Fluid Approximation of a Call Center Model with Redials and Reconnects

In many call centers, callers may call multiple times. Some of the calls are re-attempts after abandonments (redials), and some are re-attempts after connected calls (reconnects). The combination of redials and reconnects has not been considered when making staffing decisions, while ignoring them will inevitably lead to under- or overestimation of call volumes, which results in improper and hence costly staffing decisions. Motivated by this, in this paper we study call centers where customers can abandon, and abandoned customers may redial, and when a customer finishes his conversation with an agent, he may reconnect. We use a fluid model to derive first order approximations for the number of customers in the redial and reconnect orbits in the heavy traffic. We show that the fluid limit of such a model is the unique solution to a system of three differential equations. Furthermore, we use the fluid limit to calculate the expected total arrival rate, which is then given as an input to the Erlang A model for the purpose of calculating service levels and abandonment rates. The performance of such a procedure is validated in the case of single intervals as well as multiple intervals with changing parameters

A multiphysics and multiscale software environment for modeling astrophysical systems

We present MUSE, a software framework for combining existing computational tools for different astrophysical domains into a single multiphysics, multiscale application. MUSE facilitates the coupling of existing codes written in different languages by providing inter-language tools and by specifying an interface between each module and the framework that represents a balance between generality and computational efficiency. This approach allows scientists to use combinations of codes to solve highly-coupled problems without the need to write new codes for other domains or significantly alter their existing codes. MUSE currently incorporates the domains of stellar dynamics, stellar evolution and stellar hydrodynamics for studying generalized stellar systems. We have now reached a "Noah's Ark" milestone, with (at least) two available numerical solvers for each domain. MUSE can treat multi-scale and multi-physics systems in which the time- and size-scales are well separated, like simulating the evolution of planetary systems, small stellar associations, dense stellar clusters, galaxies and galactic nuclei. In this paper we describe three examples calculated using MUSE: the merger of two galaxies, the merger of two evolving stars, and a hybrid N-body simulation. In addition, we demonstrate an implementation of MUSE on a distributed computer which may also include special-purpose hardware, such as GRAPEs or GPUs, to accelerate computations. The current MUSE code base is publicly available as open source at http://muse.liComment: 24 pages, To appear in New Astronomy Source code available at http://muse.l

Protein Kinase A-induced tamoxifen resistance is mediated by anchoring protein AKAP13

Univariate analysis for different AKAP13 probes. Table S2. Univariate analysis. Table S3. Multivariate analysis. (PDF 64 kb

Metaphors in Invasion Biology: Implications for Risk Assessment and Management of Non-Native Species

Contains fulltext : 161410.pdf (publisher's version ) (Closed access

Clinical and Pathological Findings in SARS-CoV-2 Disease Outbreaks in Farmed Mink (Neovison vison)

SARS-CoV-2, the causative agent of COVID-19, caused respiratory disease outbreaks with increased mortality in 4 mink farms in the Netherlands. The most striking postmortem finding was an acute interstitial pneumonia, which was found in nearly all examined mink that died at the peak of the outbreaks. Acute alveolar damage was a consistent histopathological finding in mink that died with pneumonia. SARS-CoV-2 infections were confirmed by detection of viral RNA in throat swabs and by immunohistochemical detection of viral antigen in nasal conchae, trachea, and lung. Clinically, the outbreaks lasted for about 4 weeks but some animals were still polymerase chain reaction–positive for SARS-CoV-2 in throat swabs after clinical signs had disappeared. This is the first report of the clinical and pathological characteristics of SARS-CoV-2 outbreaks in mink farms

An Air-liquid Interface Bronchial Epithelial Model for Realistic, Repeated Inhalation Exposure to Airborne Particles for Toxicity Testing.

For toxicity testing of airborne particles, air-liquid interface (ALI) exposure systems have been developed for in vitro tests in order to mimic realistic exposure conditions. This puts specific demands on the cell culture models. Many cell types are negatively affected by exposure to air (e.g., drying out) and only remain viable for a few days. This limits the exposure conditions that can be used in these models: usually relatively high concentrations are applied as a cloud (i.e., droplets containing particles, which settle down rapidly) within a short period of time. Such experimental conditions do not reflect realistic long-term exposure to low concentrations of particles. To overcome these limitations the use of a human bronchial epithelial cell line, Calu-3 was investigated. These cells can be cultured at ALI conditions for several weeks while retaining a healthy morphology and a stable monolayer with tight junctions. In addition, this bronchial model is suitable for testing the effects of repeated exposures to low, realistic concentrations of airborne particles using an ALI exposure system. This system uses a continuous airflow in contrast to other ALI exposure systems that use a single nebulization producing a cloud. Therefore, the continuous flow system is suitable for repeated and prolonged exposure to airborne particles while continuously monitoring the particle characteristics, exposure concentration, and delivered dose. Taken together, this bronchial model, in combination with the continuous flow exposure system, is able to mimic realistic, repeated inhalation exposure conditions that can be used for toxicity testing

Protein Kinase A-induced tamoxifen resistance is mediated by anchoring protein AKAP13

Background: Estrogen Receptor alpha (ERaα)-positive breast cancer patients receive endocrine therapy, often in the form of tamoxifen. However, resistance to tamoxifen is frequently observed. A signalling cascade that leads to tamoxifen resistance is dictated by activation of the Protein Kinase A (PKA) pathway, which leads to phosphorylation of ERaα on Serine 305 and receptor activation, following tamoxifen binding. Thus far, it remains elusive what protein complexes enable the PKA-ERaα interaction resulting in ERaα Serine 305 phosphorylation. Methods: We performed immunohistochemistry to detect ERaαSerine 305 phosphorylation in a cohort of breast cancer patients who received tamoxifen treatment in the metastatic setting. From the same tumor specimens, Agilent 44 nK gene expression analyses were performed and integrated with clinicopathological data and survival information. In vitro analyses were performed using MCF7 breast cancer cells, which included immunoprecipitations and Fluorescence Resonance Energy Transfer (FRET) analyses to illustrate ERaα complex formation. siRNA mediated knockdown experiments were performed to assess effects on ERaαSerine 305 phosphorylation status, ERaα/PKA interactions and downstream responsive gene activity. Results: Stratifying breast tumors on ERaα Serine 305 phosphorylation status resulted in the identification of a gene network centered upon AKAP13. AKAP13 mRNA expression levels correlate with poor outcome in patients who received tamoxifen treatment in the metastatic setting. In addition, AKAP13 mRNA levels correlate with ERaαSerine 305 phosphorylation in breast tumor samples, suggesting a functional connection between these two events. In a luminal breast cancer cell line, AKAP13 was found to interact with ERaα as well as with a regulatory subunit of PKA. Knocking down of AKAP13 prevented PKA-mediated Serine 305 phosphorylation of ERaα and abrogated PKA-driven tamoxifen resistance, illustrating that AKAP13 is an essential protein in this process. Conclusions: We show that the PKA-anchoring protein AKAP13 is essential for the phosphorylation of ERaαS305, which leads to tamoxifen resistance both in cell lines and tamoxifen-treated breast cancer patients