User-selected Time Research Articles

Clear hands, Clear conscience: Fog disinfection, dry hand washing

Proposing a water-saving hand washing solution, we introduce a system designed to reduce water usage by over 95%. Highlighting the importance of hand hygiene in combating pandemics, we challenge the notion of excessive water requirement for effective disinfection. Our system, controlled by an Arduino microcontroller, incorporates ultrasonic sensors, mist maker, UV lamp, and timer buttons. It activates mist and UV components based on user-selected time, ensuring efficient disinfection. Alerts are issued if hands are prematurely removed, enhancing hygiene without water wastage

JEDi: java essential dynamics inspector \u2014 a molecular trajectory analysis toolkit

BackgroundPrincipal component analysis (PCA) is commonly applied to the atomic trajectories of biopolymers to extract essential dynamics that describe biologically relevant motions. Although application of PCA is straightforward, specialized software to facilitate workflows and analysis of molecular dynamics simulation data to fully harness the power of PCA is lacking. The Java Essential Dynamics inspector (JEDi) software is a major upgrade from the previous JED software.ResultsEmploying multi-threading, JEDi features a user-friendly interface to control rapid workflows for interrogating conformational motions of biopolymers at various spatial resolutions and within subregions, including multiple chain proteins. JEDi has options for Cartesian-based coordinates (cPCA) and internal distance pair coordinates (dpPCA) to construct covariance (Q), correlation (R), and partial correlation (P) matrices. Shrinkage and outlier thresholding are implemented for the accurate estimation of covariance. The effect of rare events is quantified using outlier and inlier filters. Applying sparsity thresholds in statistical models identifies latent correlated motions. Within a hierarchical approach, small-scale atomic motion is first calculated with a separate local cPCA calculation per residue to obtain eigenresidues. Then PCA on the eigenresidues yields rapid and accurate description of large-scale motions. Local cPCA on all residue pairs creates a map of all residue-residue dynamical couplings. Additionally, kernel PCA is implemented. JEDi output gives high quality PNG images by default, with options for text files that include aligned coordinates, several metrics that quantify mobility, PCA modes with their eigenvalues, and displacement vector projections onto the top principal modes. JEDi provides PyMol scripts together with PDB files to visualize individual cPCA modes and the essential dynamics occurring within user-selected time scales. Subspace comparisons performed on the most relevant eigenvectors using several statistical metrics quantify similarity/overlap of high dimensional vector spaces. Free energy landscapes are available for both cPCA and dpPCA.ConclusionJEDi is a convenient toolkit that applies best practices in multivariate statistics for comparative studies on the essential dynamics of similar biopolymers. JEDi helps identify functional mechanisms through many integrated tools and visual aids for inspecting and quantifying similarity/differences in mobility and dynamic correlations.

Managing computational gateway resources with XDMoD

The U.S. National Science Foundation (NSF) has invested heavily in research computing, funding the XSEDE network of supercomputers and enabling their integration with science gateways. To ensure maximal return on this substantial investment, it is essential to monitor the use of these computing resources. XD Metrics on Demand (XDMoD) is an NSF-funded tool that was developed to help manage high performance computational resources. XDMoD metrics describe accounting and performance data for computational jobs, including resources consumed, wait times, and quality of service. XDMoD can provide information on individual jobs, or data aggregated over an ensemble of jobs. Its web interface offers centralized charting, exploration, and reporting of these metrics, for user-selected time ranges, and across resources.XDMoD is directly relevant to the gateways community. In this paper, we introduce XDMoD, demonstrate its utility for gateways, and outline our plans to further enhance its capabilities for the gateways community. Furthermore, we demonstrate how XDMoD can help gateway users and gateway and resource managers answer many questions about utilization, performance, and availability. In doing so, we showcase the evolution of gateways in the XSEDE ecosystem.

