An Optimization Model to Address Overcrowding in Emergency Departments Using Patient Transfer

Overcrowding of emergency departments (EDs) is a problem that affected many hospitals especially during the response to emergency situations such as pandemics or disasters. Transferring nonemergency patients is one approach that can be utilized to address ED overcrowding. We propose a novel mixed-integer nonlinear programming (MINLP) model that explicitly considers queueing effects to address overcrowding in a network of EDs, via a combination of two decisions: modifying service capacity to EDs and transferring patients between EDs. Computational testing is performed using a Design of Experiments to determine the sensitivity of the MINLP solutions to changes in the various input parameters. Additional computational testing examines the effect of ED size on the number of transfers occurring in the system, identifying an efficient frontier for the tradeoff between system cost (measured as a function of the service capacity and the number of patient transfers) and the systemwide average expected waiting time. Taken together, these results suggest that our optimization model can identify a range of efficient alternatives for healthcare systems designing a network of EDs across multiple hospitals.

Rotating Microtab Implementation on a DU91W250 Airfoil Based on the Cell-Set Model

Flow control device modeling is an engaging research field for wind turbine optimization, since in recent years wind turbines have grown in proportions and weight. The purpose of the present work was to study the performance and effects generated by a rotating microtab (MT) implemented on the trailing edge of a DU91W250 airfoil through the novel cell-set (CS) model for the first time via CFD techniques. The CS method is based on the reutilization of an already calculated mesh for the addition of new geometries on it. To accomplish that objective, the required region is split from the main domain, and new boundaries are assigned to the mentioned construction. Three different MT lengths were considered: h = 1%, 1.5% and 2% of the airfoil chord length, as well as seven MT orientations (β): from 0° to −90° regarding the horizontal axis, for five angles of attack: 0°, 2°, 4°, 6° and 9°. The numerical results showed that the increases of the β rotating angle and the MT length (h) led to higher aerodynamic performance of the airfoil, CL/CD = 164.10 being the maximum ratio obtained. All the performance curves showed an asymptotic trend as the β angle reduced. Qualitatively, the model behaved as expected, proving the relationship between velocity and pressure. Taking into consideration resulting data, the cell-set method is appropriate for computational testing of trailing edge rotating microtab geometry.

The Evaluation on the Process Capability Index CL for Exponentiated Frech’et Lifetime Product under Progressive Type I Interval Censoring

We present the likelihood inferences on the lifetime performance index CL to evaluate the performance of lifetimes of products following the skewed Exponentiated Frech’et distribution in many manufacturing industries. This research is related to the topic of skewed Probability Distributions and Applications across Disciplines. Exponentiated Frech’et distribution is a generalization of some lifetime distributions. The maximum likelihood estimator for CL for lifetimes with exponentiated Frech’et distribution is derived to develop a computational testing procedure so that experimenters can implement it to test whether the lifetime performance reached the pre-assigned level of significance with a given lower specification limit under progressive type I interval censoring. At the end, two examples are provided to demonstrate the implementation on the algorithm for our proposed computational testing procedure.

Fast and accurate diagnostics from highly multiplexed sequencing assays

Scalable, inexpensive, accurate, and secure testing for SARS-CoV-2 infection is crucial for control of the novel coronavirus pandemic. Recently developed highly multiplexed sequencing assays that rely on high-throughput sequencing (HMSAs) can, in principle, meet these demands, and present promising alternatives to currently used RT-qPCR-based tests. However, the analysis and interpretation of HMSAs requires overcoming several computational and statistical challenges. Using recently acquired experimental data, we present and validate an accurate and fast computational testing workflow based on kallisto and bustools, that utilize robust statistical methods and fast, memory efficient algorithms for processing high-throughput sequencing data. We show that our workflow is effective at processing data from all recently proposed SARS-CoV-2 sequencing based diagnostic tests, and is generally applicable to any diagnostic HMSAs.

Towards a Cyber Secure Shipboard Radar

This paper presents a comparative cyber security resilience estimation of shipboard radars that are implemented on two oil/chemical tankers certified as SOLAS ships. The estimated radars were chosen from the same manufacturer, but belonged to different generations. The estimation was conducted by means of ships' crew interviews and computational testing of the radars using a widely deployed vulnerability scanning software tool. The identified cyber threats were analysed qualitatively in order to gain a holistic understanding of cyber risks threatening shipboard radar systems. The results obtained experimentally indicate that potential cyber threats mainly relate to maintenance of the radars' underlying operating system, suggesting the need for regulatory standardisation of periodic cyber security testing of radar systems.

New Sulfur-Containing Polyarsenicals from the New Caledonian Sponge Echinochalina bargibanti

Arsenicin A (C3H6As4O3) was isolated from the New Caledonian poecilosclerid sponge Echinochalina bargibanti, and described as the first natural organic polyarsenic compound. Further bioguided fractionation of the extracts of this sponge led us to isolate the first sulfur-containing organic polyarsenicals ever found in Nature. These metabolites, called arsenicin B and arsenicin C, are built on a noradamantane-type framework that is characterized by an unusual As–As bonding. Extensive NMR measurements, in combination with mass spectra, enabled the assignment of the structure for arsenicin B (C3H6As4S2) as 2. The scarcity of arsenicin C and its intrinsic chemical instability only allowed the collection of partial spectral data, which prevented the full structural definition. After the extensive computational testing of several putative structures, structure 3 was inferred for arsenicin C (C3H6As4OS) by comparing the experimental and density functional theory (DFT)-calculated 1H and 13C NMR spectra. Finally, the absolute configurations of 2 and 3 were determined with a combined use of experimental and time-dependent (TD)-DFT calculated electronic circular dichroism (ECD) spectra and observed specific rotations. These findings pose great challenges for the investigation of the biosynthesis of these metabolites and the cycle of arsenic in Nature. Arsenicins B and C showed strong antimicrobial activities, especially against S. aureus, which is comparable to the reference compound gentamycin.

New Sulfur-Containing Polyarsenicals from the New Caledonian sponge Echinochalina bargibanti

Isolated from a New Caledonian collection of the poecilosclerid sponge Echinochalina bargibanti, arsenicin A (C3H6As4O3) was described as the first natural organic polyarsenic compound. Continuing on bioassay guided fractionation of the organic extracts of this sponge, we describe here the isolation and structural elucidation of the first sulfur-containing organic polyarsenicals ever found in nature. The novel metabolites, called arsenicin B and arsenicin C, are built on a noradamantane type framework and they further distinguish from the adamantane type framework of arsenicin A by a different heteroatom composition and by the presence of an unusual As-As bonding. Extensive 1D and 2D-NMR measurements, in combination with tandem APCI mass spectra, allowed to establish the structure of arsenicin B (C3H6As4S2) as 2. The scarcity of arsenicin C and and its intrinsic chemical instability, only allowed to collect partial spectral data which prevented the full structural definition. After extensive computational testing of several putative structures, structure 3 for arsenicin C (C3H6As4OS) was inferred by comparing experimental with DFT-calculated 1H and 13C NMR spectra. Finally, the absolute configuration of 2 and 3 were determined with a combined use of experimental and TD-DFT calculated ECD spectra and observed specific rotations. These findings pose great challenges for both the biosynthesis of these metabolites and the cycle of Arsenic in nature. Arsenicin B and arsenicin C showed strong antifungal and antibacterial activities, especially against S. aureus comparable to the antibiotic gentamycin.