Predicting Spatio-Temporal Time Series Using Dimension Reduced Local States

We present a method for both cross estimation and iterated time series prediction of spatio temporal dynamics based on reconstructed local states, PCA dimension reduction, and local modelling using nearest neighbour methods. The effectiveness of this approach is shown for (noisy) data from a (cubic) Barkley model, the Bueno-Orovio-Cherry-Fenton model, and the Kuramoto-Sivashinsky model

Water quality of Texas bays (nutrients, trace elements and toxic compounds)

This manuscript is designed to compare the nutrient balances and trace element significance in Texas Bays and Estuaries. The task of assigning water quality criteria in all estuarine waters rests with the federal Environmental Protection Agency. However, the Texas Bays and Estuaries represent a unique range of environments of the U.S. Coast that stand alone and therefore must be assigned standards appropriate to the environment. Therefore we have compared several Texas Bays relative to nutrients and trace elements through an analysis of data from our files, a life history data bank from literature survey, a study of the Corpus Christi area, personal communication with a wide range of individuals and information from the Texas Water Quality Board, Texas Water Development Board, the U.S. Geological Survey and the State Health Department.May 30, 1974Taken in part from a report on Development of Biological Criteria, Establishment of Guidelines for Texas Coast Management IAC-(74-75)-0685 NSF RANN-61-34870xMarine Scienc

Debido proceso y su recepción en la Ley Nº 19.880: valoración y estándar de prueba en sede administrativa

This paper aims to analyze and discuss how due process is collected in Law No. 19.880,and if there is to some extent tension between the valuation rules of evidence contained in that law and the right to due process. To discuss this, we will take as example recent cases decided by the Superintendency of Securities and Insurance, henceforth the “SVS”,on punitive matters.El objetivo del presente artículo es analizar y discutir de qué manera el debido proceso se encuentra recogido en la Ley Nº 19.880 y, si en alguna medida existe tensión entre las reglas de valoración de la prueba contendidas en dicha ley y el derecho al debido proceso. Para discutir sobre ello, tomaremos como ejemplo alguno de los recientes casos resueltos por la Superintendencia de Valores y Seguros, en adelante la “SVS”, en materia sancionatoria

Interactions between satellites and plasma

The interactions of a spacecraft with the surrounding, streaming plasma were determined by the following effects: the fade out of the plasma in the wake of the probe, the emission of photoelectrons and secondary electrons, the differential charging of the surface of the probe, and a spatial potential distribution in the vicinity of the space probe. These effects and their importance are discussed and following plasma conditions are considered: (1) geostationary satellite orbits; (2) in the solar wind (HELIOS mission); and (3) in the ionosphere at an altitude of 250 km (the projected OSV on Spacelab). The fundamental models are reviewed

Automated Design of Deep Learning Methods for Biomedical Image Segmentation

Biomedical imaging is a driver of scientific discovery and core component of medical care, currently stimulated by the field of deep learning. While semantic segmentation algorithms enable 3D image analysis and quantification in many applications, the design of respective specialised solutions is non-trivial and highly dependent on dataset properties and hardware conditions. We propose nnU-Net, a deep learning framework that condenses the current domain knowledge and autonomously takes the key decisions required to transfer a basic architecture to different datasets and segmentation tasks. Without manual tuning, nnU-Net surpasses most specialised deep learning pipelines in 19 public international competitions and sets a new state of the art in the majority of the 49 tasks. The results demonstrate a vast hidden potential in the systematic adaptation of deep learning methods to different datasets. We make nnU-Net publicly available as an open-source tool that can effectively be used out-of-the-box, rendering state of the art segmentation accessible to non-experts and catalyzing scientific progress as a framework for automated method design.Comment: * Fabian Isensee and Paul F. J\"ager share the first authorshi