Limited-area short-range ensemble predictions targeted for heavy rain in Europe

International audienceInherent uncertainties in short-range quantitative precipitation forecasts (QPF) from the high-resolution, limited-area numerical weather prediction model DMI-HIRLAM (LAM) are addressed using two different approaches to creating a small ensemble of LAM simulations, with focus on prediction of extreme rainfall events over European river basins. The first ensemble type is designed to represent uncertainty in the atmospheric state of the initial condition and at the lateral LAM boundaries. The global ensemble prediction system (EPS) from ECMWF serves as host model to the LAM and provides the state perturbations, from which a small set of significant members is selected. The significance is estimated on the basis of accumulated precipitation over a target area of interest, which contains the river basin(s) under consideration. The selected members provide the initial and boundary data for the ensemble integration in the LAM. A second ensemble approach tries to address a portion of the model-inherent uncertainty responsible for errors in the forecasted precipitation field by utilising different parameterisation schemes for condensation and convection in the LAM. Three periods around historical heavy rain events that caused or contributed to disastrous river flooding in Europe are used to study the performance of the LAM ensemble designs. The three cases exhibit different dynamic and synoptic characteristics and provide an indication of the ensemble qualities in different weather situations. Precipitation analyses from the Deutsche Wetterdienst (DWD) are used as the verifying reference and a comparison of daily rainfall amounts is referred to the respective river basins of the historical cases

Query processing of pre-partitioned data using Sandwich Operators

textabstractIn this paper we present the Sandwich Operators, an elegant approach to exploit pre-sorting or pre-grouping from clustered storage schemes in operators such as Aggregation/Grouping, HashJoin, and Sort of a database management system. Thereby, each of these operator types is "sandwiched" by two new operators, namely PartitionSplit and PartitionRestart. PartitionSplit splits the input relation into its smaller independent groups on which the sandwiched operator is executed. After a group is processed PartitionRestart is used to trigger the execution on the following group. Executing one of these operator types with the help of the Sandwich Operators introduces minimal overhead and does not penalty performance of the sandwiched operator as its implementation remains unchanged. On the contrary, we show that sandwiched execution of an operator results in lower memory consumption and faster execution time. PartitionSplit and PartitionRestart replace special implementations of partitioned versions of these operator. Sandwich Operators also turn blocking operators in streaming operators, resulting in faster response times for the first query results

Critical Kauffman networks under deterministic asynchronous update

We investigate the influence of a deterministic but non-synchronous update on Random Boolean Networks, with a focus on critical networks. Knowing that ``relevant components'' determine the number and length of attractors, we focus on such relevant components and calculate how the length and number of attractors on these components are modified by delays at one or more nodes. The main findings are that attractors decrease in number when there are more delays, and that periods may become very long when delays are not integer multiples of the basic update step.Comment: 8 pages, 3 figures, submitted to a journa

A comparative approach to confirm antibiotic-resistant microbes in the cryosphere

Antibiotic-resistant microbes pose one of the biggest challenges of the current century. While areas with proximity to human impact are closely studied, a lot is yet to learn about antimicrobial resistance in remote regions like the cryosphere. Nowadays, antibiotic (AB) resistance is considered a pollution that has reached the Earth’s most pristine areas. However, monitoring of resistant environmental bacteria therein faces several challenges that inhibit scientific progress in this field. Due to many cultivation-based antibiotic susceptibility tests being optimized for mesophilic pathogenic microorganisms, many researchers opt for expensive molecular biological approaches to detect antibiotic resistance in the cryosphere. However, some disadvantages of these methods prohibit effective comprehensive monitoring of resistant bacteria in pristine areas, hence we suggest established cultivation-based approaches when looking for antimicrobial resistance in the cryosphere. In this study, we compared two common antibiotic susceptibility tests and optimized them to meet the needs of psychrophilic microorganisms. The resulting cultures thereof originated from cryospheric habitats with differing anthropogenic impacts. The results show that these methods are applicable to detect antibiotic resistance in cryospheric habitats and could potentially increase the comparability between studies

Automatic Schema Design for Co-Clustered Tables

Schema design of analytical workloads provides opportunities to index, cluster, partition and/or materialize. With these opportunities also the complexity of finding the right setup rises. In this paper we present an automatic schema design approach for a table co-clustering scheme called Bitwise Dimensional Co-Clustering, aimed at schemas with a moderate amount dimensions, but not limited to typical star and snowflake schemas. The goal is to design one primary schema and keep the knobs to turn to a minimum while providing a robust schema for a wide range of queries. In our approach a clustered schema is derived by trying to apply dimensions throughout the whole schema and co-cluster as many tables as possible according to at least one common dimension. Our approach is based on the assumption that initially foreign key relationships and a set of dimensions are defined based on classic DDL

