Software models: A Bayesian approach to parameter estimation in the Jelenski-Moranda software reliability model

Maximum likelihood estimation procedures for the Jelinski-Moranda software reliability model often give misleading answers. A reparameterization and a Bayesian analysis eliminate some of the problems incurred by MLE methods and often give better predictions on sets of real and simulated data. Practical difficulties in estimating the initial number of errors N and the failure rate of each error phi by the method of maximum likelihood are: N, the MLE of N, is occasionally infinite (i.e., the routines for calculating N and phi do not converge). It is shown that N is finite sub i only if the regression line of the interevent times t sub i vs. i has positive slope. A serious problem is that often N approximates n, the sample size, and sometimes N = n. Thus the MLE predicts that the program is perfect even when it is far from being so. Only when almost all failures have been removed can N and phi be trusted near the end of debugging

A Bayesian modification to the Jelinski-Moranda software reliability growth model

The Jelinski-Moranda (JM) model for software reliability was examined. It is suggested that a major reason for the poor results given by this model is the poor performance of the maximum likelihood method (ML) of parameter estimation. A reparameterization and Bayesian analysis, involving a slight modelling change, are proposed. It is shown that this new Bayesian-Jelinski-Moranda model (BJM) is mathematically quite tractable, and several metrics of interest to practitioners are obtained. The BJM and JM models are compared by using several sets of real software failure data collected and in all cases the BJM model gives superior reliability predictions. A change in the assumption which underlay both models to present the debugging process more accurately is discussed

Completely monotone regression estimates of software failure rates

A method for estimating the present failure rate of a program is presented. A crude nonparameter estimate of the failure rate function is obtained from past failure times. This estimate is then smoothed by fitting a completely monotonic function, which is the solution of a quadratic programming problem. The value of the smoothed function at present time is used as the estimate of present failure rate. Results of a Monte Carlo study of performance are given

Quantum enhanced X-ray detection

We present the first experimental demonstration of quantum-enhanced detection at x-ray wavelengths. We show that x-ray pairs that are generated by spontaneous down-conversion can be used for the generation of heralded x-ray photons and measure directly the sub-Poissonian statistics of the single photons by using photon number resolving detectors. We utilize the properties of the strong time-energy correlations of the down converted photons to demonstrate the ability to improve the visibility and the signal-to-noise ratio of an image with a small number of photons in an environment with a noise level that is higher than the signal by many orders of magnitude. In our work we demonstrate a new protocol for the measurement of quantum effects with x-rays using advantages such as background free measurements that the x-ray regime offers for experiments aiming at testing fundamental concepts in quantum optics.Comment: 12 page

Microscopic parameters of the van der Waals CrSBr antiferromagnet from microwave absorption experiments

Microwave absorption experiments employing a phase-sensitive external resistive detection are performed for a topical van der Waals antiferromagnet CrSBr. The field dependence of two resonance modes is measured in an applied field parallel to the three principal crystallographic directions, revealing anisotropies and magnetic transitions in this material. To account for the observed results, we formulate a microscopic spin model with a bi-axial single-ion anisotropy and inter-plane exchange. Theoretical calculations give an excellent description of full magnon spectra enabling us to precisely determine microscopic interaction parameters for CrSBr.Comment: includes a supplementary information documen

Antimonene-modified screen-printed carbon nanofibers electrode for enhanced electroanalytical response of metal ions.

A two-dimensional (2D) Sb-modified screen-printed carbon nanofibers electrode (2D Sbexf-SPCNFE) was developed to improve the stripping voltammetric determination of Cd(II) and Pb(II), taking advantage of the synergistic effect between the two nanomaterials. The surface morphology of the 2D Sbexf-SPCNFE was investigated by scanning electron microscopy, energy-dispersive X-ray spectroscopy, and Raman spectroscopy. The analytical performance of 2D Sbexf-SPCNFE was compared to those presented by screen-printed carbon electrodes modified with 2D Sbexf (2D Sbexf-SPCE) and the corresponding bare electrodes: screen-printed carbon nanofibers electrode (SPCNFEbare) and screen-printed carbon electrode (SPCEbare). After optimizing the experimental conditions, the 2D Sbexf-SPCNFE exhibited much better analytical parameters compared to the other assessed sensors. Analysis in 0.01 mol L−1 HCl (pH = 2) using 2D Sbexf-SPCNFE showed excellent linear behavior in the concentration range of 2.9 to 85.0 µg L−1 and 0.3 to 82.0 µg L−1 for Cd(II) and Pb(II), respectively. The limits of detection after 240 s deposition time for Cd(II) and Pb(II) were 0.9 and 0.1 µg L−1, and sensitivities between 1.5 and 3 times higher than those displayed by SPCEbare, SPCNFEbare, and 2D Sbexf-SPCE were obtained. Finally, the 2D Sbexf-SPCNFE was successfully applied to the determination of Cd(II) and Pb(II) traces in a certified estuarine water sample