Fast and efficient chemical process flowsheet simulation by pseudo-transient continuation on inertial manifolds

Process flowsheets are mathematical models that describe the steady-state operation of (petro)chemical processes and comprise large-scale systems of nonlinear algebraic equations. The solution of these systems (referred to as “flowsheet simulation”) is challenging for practically-relevant problems. Pseudo-transient continuation is a promising numerical approach for process flowsheet simulation, and has been shown to converge flowsheets reliably from a wider range of initial guesses compared to standard Newton-type methods. However, the pseudo-transient approach is more computationally demanding than flowsheet simulation with a Newton-type solver (assuming a good initial guess is available for the latter). Moreover, process flowsheet simulation with pseudo-transient continuation involves defining a set of dynamics in pseudo-time, and both convergence and computational efficiency can be highly dependent on the user-selected time constants that govern this dynamic behavior. In this work, we address these challenges with a novel algorithm for process flowsheet simulation based on a hierarchical, multiply-singularly perturbed formulation of pseudo-transient dynamics, and an associated cascade of quasi-steady-state assumptions. The algorithm replaces a subset of the differential equations of the reformulated model with algebraic quasi-steady-state conditions when the system approaches the inertial manifold defined by steady state of the respective dynamics. The proposed technique allows a seamless transition from pseudo-time integration to efficient algebraic solvers, and we prove that the method converges to the solution of the original algebraic system in a finite number of steps. Moreover, the time-scale decomposition of the pseudo-transient dynamics eliminates the need to explicitly set the time constants of the dynamics in each time scale. Using two prototype chemical process examples, we show that the proposed method significantly reduces the computational effort involved in pseudo-transient process flowsheet simulation.

Band gap synthesis in elastic monatomic lattices via input shaping

This work describes control-theoretic methods for inducing a band gap-like behavior in elastic monatomic lattices. The dynamics of the system under consideration are derived in detail. Open-loop pre-filtering techniques, in the form of Posicast and user-selected time delay filters, are then utilized to eliminate specific frequency contents from the response of the multi-degree of freedom spring-mass chain. The input shaping approach is used to synthesize one or more band gaps in a homogenous lattice that can be designed to resemble Bragg-scattering in phononic crystals, as well as local resonance effects in acoustic metamaterials. The presence of the synthesized band gaps in the lattice’s dispersion behavior is validated using a spatiotemporal Fourier transform of the system’s impulse response as well as the frequency response of the end-to-end transfer function. Finally, an analysis of the control effort required to cancel the targeted system poles is carried out.

JED: a Java Essential Dynamics Program for comparative analysis of protein trajectories

BackgroundEssential Dynamics (ED) is a common application of principal component analysis (PCA) to extract biologically relevant motions from atomic trajectories of proteins. Covariance and correlation based PCA are two common approaches to determine PCA modes (eigenvectors) and their eigenvalues. Protein dynamics can be characterized in terms of Cartesian coordinates or internal distance pairs. In understanding protein dynamics, a comparison of trajectories taken from a set of proteins for similarity assessment provides insight into conserved mechanisms. Comprehensive software is needed to facilitate comparative-analysis with user-friendly features that are rooted in best practices from multivariate statistics.ResultsWe developed a Java based Essential Dynamics toolkit called JED to compare the ED from multiple protein trajectories. Trajectories from different simulations and different proteins can be pooled for comparative studies. JED implements Cartesian-based coordinates (cPCA) and internal distance pair coordinates (dpPCA) as options to construct covariance (Q) or correlation (R) matrices. Statistical methods are implemented for treating outliers, benchmarking sampling adequacy, characterizing the precision of Q and R, and reporting partial correlations. JED output results as text files that include transformed coordinates for aligned structures, several metrics that quantify protein mobility, PCA modes with their eigenvalues, and displacement vector (DV) projections onto the top principal modes. Pymol scripts together with PDB files allow movies of individual Q- and R-cPCA modes to be visualized, and the essential dynamics occurring within user-selected time scales. Subspaces defined by the top eigenvectors are compared using several statistical metrics to quantify similarity/overlap of high dimensional vector spaces. Free energy landscapes can be generated for both cPCA and dpPCA.ConclusionsJED offers a convenient toolkit that encourages best practices in applying multivariate statistics methods to perform comparative studies of essential dynamics over multiple proteins. For each protein, Cartesian coordinates or internal distance pairs can be employed over the entire structure or user-selected parts to quantify similarity/differences in mobility and correlations in dynamics to develop insight into protein structure/function relationships.