The Impact of Burnout Identification and Interventions in Nursing Students and Newly Licensed Nurses: A Literature Review

Burnout is a problem that is plaguing the healthcare system globally, potentially resulting in individuals leaving their respective professions. Worldwide, there is a shortage of over 6 million nurses. Newly licensed registered nurses, both the associates degree and baccalaureate prepared, are poorly equipped to manage the stress and emotional exhaustion of providing patient care resulting in new nurses leaving the nursing field within one to two years of graduation. The purpose of this project was to identify: (1) if burnout experienced during nursing school continues into the new graduate nurse’s career; (2) how this influences the new graduate as a newly licensed registered nurse’s choice to exit the profession within the first few years of work; and (3) what interventions can be implemented to minimize burnout and improve retention rates of new nurses. A literature review was conducted, and the Health Belief Model was utilized to guide appropriate recommendations to minimize the negative effects of burnout. Approximately 175,000 registered nurses within the United States will leave the profession each year for a wide range of reasons. If nursing students experience burnout while in their respective programs, job stressors and job demands can increase the probability of newly licensed nurses burning out and subsequently leaving the profession. Implementation of various interventions have been shown to minimize burnout in nursing students and new nurses and subsequent retention in the nursing profession. It is recommended that education regarding burnout be implemented in nursing programs to provide students with the necessary skills to mitigate burnout prior to entering the profession. &nbsp

Hospital-Based Harm Reduction Interventions: A Systematic Review

Background: In the U.S., the number of hospitalized patients diagnosed with a substance use disorder (SUD; e.g., opioid use disorder, alcohol use disorder) is growing at an alarming rate. Often negatively impacted by stigma, homelessness and physical and mental comorbidities, this vulnerable patient population may benefit from the use of hospital-based harm reduction interventions (HHRIs) to improve overall hospital care experiences and negative health outcomes. Purpose: To examine how harm reduction principles have been successfully applied to HHRIs resulting in decreased negative health outcomes associated with SUD, improved healthcare provider-patient relationships, and reduced financial burden of healthcare systems. Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and flow diagram were utilized for this systematic review. Nineteen studies met the eligibility criteria for inclusion in the review. Implications: Four consistent themes that either inhibit or facilitate the implementation of HHRIs (e.g., establishing specialized SUD hospital units, employing peer support specialists, utilizing the clinical opiate withdrawal scale) were identified: ethical responsibility, stigma, structural changes to hospital systems, and noted gaps associated with post-discharge care. Conclusion: HHRIs are a useful treatment option to manage the unique needs associated with the growing SUD patient population

Application of Electrochemical Impedance Spectroscopy on Different Battery Circuits

For the operation of a battery pack, the cell state estimation plays a central role. For that, enough information about the current charge condition (SoC, state of charge) and the health status (SoH, state of health) of the individual cells or cell strings must be available. One way to draw out conclusions about the state of charge and health provides the electrochemical impedance spectroscopy (EIS) [1]. The test cells are thereby stimulated with an alternating current signal, and the resulting voltage signal is detected. These results in cell impedances, which are addicted to the signal frequencies and the respective cell states. This poster shows an experimental platform which uses the EIS to detect asymmetries in SoC and/or SoH on circuited cells. For that, the behavior of the amplitudes and frequencies of the signals should be analyzed, because for the calculation of the precise impedance, these factors are crucial. Thereby the required alternating current and voltage signals are acquired and analyzed separately for each single cell. As cell type lithium iron-phosphate round cells of the size 18650 are used. The investigations are made on a series circuit (Fig.1) made up of three cells and on a parallel circuit made up of two strings, each having two cells in series. It shows that both a series and a parallel connection within the working range the experimental platform impedances of individual cells can be determined. For these cases, differences in state of charge and state of health can be highlighted and assigned to the respective cells

Hybridization-related correction to the jellium model for fullerenes

We introduce a new type of correction for a more accurate description of fullerenes within the spherically symmetric jellium model. This correction represents a pseudopotential which originates from the comparison between an accurate ab initio calculation and the jellium model calculation. It is shown that such a correction to the jellium model allows one to account, at least partly, for the sp2-hybridization of carbon atomic orbitals. Therefore, it may be considered as a more physically meaningful correction as compared with a structureless square-well pseudopotential which has been widely used earlier.Comment: 16 pages, 10 figure