Antimony nanomaterials modified screen-printed electrodes for the voltammetric determination of metal ions

Exfoliated β-Sb or two dimensional (2D) antimonene-based modified screen-printed electrode (2D Sb-SPCE), prepared by drop-casting of an exfoliated layered β-antimony (2D Sb) suspension, was used for the simultaneous determination of Pb(II) and Cd(II) by differential pulse anodic stripping voltammetry (DPASV). 2D Sb-SPCE was characterized by microscopic and analytical techniques, and compared not only to bare SPCE but also to layered antimony chalcogenides based-sensors. Both Sb2S3 and Sb2Se3 have an isomorphous tubular one-dimensional (1D) crystal structure, whereas Sb2Te3 and monoelement β-Sb have a 2D layered structure. Under optimized conditions, 2D Sb-SPCE displays an excellent analytical performance with detection limits of 0.3 and 2.7 μg L−1 for Pb(II) and Cd(II), respectively, and a linear response from 1.1 to 128.3 µg L−1 for Pb(II) and from 9.1 to 132.7 µg L−1 for Cd(II). Moreover, 2D Sb-SPCE was successfully applied for the DPASV determination of Pb(II) and Cd(II) in tap water, achieving statistically comparable results to those provided by ICP-MS measurements

Variant-specific inflation factors for assessing population stratification at the phenotypic variance level

In modern Whole Genome Sequencing (WGS) epidemiological studies, participant-level data from multiple studies are often pooled and results are obtained from a single analysis. We consider the impact of differential phenotype variances by study, which we term \u27variance stratification\u27. Unaccounted for, variance stratification can lead to both decreased statistical power, and increased false positives rates, depending on how allele frequencies, sample sizes, and phenotypic variances vary across the studies that are pooled. We develop a procedure to compute variant-specific inflation factors, and show how it can be used for diagnosis of genetic association analyses on pooled individual level data from multiple studies. We describe a WGS-appropriate analysis approach, implemented in freely-available software, which allows study-specific variances and thereby improves performance in practice. We illustrate the variance stratification problem, its solutions, and the proposed diagnostic procedure, in simulations and in data from the Trans-Omics for Precision Medicine Whole Genome Sequencing Program (TOPMed), used in association tests for hemoglobin concentrations and BMI

Enhanced voltammetric performance of sensors based on oxidized 2D layered black phosphorus

The exceptional properties of 2D layered black phosphorus (BP) make it a promising candidate for electrochemical sensing applications and, even though BP is considered unstable and tends to degrade by the presence of oxygen and moisture, its oxidation can be beneficial in some situations. In this work, we present an unequivocal demonstration that the exposition of BP-based working electrodes to normal ambient conditions can indeed be advantageous, leading to an enhancement of voltammetric sensing applications. This point was proved using a BP modified screen-printed carbon electrode (BP-SPCE) for the voltammetric determination of dopamine (DA) as a model target analyte. Oxidized BP-SPCE (up to 35% of PxOy at the surface) presented an enhanced analytical performance with a 5-fold and 2-fold increase in sensitivity, as compared to bare-SPCE and non-oxidized BP-SPCE stored in anhydrous atmosphere, respectively. Good detection limit, repeatability, reproducibility, stability, selectivity, and accuracy were also achieved. Overall, the results presented herein display the prominent possibilities of preparing and working with BP based-sensors in normal ambient settings and showcase their implementation under physiological conditions

Heat-Up Colloidal Synthesis of Shape-Controlled Cu-Se-S Nanostructures—Role of Precursor and Surfactant Reactivity and Performance in N2 Electroreduction

Copper selenide-sulfide nanostructures were synthesized using metal-organic chemical routes in the presence of Cu- and Se-precursors as well as S-containing compounds. Our goal was first to examine if the initial Cu/Se 1:1 molar proportion in the starting reagents would always lead to equiatomic composition in the final product, depending on other synthesis parameters which affect the reagents reactivity. Such reaction conditions were the types of precursors, surfactants and other reagents, as well as the synthesis temperature. The use of ‘hot-injection’ processes was avoided, focusing on ‘non-injection’ ones; that is, only heat-up protocols were employed, which have the advantage of simple operation and scalability. All reagents were mixed at room temperature followed by further heating to a selected high temperature. It was found that for samples with particles of bigger size and anisotropic shape the CuSe composition was favored, whereas particles with smaller size and spherical shape possessed a Cu2−xSe phase, especially when no sulfur was present. Apart from elemental Se, Al2Se3 was used as an efficient selenium source for the first time for the acquisition of copper selenide nanostructures. The use of dodecanethiol in the presence of trioctylphosphine and elemental Se promoted the incorporation of sulfur in the materials crystal lattice, leading to Cu-Se-S compositions. A variety of techniques were used to characterize the formed nanomaterials such as XRD, TEM, HRTEM, STEM-EDX, AFM and UV-Vis-NIR. Promising results, especially for thin anisotropic nanoplates for use as electrocatalysts in nitrogen reduction reaction (NRR), were obtained