A small spring fed stream precipitates calcite by outgassing of CO<sub>2</sub> due to chemically controlled inorganic processes. The chemical composition of the water was measured along 9 stations downstre...A small spring fed stream precipitates calcite by outgassing of CO<sub>2</sub> due to chemically controlled inorganic processes. The chemical composition of the water was measured along 9 stations downstream with respect to Ca<sup>2+</sup>, Mg<sup>2+</sup>, Na<sup>+</sup>,K<sup>+</sup>, Cl<sup>-</sup>, carbonate alkalinlty, and SO<sub>4</sub><sup>2-</sup>. Temperature and pH were measured in situ. Small rectangular shaped tablets of limestone from the area were immersed into the stream for short periods and water analyses were carried out at the same time. From weight increase of the tablets, precipitation rates展开更多
Objective and Impact Statement.Atrial fibrillation(AF)is a serious medical condition that requires effective and timely treatment to prevent stroke.We explore deep neural networks(DNNs)for learning cardiac cycles and ...Objective and Impact Statement.Atrial fibrillation(AF)is a serious medical condition that requires effective and timely treatment to prevent stroke.We explore deep neural networks(DNNs)for learning cardiac cycles and reliably detecting AF from single-lead electrocardiogram(ECG)signals.Introduction.Electrocardiograms are widely used for diagnosis of various cardiac dysfunctions including AF.The huge amount of collected ECGs and recent algorithmic advances to process time-series data with DNNs substantially improve the accuracy of the AF diagnosis.DNNs,however,are often designed as general purpose black-box models and lack interpretability of their decisions.Methods.We design a three-step pipeline for AF detection from ECGs.First,a recording is split into a sequence of individual heartbeats based on R-peak detection.Individual heartbeats are then encoded using a DNN that extracts interpretable features of a heartbeat by disentangling the duration of a heartbeat from its shape.Second,the sequence of heartbeat codes is passed to a DNN to combine a signal-level representation capturing heart rhythm.Third,the signal representations are passed to a DNN for detecting AF.Results.Our approach demonstrates a superior performance to existing ECG analysis methods on AF detection.Additionally,the method provides interpretations of the features extracted from heartbeats by DNNs and enables cardiologists to study ECGs in terms of the shapes of individual heartbeats and rhythm of the whole signals.Conclusion.By considering ECGs on two levels and employing DNNs for modelling of cardiac cycles,this work presents a method for reliable detection of AF from single-lead ECGs.展开更多
In Germany, all types of radioactive wastes will be disposed of in deep geological repositories. While a repository for low-level radioactive waste （LLW） has recently been licensed, different host rock formations ar...In Germany, all types of radioactive wastes will be disposed of in deep geological repositories. While a repository for low-level radioactive waste （LLW） has recently been licensed, different host rock formations are considered for disposal of heat producing high-level waste （HLW）. The latter includes directly disposed spent fuel （SF） and vitrified waste from its reprocessing. Different canisters and disposal concepts are considered for spent fuel disposal, i.e. thick-walled iron casks in horizontal drifts or thin-walled BSK3 steel casks in vertical boreholes. GRS is the leading expert institution in Germany concerning nuclear safety and waste management. For the recent 30 years, GRS has developed and continuously improves a set of computer codes, which allow assessing the performance and the long-term safety of repositories in various host rocks （salt, clay or granite） adopting different technical options. Advanced methods for deterministic as well as probabilistic assessments are available. To characterize the host rocks and backfill/buffer materials and to develop disposal technologies, comprehensive laboratory experiments and a large number of in-situ tests have been performed at GRS＇ geo-laboratory and underground research laboratories in different host formations. Thermo-hydro-mechanico-chemical （THMC） processes occurring in the host rocks and engineered barrier systems are numerically simulated. The paper presents an overview of GRS＇ work highlighting important results of performance assessment （PA） studies for both the salt and clay options. Also, recent results of in-situ investigations and laboratory studies are presented together with modeling results. Special emphasis is dedicated to the consideration of coupled THM processes which are of relevance in PA.展开更多
文摘A small spring fed stream precipitates calcite by outgassing of CO<sub>2</sub> due to chemically controlled inorganic processes. The chemical composition of the water was measured along 9 stations downstream with respect to Ca<sup>2+</sup>, Mg<sup>2+</sup>, Na<sup>+</sup>,K<sup>+</sup>, Cl<sup>-</sup>, carbonate alkalinlty, and SO<sub>4</sub><sup>2-</sup>. Temperature and pH were measured in situ. Small rectangular shaped tablets of limestone from the area were immersed into the stream for short periods and water analyses were carried out at the same time. From weight increase of the tablets, precipitation rates
基金the Deutsche Forschungsgemeinschaft (grant SFB 410)the German-Israeli Foundation for Scientific Research and Development (grant 881/05)+4 种基金the NSF(grant DMR-0342832)the U.S.Department of EnergyOffice of Basic Energy Sciencesunder contract DE-AC03-76SF00515Focus Center Research Program (FCRP) Center on Functional Engineered Nanoarchitectonics (FENA)
基金funded by the Swiss Heart Failure Network (PHRT122/2018DRI14) (J.M.Buhmann,PI).