An Automated Liquid Chromatography-Mass Spectrometry Process to Determine Metabolic Stability Half-Life and Intrinsic Clearance of Drug Candidates by Substrate Depletion

An automated process is described for the detailed assessment of the in vitro metabolic stability properties of drug candidates in support of pharmaceutical property profiling. Compounds are incubated with liver microsomes using a robotic liquid handler. Aliquots are taken at various time points, and the resulting samples are quantitatively analyzed by liquid chromatography-mass spectrometry utilizing ion trap mass spectrometers to determine the amount of compound remaining. From these data metabolism rates can be calculated. A high degree of automation is achieved through custom software, which is employed for instrument setup, data processing, and results reporting. The assay setup is highly configurable, allowing for any combination of up to six user-selected time points, variable substrate concentration, and microsomes or other biologically active media. The data, based on relative substrate depletion, affords an estimate of metabolic stability through the calculation of half-life (t(1/2)) and intrinsic clearance, which are used to differentiate and rank order drug leads. In general, t(1/2) is the time necessary for the metabolism, following first-order kinetics, of 50% of the initial compound. Intrinsic clearance is the proportionality constant between rate of metabolism of a compound and its concentration at the enzyme site. Described here is the setup of the assay, and data from assay test compounds are presented.

Eliminating diathermy-induced artifacts during intraoperative monitoring of somatosensory-evoked potentials: A hardware solution

Somatosensory-evoked potentials (SEPs) recorded intraoperatively are often contaminated by artifacts arising from unipolar diathermy. This increases variability in serial SEP recordings and decreases the reliability of SEPs for intraoperative monitoring. Rejection of single sweeps on the basis of a voltage criterion can only partially prevent the inclusion of sweeps containing artifacts. We describe a low-cost hardware system that will halt SEP acquisition automatically before diathermy becomes active. Activation of the diathermy switch will halt SEP acquisition by sending a digital inhibit signal to the evoked potential machine via a fiberoptic cable. A timer delays the activation of the diathermy until the last sweep has been completed. To allow the electroencephalographic amplifiers to recover from any overload condition resulting from the high-voltage/high-frequency input during diathermy, acquisition is resumed only after a user-selectable time interval. The system was evaluated in 50 patients. It effectively interrupted SEP acquisition each time diathermy was used. By eliminating diathermy noise from the averaged waveforms, the system will allow evoked potential monitoring even during periods of intensive use of diathermy.

Feature enhanced ultrasonic imaging—Application of signal processing and analysis

Automatic systems with imaging capabilities are routinely used today for reliable inspection of nuclear reactor components. To provide additional quantitative measures to the operator for an objective decision, imaging capabilities are being augmented with a variety of signal processing techniques—feature enhanced imaging. These enhancements have included measures of the signal persistence and time-of-flight consistency which were found to be valuable for discriminating reflector types in boiling water reactor (BWR) recirculation piping welds; an ability to perform spatial averaging and filtering to minimize grain noise, particularly in cast steel components; and techniques for rapid display of images with user-selectable time gates to eliminate signals from spurious sources. The paper focuses on two systems developed recently with EPRI funding. The first is a field system for rapid scanning and display of ultrasonic inspection. The second is a class of personal computer (PC) based systems which have found increasing use because of their power and low cost. The PC-based systems are capable of acquiring, analyzing, imaging, and managing inspection data. Field experience with these systems is also discussed in this paper.

Rat rotation monitoring for pharmacology research

Much current neuropharmacological research describes drug site of action and effect in terms of rotational behavior in rats. Such studies at the National Institutes of Health led to the development of required instrumentation capabilities. The method developed for quantifying rotational behavior to the exclusion of other locomotor activity is presented. Such full turns counts can be output as mechanical counter inputs, computer inputs, user-selected time interval subtotals, summary totals, or a voltage proportional to cumulative count which provides turning-rate data when recorded on strip-chart. The latter two options are described herein.