Computer model calibration with large non-stationary spatial outputs: application to the calibration of a climate model

Bayesian calibration of computer models tunes unknown input parameters by comparing outputs with observations. For model outputs that are distributed over space, this becomes computationally expensive because of the output size. To overcome this challenge, we employ a basis representation of the model outputs and observations: we match these decompositions to carry out the calibration efficiently. In the second step, we incorporate the non-stationary behaviour, in terms of spatial variations of both variance and correlations, in the calibration. We insert two integrated nested Laplace approximation-stochastic partial differential equation parameters into the calibration. A synthetic example and a climate model illustration highlight the benefits of our approach

Zero-Energy Modes from Coalescing Andreev States in a Two-Dimensional Semiconductor-Superconductor Hybrid Platform

We investigate zero-bias conductance peaks that arise from coalescing subgap Andreev states, consistent with emerging Majorana zero modes, in hybrid semiconductor-superconductor wires defined in a two-dimensional InAs/Al heterostructure using top-down lithography and gating. The measurements indicate a hard superconducting gap, ballistic tunneling contact, and in-plane critical fields up to $3$~T. Top-down lithography allows complex geometries, branched structures, and straightforward scaling to multicomponent devices compared to structures made from assembled nanowires.Comment: Includes Supplementary Materia

Optimizing Cybersecurity Budgets with AttackSimulation

Modern organizations need effective ways to assess cybersecurity risk. Successful cyber attacks can result in data breaches, which may inflict significant loss of money, time, and public trust. Small businesses and non-profit organizations have limited resources to invest in cybersecurity controls and often do not have the in-house expertise to assess their risk. Cyber threat actors also vary in sophistication, motivation, and effectiveness. This paper builds on the previous work of Lerums et al., who presented an AnyLogic model for simulating aspects of a cyber attack and the efficacy of controls in a generic enterprise network. This paper argues that their model is an effective quantitative means of measuring the probability of success of a threat actor and implements two primary changes to increase the model\u27s accuracy. First, the authors modified the model\u27s inputs, allowing users to select threat actors based on the organization\u27s specific threat model. Threat actor effectiveness is evaluated based on publicly available breach data (in addition to security control efficacy), resulting in further refined attack success probabilities. Second, all three elements - threat effectiveness, control efficacy, and model variance - are computed and evaluated at each node to increase the estimation fidelity in place of pooled variance calculations. Visualization graphs, multiple simulation runs (up to 1 million), attack path customization, and code efficiency changes are also implemented. The result is a simulation tool that provides valuable insight to decision-makers and practitioners about where to most efficiently invest resources in their computing environment to increase cybersecurity posture. AttackSimulation and its source code are freely available on GitHub

Mental Health Matters: College Student Mental Health in the Twenty-First Century

Authors present the content, delivery, and benefits of a one-semester honors college lecture series on college student mental health

Detection limits of organic compounds achievable with intense, short-pulse lasers

Many organic molecules have strong absorption bands which can be accessed by ultraviolet short pulse lasers to produce efficient ionization. This resonant multiphoton ionization scheme has already been exploited as an ionization source in time-of-flight mass spectrometers used for environmental trace analysis. In the present work we quantify the ultimate potential of this technique by measuring absolute ion yields produced from the interaction of 267 nm femtosecond laser pulses with the organic molecules indole and toluene, and gases Xe, N2 and O2. Using multiphoton ionization cross sections extracted from these results, we show that the laser pulse parameters required for real-time detection of aromatic molecules at concentrations of one part per trillion in air and a limit of detection of a few attomoles are achievable with presently available commercial laser systems. The potential applications for the analysis of human breath, blood and tissue samples are discussed

An Inversion Method for Measuring Beta in Large Redshift Surveys

A precision method for determining the value of Beta= Omega_m^{0.6}/b, where b is the galaxy bias parameter, is presented. In contrast to other existing techniques that focus on estimating this quantity by measuring distortions in the redshift space galaxy-galaxy correlation function or power spectrum, this method removes the distortions by reconstructing the real space density field and determining the value of Beta that results in a symmetric signal. To remove the distortions, the method modifies the amplitudes of a Fourier plane-wave expansion of the survey data parameterized by Beta. This technique is not dependent on the small-angle/plane-parallel approximation and can make full use of large redshift survey data. It has been tested using simulations with four different cosmologies and returns the value of Beta to +/- 0.031, over a factor of two improvement over existing techniques.Comment: 16 pages including 6 figures Submitted to The Astrophysical Journa

Species and genus level resolution analysis of gut microbiota in Clostridium difficile patients following fecal microbiota transplantation

BACKGROUND: Clostridium difficile is an opportunistic human intestinal pathogen, and C. difficile infection (CDI) is one of the main causes of antibiotic-induced diarrhea and colitis. One successful approach to combat CDI, particularly recurrent form of CDI, is through transplantation of fecal microbiota from a healthy donor to the infected patient. In this study we investigated the distal gut microbial communities of three CDI patients before and after fecal microbiota transplantation, and we compared these communities to the composition of the donor’s fecal microbiota. We utilized phylogenetic Microbiota Array, high-throughput Illumina sequencing, and fluorescent in situ hybridization to profile microbiota composition down to the genus and species level resolution. RESULTS: The original patients’ microbiota had low diversity, was dominated by members of Gammaproteobacteria and Bacilli, and had low numbers of Clostridia and Bacteroidia. At the genus level, fecal samples of CDI patients were rich in members of the Lactobacillus, Streptococcus, and Enterobacter genera. In comparison, the donor community was dominated by Clostridia and had significantly higher diversity and evenness. The patients’ distal gut communities were completely transformed within 3 days following fecal transplantation, and these communities remained stable in each patient for at least 4 months. Despite compositional differences among recipients’ pre-treatment gut microbiota, the transplanted gut communities were highly similar among recipients post-transplantation, were indistinguishable from that of the donor, and were rich in members of Blautia, Coprococcus, and Faecalibacterium. In each case, the gut microbiota restoration led to a complete patient recovery and symptom alleviation. CONCLUSION: We conclude that C. difficile infection can be successfully treated by fecal microbiota transplantation and that this leads to stable transformation of the distal gut microbial community from the one abundant in aerotolerant species to that dominated by members of the Clostridia