Settling the half-life of ⁶⁰Fe: fundamental for a versatile astrophysical chronometer

In order to resolve a recent discrepancy in the half-life of ⁶⁰Fe, we performed an independent measurement with a new method that determines the ⁶⁰Fe content of a material relative to Fe55 (t1/2=2.744yr) with accelerator mass spectrometry. Our result of (2.50±0.12)×10⁶yr clearly favors the recently reported value (2.62±0.04)×10⁶yr, and rules out the older result of (1.49±0.27)×10⁶yr. The present weighted mean half-life value of (2.60±0.05)×10⁶yr substantially improves the reliability as an important chronometer for astrophysical applications in the million-year time range. This includes its use as a sensitive probe for studying recent chemical evolution of our Galaxy, the formation of the early Solar System, nucleosynthesis processes in massive stars, and as an indicator of a recent nearby supernova.Part of this work was funded by the Austrian Science Fund (FWF) Projects No. AP20434 and AI00428 (FWF and CoDustMas, Eurogenesis via ESF)

A Self Healing Microservices Architecture: A Case Study in Docker Swarm Cluster

One desired aspect of a self-adapting microservices architecture is the ability to continuously monitor the operational environment, detect and observe anomalous behaviour as well as implement a reasonable policy for self-scaling, self-healing, and self-tuning the computational resources in order to dynamically respond to a sudden change in its operational environment. Often the behaviour of a microservices architecture continuously changes over time and the identification of both normal and abnormal behaviours of running services becomes a challenging task. This paper proposes a self-healing Microservice architecture that continuously monitors the operational environment, detects and observes anomalous behaviours, and provides a reasonable adaptation policy using a multi-dimensional utility-based model. This model preserves the cluster state and prevents multiple actions to taking place at the same time. It also guarantees that the executed adaptation action fits the current execution context and achieves the adaptation goals. The results show the ability of this model to dynamically scale the architecture horizontally or vertically in response to the context changes

Novel method to study neutron capture of U 235 and U 238 simultaneously at keV energies

The neutron capture cross sections of the main uranium isotopes, U235 and U238, were measured simultaneously for keV energies, for the first time by combining activation technique and atom counting of the reaction products using accelerator mass spectrometry. New data, with a precision of 3%-5%, were obtained from mg-sized natural uranium samples for neutron energies with an equivalent Maxwell-Boltzmann distribution of kT∼25keV and for a broad energy distribution peaking at 426 keV. The cross-section ratio of U235(n,γ)/U238(n,γ) can be deduced in accelerator mass spectrometry directly from the atom ratio of the reaction products U236/U239, independent of any fluence normalization. Our results confirm the values at the lower band of existing data. They serve as important anchor points to resolve present discrepancies in nuclear data libraries as well as for the normalization of cross-section data used in the nuclear astrophysics community for s-process studies

AI-based structure prediction empowers integrative structural analysis of human nuclear pores

Nuclear pore complexes (NPCs) mediate nucleocytoplasmic transport. Their intricate 120-megadalton architecture remains incompletely understood. Here, we report a 70-megadalton model of the humanNPC scaffold with explicit membrane and in multiple conformational states. We combined artificial intelligence (AI)–based structure prediction with in situ and in cellulo cryo–electron tomography and integrative modeling. We show that linker nucleoporins spatially organize the scaffold within and across subcomplexes to establish the higher-order structure. Microsecond-long molecular dynamics simulationssuggest that the scaffold is not required to stabilize the inner and outer nuclear membrane fusion but rather widens the central pore. Our work exemplifies how AI-based modeling can be integrated within situ structural biology to understand subcellular architecture across spatial organization levels

Nuclear data from AMS & nuclear data for AMS - some examples

We summarize some recent cross-section measurements using accelerator mass spectrometry (AMS). AMS represents an ultra-sensitive technique for measuring a limited, but steadily increasing number of longer-lived radionuclides. This method implies a two-step procedure with sample activation and subsequent AMS measurement. Applications include nuclear astrophysics, nuclear technology (nuclear fusion, nuclear fission and advanced reactor concepts and radiation dose estimations). A series of additional applications involves cosmogenic radionuclides in environmental, geological and extraterrestrial studies. Lack of information exists for a list of nuclides as pointed out by nuclear data requests. An overview of some recent measurements is given and the method is exemplified for some specific neutron-induced reactions.JRC.D.4-Standards for Nuclear Safety, Security and Safeguard

Data-driven approach for creating synthetic electronic medical records

<p>Abstract</p> <p>Background</p> <p>New algorithms for disease outbreak detection are being developed to take advantage of full electronic medical records (EMRs) that contain a wealth of patient information. However, due to privacy concerns, even anonymized EMRs cannot be shared among researchers, resulting in great difficulty in comparing the effectiveness of these algorithms. To bridge the gap between novel bio-surveillance algorithms operating on full EMRs and the lack of non-identifiable EMR data, a method for generating complete and synthetic EMRs was developed.</p> <p>Methods</p> <p>This paper describes a novel methodology for generating complete synthetic EMRs both for an outbreak illness of interest (tularemia) and for background records. The method developed has three major steps: 1) synthetic patient identity and basic information generation; 2) identification of care patterns that the synthetic patients would receive based on the information present in real EMR data for similar health problems; 3) adaptation of these care patterns to the synthetic patient population.</p> <p>Results</p> <p>We generated EMRs, including visit records, clinical activity, laboratory orders/results and radiology orders/results for 203 synthetic tularemia outbreak patients. Validation of the records by a medical expert revealed problems in 19% of the records; these were subsequently corrected. We also generated background EMRs for over 3000 patients in the 4-11 yr age group. Validation of those records by a medical expert revealed problems in fewer than 3% of these background patient EMRs and the errors were subsequently rectified.</p> <p>Conclusions</p> <p>A data-driven method was developed for generating fully synthetic EMRs. The method is general and can be applied to any data set that has similar data elements (such as laboratory and radiology orders and results, clinical activity, prescription orders). The pilot synthetic outbreak records were for tularemia but our approach may be adapted to other infectious diseases. The pilot synthetic background records were in the 4-11 year old age group. The adaptations that must be made to the algorithms to produce synthetic background EMRs for other age groups are indicated.</p

Nuclear Data from AMS & Nuclear Data for AMS -some examples

We summarize some recent cross-section measurements using accelerator mass spectrometry (AMS). AMS represents an ultra-sensitive technique for measuring a limited, but steadily increasing number of longer-lived radionuclides. This method implies a two-st