Performance Of Various Implementations Research Articles

Bayesian workflow for time-varying transmission in stratified compartmental infectious disease transmission models.

Compartmental models that describe infectious disease transmission across subpopulations are central for assessing the impact of non-pharmaceutical interventions, behavioral changes and seasonal effects on the spread of respiratory infections. We present a Bayesian workflow for such models, including four features: (1) an adjustment for incomplete case ascertainment, (2) an adequate sampling distribution of laboratory-confirmed cases, (3) a flexible, time-varying transmission rate, and (4) a stratification by age group. Within the workflow, we benchmarked the performance of various implementations of two of these features (2 and 3). For the second feature, we used SARS-CoV-2 data from the canton of Geneva (Switzerland) and found that a quasi-Poisson distribution is the most suitable sampling distribution for describing the overdispersion in the observed laboratory-confirmed cases. For the third feature, we implemented three methods: Brownian motion, B-splines, and approximate Gaussian processes (aGP). We compared their performance in terms of the number of effective samples per second, and the error and sharpness in estimating the time-varying transmission rate over a selection of ordinary differential equation solvers and tuning parameters, using simulated seroprevalence and laboratory-confirmed case data. Even though all methods could recover the time-varying dynamics in the transmission rate accurately, we found that B-splines perform up to four and ten times faster than Brownian motion and aGPs, respectively. We validated the B-spline model with simulated age-stratified data. We applied this model to 2020 laboratory-confirmed SARS-CoV-2 cases and two seroprevalence studies from the canton of Geneva. This resulted in detailed estimates of the transmission rate over time and the case ascertainment. Our results illustrate the potential of the presented workflow including stratified transmission to estimate age-specific epidemiological parameters. The workflow is freely available in the R package HETTMO, and can be easily adapted and applied to other infectious diseases.

Visual-Inertial Odometry Using High Flying Altitude Drone Datasets

Positioning of unoccupied aerial systems (UAS, drones) is predominantly based on Global Navigation Satellite Systems (GNSS). Due to potential signal disruptions, redundant positioning systems are needed for reliable operation. The objective of this study was to implement and assess a redundant positioning system for high flying altitude drone operation based on visual-inertial odometry (VIO). A new sensor suite with stereo cameras and an inertial measurement unit (IMU) was developed, and a state-of-the-art VIO algorithm, VINS-Fusion, was used for localisation. Empirical testing of the system was carried out at flying altitudes of 40–100 m, which cover the common flight altitude range of outdoor drone operations. The performance of various implementations was studied, including stereo-visual-odometry (stereo-VO), monocular-visual-inertial-odometry (mono-VIO) and stereo-visual-inertial-odometry (stereo-VIO). The stereo-VIO provided the best results; the flight altitude of 40–60 m was the most optimal for the stereo baseline of 30 cm. The best positioning accuracy was 2.186 m for a 800 m-long trajectory. The performance of the stereo-VO degraded with the increasing flight altitude due to the degrading base-to-height ratio. The mono-VIO provided acceptable results, although it did not reach the performance level of the stereo-VIO. This work presented new hardware and research results on localisation algorithms for high flying altitude drones that are of great importance since the use of autonomous drones and beyond visual line-of-sight flying are increasing and will require redundant positioning solutions that compensate for potential disruptions in GNSS positioning. The data collected in this study are published for analysis and further studies.

An integrated model for bead-based immunoassays

Bead-based immunoassays have shown great promise for rapid and sensitive protein quantification. However, there still lacks holistic understanding of assay performance that can inform assay design and optimization. In this paper, we present an integrated mathematical model for surface coverage bead-based assays. This model examines the building blocks of surface coverage assays, including heterogeneous binding of analyte molecules on bead or sensor surfaces, attachment of bead labels to sensor surfaces, and generation of electrochemical current by bead labels. To demonstrate and validate this model, we analyze a semi-homogeneous bead-based electronic enzyme-linked immunosorbent assay and find that experimental results agree with various model predictions. We show that the model can provide design guidance for choice of various assay parameters including bead size, bead number, antibody affinity and assay time, and provide a perspective to reconcile the performance of various implementations of surface coverage assays.

Performance Evaluation of Efficient XOR Structures in Quantum-Dot Cellular Automata (QCA)

Quantum-dot cellular automaton (QCA) is an emerging, promising, future generation nanoelectronic computational architecture that encodes binary information as electronic charge configuration of a cell. It is a digital logic architecture that uses single electrons in arrays of quantum dots to perform binary operations. Fundamental unit in building of QCA circuits is a QCA cell. A QCA cell is an elementary building block which can be used to build basic gates and logic devices in QCA architectures. This paper evaluates the performance of various implementations of QCA based XOR gates and proposes various novel layouts with better performance parameters. We presented the various QCA circuit design methodology for XOR gate. These layouts show less number of crossovers and lesser cell count as compared to the conventional layouts already present in the literature. These design topologies have special functions in communication based circuit applications. They are particularly useful in phase detectors in digital circuits, arithmetic operations and error detection & correction circuits. The comparison of various circuit designs is also given. The proposed designs can be effectively used to realize more complex circuits. The simulations in the present work have been carried out using QCADesigner tool.