文摘Objective and Impact Statement.Atrial fibrillation(AF)is a serious medical condition that requires effective and timely treatment to prevent stroke.We explore deep neural networks(DNNs)for learning cardiac cycles and reliably detecting AF from single-lead electrocardiogram(ECG)signals.Introduction.Electrocardiograms are widely used for diagnosis of various cardiac dysfunctions including AF.The huge amount of collected ECGs and recent algorithmic advances to process time-series data with DNNs substantially improve the accuracy of the AF diagnosis.DNNs,however,are often designed as general purpose black-box models and lack interpretability of their decisions.Methods.We design a three-step pipeline for AF detection from ECGs.First,a recording is split into a sequence of individual heartbeats based on R-peak detection.Individual heartbeats are then encoded using a DNN that extracts interpretable features of a heartbeat by disentangling the duration of a heartbeat from its shape.Second,the sequence of heartbeat codes is passed to a DNN to combine a signal-level representation capturing heart rhythm.Third,the signal representations are passed to a DNN for detecting AF.Results.Our approach demonstrates a superior performance to existing ECG analysis methods on AF detection.Additionally,the method provides interpretations of the features extracted from heartbeats by DNNs and enables cardiologists to study ECGs in terms of the shapes of individual heartbeats and rhythm of the whole signals.Conclusion.By considering ECGs on two levels and employing DNNs for modelling of cardiac cycles,this work presents a method for reliable detection of AF from single-lead ECGs.
基金funded by the German Federal Ministry of Economics and Technology(BMWi)and the Commission of the European Communities
文摘In Germany, all types of radioactive wastes will be disposed of in deep geological repositories. While a repository for low-level radioactive waste （LLW） has recently been licensed, different host rock formations are considered for disposal of heat producing high-level waste （HLW）. The latter includes directly disposed spent fuel （SF） and vitrified waste from its reprocessing. Different canisters and disposal concepts are considered for spent fuel disposal, i.e. thick-walled iron casks in horizontal drifts or thin-walled BSK3 steel casks in vertical boreholes. GRS is the leading expert institution in Germany concerning nuclear safety and waste management. For the recent 30 years, GRS has developed and continuously improves a set of computer codes, which allow assessing the performance and the long-term safety of repositories in various host rocks （salt, clay or granite） adopting different technical options. Advanced methods for deterministic as well as probabilistic assessments are available. To characterize the host rocks and backfill/buffer materials and to develop disposal technologies, comprehensive laboratory experiments and a large number of in-situ tests have been performed at GRS＇ geo-laboratory and underground research laboratories in different host formations. Thermo-hydro-mechanico-chemical （THMC） processes occurring in the host rocks and engineered barrier systems are numerically simulated. The paper presents an overview of GRS＇ work highlighting important results of performance assessment （PA） studies for both the salt and clay options. Also, recent results of in-situ investigations and laboratory studies are presented together with modeling results. Special emphasis is dedicated to the consideration of coupled THM processes which are of relevance in PA.
