сетевой разведки по идентификации состава и структуры клиент-серверных вычислительных сетей вследствие стационарности их структурно-функциональных характеристик. Вскрытые особенности защиты клиент-серверных вычислительных сетей, основанных на реализации принципов пространственного обеспечения безопасности, а также формализация и внедрение множества запрещающих регламентов обосновывают актуальность задачи динамического управления структурно-функциональными характеристиками клиент-серверных вычислительных сетей, функционирующих в условиях сетевой разведки. Представлена математическая модель, позволяющая находить оптимальные режимы динамического конфигурирования структурно-функциональных характеристик клиент-серверных вычислительных сетей для различных ситуаций. Приведены результаты расчетов. Представлен алгоритм решения задачи динамической конфигурации структурно-функциональных характеристик клиент-серверной вычислительной сети, обеспечивающий уменьшение времени достоверности добываемых сетевой разведкой данных. Показаны результаты практических испытаний разработанного на основе алгоритма динамического конфигурирования клиент-серверных вычислительных сетей программного обеспечения. Полученные результаты свидетельствуют, что использование представленного решения по динамическому конфигурированию клиент-серверных вычислительных сетей позволяет повысить результативность защиты за счет изменения структурно-функциональных характеристик клиент-серверных вычислительных сетей в рамках нескольких подсетей. При этом достигнуто поддержание критически важных соединений, а интервалы времени изменения структурно-функциональных характеристик адаптивны к условиям функционирования и действиям злоумышленника. Новизна разработанной модели заключается в применении математического аппарата теории марковских случайных процессов и решении уравнений Колмогорова для обоснования выбора режимов динамического конфигурирования структурно-функциональных характеристик клиент-серверных вычислительных сетей. Новизна разработанного алгоритма состоит в применении модели динамического конфигурирования структурно-функциональных характеристик клиент-серверных вычислительных сетей для динамического управления структурно-функциональными характеристиками клиент-серверной вычислительной сети в условиях сетевой разведки

Transparent and flexible, nanostructured and mediatorless glucose/oxygen enzymatic fuel cells

Here we detail transparent, flexible, nanostructured, membrane-less and mediator-free glucose/oxygen enzymatic fuel cells, which can be reproducibly fabricated with industrial scale throughput. The electrodes were built on a biocompatible flexible polymer, while nanoimprint lithography was used for their nanostructuring. The electrodes were covered with gold, their surfaces were visualised using scanning electron and atomic force microscopies, and they were also studied spectrophotometrically and electrochemically. The enzymatic fuel cells were fabricated following our previous reports on membrane-less and mediator-free biodevices in which cellobiose dehydrogenase and bilirubin oxidase were used as anodic and cathodic biocatalysts, respectively. The following average characteristics of transparent and flexible biodevices operating in glucose and chloride containing neutral buffers were registered: 0.63 V open-circuit voltage, and 0.6 mu W cm(-2) maximal power density at a cell voltage of 0.35 V. A transparent and flexible enzymatic fuel cell could still deliver at least 0.5 mu W cm(-2) after 12 h of continuous operation. Thus, such biodevices can potentially be used as self-powered biosensors or electric power sources for smart electronic contact lenses. (C) 2015 Elsevier B.V. All rights reserved

Spherical means-based free-water volume fraction from diffusion MRI increases non-linearly with age in the white matter of the healthy human brain

Producción CientíficaThe term free-water volume fraction (FWVF) refers to the signal fraction that could be found as the cerebrospinal fluid of the brain, which has been demonstrated as a sensitive measure that correlates with cognitive performance and various neuropathological processes. It can be quantified by properly fitting the isotropic component of the magnetic resonance (MR) signal in diffusion-sensitized sequences. Using healthy subjects (178F/109M) aged 25-94, this study examines in detail the evolution of the FWVF obtained with the spherical means technique from multi-shell acquisitions in the human brain white matter across the adult lifespan, which has been previously reported to exhibit a positive trend when estimated from single-shell data using the bi-tensor signal representation. We found evidence of a noticeably non-linear gain after the sixth decade of life, with a region-specific variate and varying change rate of the spherical means-based multi-shell FWVF parameter with age, at the same time, a heteroskedastic pattern across the adult lifespan is suggested. On the other hand, the FW corrected diffusion tensor imaging (DTI) leads to a region-dependent flattened age-related evolution of the mean diffusivity (MD) and fractional anisotropy (FA), along with a considerable reduction in their variability, as compared to the studies conducted over the standard (single-component) DTI. This way, our study provides a new perspective on the trajectory-based assessment of the brain and explains the conceivable reason for the variations observed in FA and MD parameters across the lifespan with previous studies under the standard diffusion tensor imaging.Ministerio de Ciencia e Innovación (MCIN-AEI) y FEDER-UE (grant PID2021-124407NB-I00)Ministerio de Ciencia e Innovación (MCIN-AEI) - Unión Europea “NextGenerationEU/PRTR” (grant TED2021-130758B-I00)Ministry of Science and Higher Education (Poland) - Bekker programme (grant PPN/BEK/2019/1/00421)Norwegian ExtraFoundation for Health and Rehabilitation (2015/FO5146)European Union's Horizon 2020 research and Innovation program (ERC 802998

Considerations on brain age predictions from repeatedly sampled data across time

Introduction Brain age, the estimation of a person's age from magnetic resonance imaging (MRI) parameters, has been used as a general indicator of health. The marker requires however further validation for application in clinical contexts. Here, we show how brain age predictions perform for the same individual at various time points and validate our findings with age-matched healthy controls. Methods We used densely sampled T1-weighted MRI data from four individuals (from two densely sampled datasets) to observe how brain age corresponds to age and is influenced by acquisition and quality parameters. For validation, we used two cross-sectional datasets. Brain age was predicted by a pretrained deep learning model. Results We found small within-subject correlations between age and brain age. We also found evidence for the influence of field strength on brain age which replicated in the cross-sectional validation data and inconclusive effects of scan quality. Conclusion The absence of maturation effects for the age range in the presented sample, brain age model bias (including training age distribution and field strength), and model error are potential reasons for small relationships between age and brain age in densely sampled longitudinal data. Clinical applications of brain age models should consider of the possibility of apparent biases caused by variation in the data acquisition process.publishedVersio

ROFI of the Elbe river during flood event, unstructured-mesh model study.

Regional models help to significantly improve our understanding of the global and regional cycles of, for example, carbon and nutrients. However, regional models often poorly resolve estuarine dynamics and are rather controlled by open boundary conditions. To investigate ecosystem processes in the south-eastern North Sea and Elbe estuary while avoiding the problems associated with nesting solutions we developed and applied an unstructured-mesh physical ocean model (FESOM-C). The FESOM-C model employs mixed unstructured-mesh methods and a finite - volume discretization. It is based on three-dimensional primitive equations for momentum, continuity, and density constituents. Vertically, the model uses a σ-coordinate system. The unstructured grid consists of quads and triangles zooming into the estuary, its vicinity and the coastline. Decrease in horizontal resolution provides a better numerical representation of coastal processes like asymmetries in tidal and residual flows, and periodic stratification. The lower resolution in the open sea allows conducting comparatively large regional studies. We developed a construction methodology for model setups in regions with complex coastal lines, including mixed mesh and bathymetry generation, open boundary and initial conditions and rivers distribution formation. The newly developed FESOM-C model could reproduce both barotropic and baroclinic dynamics of the coastal and estuary regions reasonably well. An Elbe summer flood event was well captured by the physical model. Investigation of flood event on ROFI of Elbe River were conducted with developed model by introduction of passive tracers in river outflow