Minimizing binary functions with simulated annealing algorithm with applications to binary tomography

The minimization of binary functions finds many applications in practice, and can be solved by the simulated annealing (SA) algorithm. However, the SA algorithm is designed for general combinatorial problems, not specifically for binary problems. Consequently, a direct application of the SA algorithm might not provide optimal performance and efficiency. Therefore, this study specifically investigated the performance of various implementations of the SA algorithm when applied to binary functions. Results obtained in this investigation demonstrated that 1) the SA algorithm can reliably minimize difficult binary functions, 2) a simple technique, analogous to the local search technique used in minimizing continuous functions, can exploit the special structure of binary problems and significantly improve the solution with negligible computational cost, and 3) this technique effectively reduces computational cost while maintaining reconstruction fidelity in binary tomography problems. This study also developed two classes of binary functions to represent the typical challenges encountered in minimization.

Temporal Compression Of Speech: An Evaluation

Efficient browsing of speech recordings is problematic. The linear nature of speech, coupled with the lack of abstraction that the medium affords, means that listeners have to listen to long segments of a recording to locate points of interest. We explore temporal compression algorithms that attempt to reduce the amount of time users require to listen to speech recordings, while retaining the important content. This paper implements two main approaches to temporal compression: artificial speech rate alteration (speed-up) and unimportant segment removal (excision). We evaluate the effectiveness of these approaches by having listeners rate comprehension and listening effort for different types of temporal compression. For different compression levels, we compare performance of various implementations of speed-up and excision as well as techniques based on semantic features and acoustic features. Our results indicate that listeners prefer low compression levels, excision over speed-up, and algorithms based on semantic rather than acoustic features. Finally, listeners were negative about hybrid algorithms that used speed-up to indicate missing regions in an excised recording.

Interaction of neutral and zwitterionic glycine with Zn2+ in gas phase:ab initio and SIBFA molecular mechanics calculations

The interaction of Zn2+ with glycine (Gly) in the gas phase is studied by a combination of ab initio and molecular mechanics techniques. The structures and energetics of the various isomers of the Gly–Zn2+ complex are first established via high-level ab initio calculations. Two low-energy isomers are characterized: one in which the metal ion interacts with the carboxylate end of zwitterionic glycine, and another in which it chelates the amino nitrogen and the carbonyl oygen of neutral glycine. These calculations lead to the first accurate value of the gas-phase affinity of glycine for Zn2+. Ab initio calculations were also used to evaluate the performance of various implementations of the SIBFA force field. To assess the extent of transferability of the distributed multipoles and polarizabilities used in the SIBFA computations, two approaches are followed. In the first, approach (a), these quantities are extracted from the ab initio Hartree–Fock wave functions of glycine or its zwitterion in its entirety, and for each individual Zn2+-binding conformation. In the second, approach (b), they are assembled from the appropriate constitutive fragments, namely methylamine and formic acid for neutral glycine, and protonated methylamine and formate for the zwitterion; they undergo the appropriate vector or matrix rotation to be assembled in the conformation studied. The values of the Zn2+–glycine interaction energies are compared to those resulting from ab initio SCF and MP2 computations using both the all-electron 6-311+G(2d,2p) basis set and an effective core potential together with the valence CEP 4-31G(2d) basis set. Approach (a) values closely reproduce the ab initio ones, both in terms of the total interaction energies and of the individual components. Approach (b) can provide a similar match to ab initio interaction energies as does approach (a), provided that the two constitutive Gly building blocks are considered as separate entities having mutual interactions that are computed simultaneously with those occurring with Zn2+. Thus, the supermolecule is treated as a three-body rather than a two-body system. These results indicate that the current implementation of the SIBFA force field should be adequate to undertake accurate studies on zinc metallopeptides. © 2000 John Wiley & Sons, Inc. J Comput Chem 21: 963–973, 2000

Implementing Data Envelopment Analysis: Primal Or Dual?

The computational performance of various implementations of a data envelopment analysis model are investigated. These include primal and dual versions of both single-stage (∊ represented as a small numerical magnitude) and two-stage (∊ not explicitly represented) approaches, It is found, contrary to widely held belief, that the implementation based on the primal DEA model is faster than that based on the dual model, which has many fewer constraints. Some reasons for this unexpected finding are suggested.